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Introducing your copilot for the web: AI-powered Bing and Microsoft Edge Aprenda Sobre Chat Gpt Bing Bard AI Blog

# Bing Chat GPT: Your AI-Powered Copilot for the Web
## Introduction
– Overview of AI-powered Bing and Microsoft Edge
– Explanation of the concept of leads in digital marketing

## Understanding Organic Leads
– What are organic leads?
– How do they differ from paid leads?
– Why are organic leads important for your business?

## Generating Organic Leads
– Optimizing your website for search engines
– Creating high-quality and engaging content
– Leveraging social media marketing
– Building an email list

## Optimizing Your Website for Search Engines
– Importance of ranking high on search engine results pages
– On-page optimization techniques for SEO
– Tips for creating SEO-friendly content

## Creating High-Quality and Engaging Content
– Importance of creating valuable content for your audience
– Tips for creating engaging content
– Importance of multimedia content

## Leveraging Social Media Marketing
– Overview of social media platforms
– Tips for maximizing your social media presence
– Importance of social media engagement

## Building an Email List
– Importance of email marketing
– Tips for building an email list
– How to craft effective email campaigns

## Conclusion
– Recap of key takeaways
– Emphasis on the importance of organic leads

## FAQ
1. What is the difference between organic and paid leads?
2. How long does it take to see results from SEO?
3. How do I know which keywords to target for my SEO strategy?
4. What are some best practices for social media marketing?
5. How can I improve my email open rates?

br>Reinventing search with a new AI-powered Microsoft Bing and Edge, your copilot for the web. Today, we launched an all new, AI-powered Bing search engine and Edge browser, available in preview now, to deliver better search, more complete answers, a new chat experience and the ability to generate content. We think of these tools as an AI copilot for the web.

To learn more visit:

Video Chapters:
0:00 – Introduction
0:13 – Satya Introduction
12:20 – Yusuf Introduction
39:00 – Sam Introduction
41:00 – Dena Introduction
46:10 – Sarah Introduction
53:50 – Yusuf Conclusion

Este vídeo foi indexado através do Youtube link da fonte
bing chat gpt ,

Bing,Edge,Microsoft,AI,copilot,chat,search,answers,search engine,AI copilot ,

https://www.youtubepp.com/watch?v=rOeRWRJ16yY ,

[MUSIC] SATYA NADELLA: Hi, everyone. Welcome. It’s great to see all of you in Seattle in person. We have an unbelievable show. I see Scott Guthrie even wore his red shirt. We welcome you to the Azure Kubernetes Container Service 2023 launch. No, don’t worry. We’ll have some fun.

Scott is not coming up to show you code onscreen anytime soon, but look, it’s an exciting time in tech. The broad contours of this next platform are just getting clearer and clearer each day. The advances, what’s possible. That’s what obviously excites us in our industry. But they’re also grounded

In what’s happening in the broader world. There’s no question. There are enormous challenges out there. In fact, it reminds me and I’ve spoken about this before of the very founding of Microsoft in 1975. In fact, when the popular electronics cover came out with the Altair, which of course our founders

Picked up and ran with it and created essentially what’s the software industry as we know of it today. That same week, Newsweek had a cover with President Carter trying to fight off the three-headed monster of inflation, recession, and an energy crisis. Today you’d have something similar.

You will have AI on one cover and then we’ll have those three challenges plus for good measure, we can add a few more. We, as Microsoft, we as the tech industry have to really ground ourselves in how do we relate one to the other? In other words, can we use technology to overcome

The challenges that people and organizations and countries face? That’s really the pursuit here. In that context, I would say, I just want to share a couple of anecdotes which gives me great hope. Quite honestly, it gives me personally a lot of satisfaction around working at Microsoft, working in this industry to

Push the state of the art of technology. The first one, obviously when Sam and his team late last year launched ChatGPT, that’s the only thing anybody your friends and family wanted to talk about throughout the holidays. It was just crazy house. It was like the Mosaic moment. The closest we’ve come.

It’s been 30 years now since when Mosaic launch, which I distinctly remember. It was very exciting time. I went on a holiday first and then I was in the first week of January I was in India. On Jan 1st, I look at my news feed and I see

This tweet that Andrej Karpathy put out. Who is our ex OpenAI and Tesla, and is now an independent AI developer. He had this thing about the product that really he was most excited about the previous year was GitHub Copilot and he was saying how 80 percent of

His code was being generated by this, I would say first at scale product built on NLM technology. This doesn’t mean he’s 80 percent somehow not doing his work. In fact, he’s getting so much more leverage. In fact, recently we crossed 100 million developers on GitHub. Think about this. There are

100 million developers on GitHub. If we can improve their productivity, just like how Andrej was able to observe. Then let’s say in the next decade we double that number, may be double it again. We get close to a half a billion developers, what economic opportunity it would create.

Because there is not a meeting that I go to today with any CEO, CXO of any organization who’s not looking for more software developers, more digital skills. That’s the currency in every sector of the economy, in every country of the world. That’s the opportunity we have to be able to take

This technology and make a difference. But then the next day I went to Mumbai and then I saw this demo. This was just for me, the most profound thing that I’ve seen in a long time. The demo was actually built by the Ministry of Electronics in India because they are building

Out a digital public goods. Their idea is look, India has got multiple official languages and they wanted to democratize essentially access to language translation. They’re building it out as a digital public good. In fact, Microsoft and Azure and Microsoft Research are all involved in that project. This is basically speech-to-text,

Text-to-speech across all of the languages in India. They showed me this demo where a farmer speaking in Hindi expresses a pretty complex thought about how he had heard about some government program and wants to apply for a subsidy that he thinks he’s eligible for. It’s a pretty complex prompt query. There’s technology,

That’s a good job. It goes to the bot, recognizes the speech, comes back and says, you know what? You should go to this portal, fill out these forms, then you’ll get your subsidy. He says, look, I’m not going to go into any portal. I’m not going to fill out any forms,

Can you help me? He does it. Then I was told that a developer said, you know what? That is Daisy Ching a model that was trained on all of the documents of the government of India using GPT with this speech recognition software. Basically two models coming together to really

Help a rural farmer in India trying to get access to a government program. Look, I grew up in India. I dreamt every day that someday the industrial revolution will get evenly distributed across the world. Here I was, seeing something so profound, something that is developed by the folks at

OpenAI in the West Coast of the United States a few months earlier, used by a developer locally to have an impact on a rural farmer. That to me is what gives me meaning and I think gives us all meaning in our industry. It is just fantastic to see that.

Now of course we’ve got to scale it and scale it with a real understanding that we can break things. It’s about being also clear-eyed about the unintended consequences of any new technology. In fact, that’s why way back in 2016 is when we came out with the AI principles.

You have both we as Microsoft and our partners at OpenAI, deeply care about this. In fact, the entire genesis of OpenAI is from that foundation. We built these principles, but we’ve not just put those principles as a document, but we’ve been practicing it because that’s the only way

Technology gets better in this particular case. When you’re talking about AI, it’s about alignment with human preferences and societal norms and you’re not going to do that in a lab. You have to do that out there in the world. It starts by the way with design decision ones makes.

When you think about AI, you can have the human in the loop, you can hear how the human on the loop or you can have the human out of the loop. Those are decisions we as product makers build, build into the products. Whenever we have come up with

Some new things and new models, we in fact put a premium on human agency. When you think about these generative AI models, remember one thing, they are prompted to do things. The prompting comes from a human being. We get to in fact help them prompt.

We get them to take the draft that gets generated. They should review the draft. They get to review the draft, they get to approve the draft using judgment. We want to give them as many perspectives, as many ways to regenerate. We want to take even just the design of AI products as

A first-class construct and build that into our products. But that’s not sufficient, we realize that. You have to write at the pre-training stage when it comes to the data, the pre-training itself, the model itself has to be safe. The safety system around the model, the application context, all will matter.

We absolutely, and you’ll see that today, we take all of that as first-class things which we want to reduce, not just to principles but to engineering practice. Such that we can build AI that’s more aligned with human values, more aligned with what our preferences are, both individually and as a society.

What is it that we should do and what should we build? I think that this technology is going to reshape pretty much every software category. We know, we’ve seen that and we’ve solved. If you think about the web, we’ve had what? Three at least very distinct platform shifts that have shaped the web.

The web was born on the PC and the server and then it evolved with mobile and Cloud. Now the question is, how is AI going to reshape the web? Each time in each one of those phases, some real foundational technology layers, sometimes I describe them as these organizational layers of technology, were born.

The browser was the first one. Without the browser, the web would have not been as popular as it is today. Same thing with search. Search organized the web. Then when it came to the mobile generation and mobile and Cloud, in fact these super apps, especially outside of the United States around messaging,

Became the way people consume the web. We also had app stores. The question is, what are the constructs? What are the organizing layers going forward? You’ll see some of that today. We think there are two things that are emerging. One is this conversational intelligent agents. I think they’re going to be things that

We’re going to have everywhere we go. All computer interaction is going to be mediated with an agent helping you. In fact, we’re going to have this notion of a co-pilot that’s going to be there across every application canvas inside of an operating system shell in a browser.

We want to show you some of this innovation starting with how it’s going to reshape the largest software category on planet Earth, which I’ve been working on for a long time, which we’re very, very excited about, Search. It’s a new day in Search. It’s a new paradigm for search.

Rapid innovation is going to come. In fact, a race starts today in terms of what you can expect and we’re going to move. We’re going to move fast. For us every day, we want to bring out new things. Most importantly, we want to have a lot of fun innovating

Again in Search because it’s high time. With that, let me turn it over to Yusuf. YUSUF MEHDI: Thanks, Satya. It’s great to be here with all of you today. We’ve been working on something we think is pretty special and we’re just eager to share it with you. In my time at the company,

I’ve been lucky to witness a few important moments. I think this might be another one of those. We believe as Satya said that we can improve the way billions of people can benefit from the Internet. Created by really an amazing team across Microsoft, from the core web engineering folks in Michael’s group,

To the brilliant folks at Microsoft Research, to the tireless people that work on the Azure AI supercomputer, we think of it humbly as the next-generation of search and browsing. Infused with AI and assembled as an integrated experience, we’re going to re-imagine the search engine, the web browser, and new chat experiences

Into something we think of as your copilot for the web. Now, copilot is a critical word because we believe in the empowering nature of AI in which you, the individual, are in charge. Now what it is, is not even as important as what it represents. That is for us an aspiration

To unlock the joy of discovery, the wonder of creation, and that feeling of empowerment from being able to harness the world’s knowledge. At the center of this new co-pilot experience is an all new Bing search engine and Edge web browser, and it’s going to do four things for you.

First, it’s a better search. It’s the search you know and love but it’s better because it’s AI powered. Second, not only does it give you the search results, but it will actually answer your questions. Third, we’re going to make it incredibly easy to use. We’re going to let you chat, we’re going to

Let you just talk to it naturally. Last, when you need that spark of creativity, Bing can generate content for you automatically to help you get started. Let’s talk a little bit about the opportunity in search and why we believe we’re at the start of the next generation.

No. Sorry about that, we’re on to the next generation. All seriousness, with over 10 billion queries a day, we all know the search engine is an incredible tool. We do. Yet as the web has grown, we’ve run into challenges. People are overwhelmed increasingly with too many links when they’re

Trying to find simple answers. But 40 percent of the time people click on search links, they click back immediately. That’s a sign they’re not finding what they want. Most notably, we have to adapt to search versus the other way around. It turns out search works better if you give it fewer keywords.

You might be surprised to know that 75 percent of all searches are three key words or less. But come on, we shouldn’t be surprised. Search has remained fundamentally the same since the last major inflection. When we moved from a directory approach to search to an algorithmic approach to search.

The user experience and the approach underlying are essentially the same as 20 years ago. Few keywords and you get millions of links. But as the world around us has changed, the way people use search has changed, we all know this. People are trying to use search to do

More than it was designed to do. To illustrate that let’s just look at a breakdown of search queries by type to understand this point. Search querries today you can bucket them into serve three types of categories. The first are what we call navigational. This is people searching for a website.

When you need to renew your driver’s license, you need to go to the DMV. When you want to tell your friend about that great pizza place, you send them the WebLink. That’s what search was designed to do, and it does it super well. The second, third of categories are what we call informational.

These are things like what’s the weather forecast? What was last night sports scores? What’s today’s stock price? Search works great for that. But for anything more complex, like hey, I got to pick up this love seat at the store, is it going to fit in the back of my car?

Search is going to fall short on that. Then the final third, we’re back into what we call everything else. These are typically more deep research in nature. This is things like trip planning or complex shopping. An example query here that people are putting in is, hey,

Can you recommend a five-day itinerary to Mexico City? For these, search falls far short of the desired goal. What this means if you just do the simple math, it means that roughly half of all searches aren’t delivering the job that people want. If you go on that 10 million queries,

It means that every second, 50,000 people searches potentially go unanswered. This is why we believe it’s time for a new approach in search. For the billions of queries that are going unanswered, we’ve seen new attempts to try address the problem. As you all know, there are vertical search attempts.

Amazon has done a better job for shopping. YouTube is great for video. Reddit is a great place to come get advice. The benefits of search are well-known. It’s fast, it’s timely, and there’s a great business model. Then more recently they’ve been another vector, more disruptive ideas like leveraging AI to

Answer questions directly and to generate content. These are amazing as well, and they show what’s possible. But what if you could get the two to come together? Not only would you get two things in one, but we think you could actually solve problems in each.

We think you could get to something that is really one plus one equals three. We’ve done that with the new Bing. I want to share with you four technical breakthroughs the Team has achieved to make this come to life. First, through our fantastic partnership with SAM and the brilliant team at OpenAI,

I’m excited to announce that Bing is running on a new next-generation large language model. One that is much more powerful than ChatGPT, and one that is customized specifically for search. It’s unlike anything you’ve had a chance to play with and we can’t wait for you to try it.

Second, we’ve developed a proprietary way of working with OpenAI that allows us to best leverage the power. We call this collection of capabilities and techniques the Prometheus model. The core idea here is that both at training and at runtime, we engage with the OpenAI model more intelligently through our knowledge of the web,

Via the Bing index and some special query techniques. We’re going to dig into this a little bit more later, but the benefits are the following. First, we can improve the relevancy of answers by feeding in and better tuning queries given our understanding of the web search index. Next, we can annotate

The answers with specific web links and citations. We can get you more up-to-date information because search crawls the web every day. We can improve understanding of geolocation. Finally, we can increase the safety of the answers as well by catching queries at initiation and then checking that again at the delivery of an answer.

Next, we’ve been making steady improvements on the Bing algorithms for years. We test these with independent judges. The shows that are search experience is on par or better than any search experience when you take away the brands. But a few weeks ago, something special happened. We applied the AI model to

Our core search ranking engine and we saw the largest jump in relevance in two decades. We believe we can continue to drive breakthroughs as we improve the models. Then finally, we are re-imagining how you interact with all of these capabilities across search, browser, and chat by pulling them into a unified experience.

I want you to think about search coming together with answers, search coming together with chat, and search coming together with the browser. As we all know and as the folks at OpenAI taught us, the user experience is as important as the underlying technical platform. Enough talk.

You guys ready to see it in action? Let’s show you how we’re going to enable the Copilot for the web. Now before I do, I want to call out two things for clarity. First, because there’s so much I’m going to show you until you don’t have to watch me type every search.

I recorded these searches live just yesterday. Second, in case there are skeptics in the room, you’re going to get a chance to play with it directly, put your hands on it and type the same queries as well as your own favorites right after this presentation. You’re all familiar with search,

So I’m not going to show you a search. I’m going to share what you can’t do with today’s search. I’m going to focus on answers, chat, and the ability to create. But first let me introduce you to the new Bing homepage. You’re going to notice some subtle but important changes.

First, we have an expanded search box capable of accepting up to 1,000 characters. Because now Bing works with natural language. You saw a little hint to chat, which I’m going to get back to in a second. Now want to set up the first search scenario. My daughter and I, we both love art.

She studied art at school and I’d like to stay connected with her on our mutual passion. Last semester, she was learning about Mexican painters. I’d like to get a quick summary of the most influential Mexican painters and the works to learn a bit more about the topic.

If I type the full query of what I’d like to know in today’s search, here’s what I get. I’ll just type in, compare the most influential Mexican artists and their top paintings, and you’ll get what you expect. In some links. It’s fine, but we can do better.

Let’s try this now in the new Bing. What you’ll see as we pull up, is first, you see the web results here on the left, but then on the right, you start to see how we start to compile the answer. What you get here now is we have

The ability to highlight these web links. We can annotate the results. That’s because we’re able to go in and apply our index onto the answers there. In other words, the answers and the search on one page has saved me a huge amount of time. This gives you a little bit of a

Sense of what you can do. Now you’ve seen some of this before, you might say, Hey, I’ve seen some of these. Let’s show you how we can do some additional things. I’m going to show you another query. Where we use the timeliness of search. Let’s go ahead and ask about events in

Scottsdale during the Super Bowl. What you’ll see is we get back and answer here, where we have events and we’re able to do that because Bing cross web. Notice how we can find not only that the Super Bowl was played in Glendale on the 12th, but then there are events like

Cardi B Super Bowl party that’s on the 10th also shows up. We were able to pull these things together. You start to get a sense of how we can build on what’s today with the Bing index. Now I’m going to show you a few more of these types of answers quickly,

So you can get a sense of the power, and the time savings from Bing. When I’m running an errand, like the example I gave to you earlier, I can ask Bing to determine if that new loveseat from IKEA is going to fit in the back of my Honda Odyssey.

What you’ll see is they can actually find the dimensions of the loveseat, the interior space of the car, and then make an estimation as to whether it will fit. In this case, I’m choosing an example of where Bing does not know the answer. We know that we can’t be definitive about it.

The reason I’m doing that is because we know we won’t be able to answer every question, every time. But Bing can still provide some helpful information as you can see on this answer. We also know we’ll make our share of mistakes, and Bing rule this out. We’ve added a quick feedback button

At the top of every search, so that you can give us feedback and we can learn. Another example, when I’m shopping, I can ask Bing to search, find, and compare the top three selling pet vacuums listing the pros and cons. Look how great this answer is.

It has all three of the products I’m looking for, super-helpful pros and cons. Stop and think. If you had to compile that, how much time that would take you to do? As you can see at the top of the page, we still have the advertising in this example,

Because we know when people are shopping, those ads are helpful. Finally on this one, if I’m cooking, and I realize I’ve forgotten a key ingredient, in this case, e.g. eggs for my cake recipe, Bing can not only find the egg substitutes, it can get me the exact amount for each ingredient.

Take a look at this. I love this. You can actually see e.g. if you go with vinegar and baking soda, the cake is lighter and more fluffy. These are just little helpful tips that everyday help make your life a little better. These are just some examples.

Then you can start to get a sense of how, with answers. We go far beyond what you can do with search day. We can actually help you get what you want to get done. Now let me tell you about how Bing goes further to help you with particularly complex questions for

Which there is not a precise answer. I wanted to introduce to you the new chat experience in Bing. I think of this as search with your own personal helper, to help you refine your query until you get exactly what you’re looking for. This comes in handy for activities

Like trip planning and shopping research. Let’s start with shopping. I’m going to look for 65 inch TV. Again, you see ads at the top, the result of the links on the left, and the answer is here on the right. You can pick whichever you’d like. We’ll give you a good set of answers.

But now I want to refine this query, so I can do that by going into chat. Now I can either swipe up with my fingers or look up here at the top of the screen. We have now a new chat scope. With that, with one click, you are now into chat.

Look how beautiful that is. Searched to check, just so seamless. Now we take away all of the content that was in your place, and you focus on your query. The search box you can see, now that can take up to 2.000 characters.

You can just talk to it. You can just ask for it. In this case, let’s say I’m going to ask for gaming optimized TV. All I have to say is which of these are best for gaming? We remember all of the context. We know that we’re talking about flat screens,

We know we’re talking about 65-inch TV’s. Look how Bing start to come back. It does all the queries on my behalf and comes back with a great answer. I just want to highlight a few things for you. Since we know you’re asking about gaming TV’s, we pull out, this one has

A game optimizer, this has Game Mode. We make that really helpful. I’m on a budget. I’ll ask it to adjust it for, which one of these is the cheapest. Again, Bing knows the context, and it just goes in and refines the queries. Easy, you just talk to it,

And you can refine your shopping experience. Again, we find the prices here. I didn’t know you could get a flat-screen for under $500, but that’s a good deal there on Bing if you’re looking for TV. We think that’s going to make shopping easier. Let’s talk about travel.

Before I jump in, I want to just have you remind yourself, when you’re going to plan a trip to a foreign country, think about all the things you go through. Travel times, what sites do I want to see, regulations to observe, budget. Our research shows on Bing, people spend on average weeks

To even months to plan a trip, and to use our organizational tools. I’m going to show you how we make that so much easier with the new Bing. I’m traveling to Mexico for my cousin’s wedding, and with the new Bing, I now don’t have to start with something that’s dumbed down,

Like Mexico City travel tips. I can ask for what I want. First, let me just compare that against what you get in today’s search engines. I’ll type in this long query of what I really want, and you get what you expect. Links to go try to find the answer for yourself.

But we can do much better. Let’s try it in the new Bing. I’ll put in the long query, which is essentially create an itinerary for a five-day trip to Mexico City for me and my family. Just like that, Bing Goes to work. Just take a look at how it starts to compile.

Starts with Day 1, and we put it in there. Look, arrive in Mexico City, check into your hotel, go check out maybe de Bella de Artes, have some lunch. Then there’s Day 2. You see, isn’t this just so much better as a starting point?

Look, if you want to learn more, if you like, hey, I don’t love these five days, no problem. Down there, we have links where you can go and learn more. We put in some nice touches in there as well. Again, now, let’s say business travel changes. Oh, I only have a three day.

I don’t have to go back out there and figure out. I just say, Hey, make this a three-day trip, and Bing reflows that recommendation into a three-day trip. Now let’s just have some fun. Let’s say, Okay, yeah, I’m still trip planning. We’d like to shop, where can I shop?

You get some shopping recommendations. Like to go out at night. Make the most of the trip. Where’s the nightlife? You get a list of nightlife. You see this is just so much better than today’s search to start for your travel planning.

Let me show you a final example of chat and how I think the new language models are going to maybe help bring the world a little bit closer together. Understanding different cultures is often done through the arts like music and literature. I’ve been fascinated by Japanese traditions. [inaudible] share with me one of

His favorite searches from a while back on poetry. With that, I’m going to use that as inspiration. Without a clear idea of what I want necessarily, I’m just going to type in a simple prompt, top Japanese poets and Bing starts to respond with a nice list.

You see this, it does a great job of mixing the Japanese language and the English language and it knows since I’m Korean and English to do that. Right away, I learn about this poet, Matsuo Basho. It turns out he is one of the greatest haiku masters of the world.

I love how it now enlists his name, but we go ahead and we give you one of his famous haikus in Japanese and we auto-translate it in English. Great. I can say, I want to learn a little bit more about Matsuo. I can say, tell me a little bit more.

It’ll give you another jumping-off point, that’s great. Then I can say, hey, tell me about another haiku. Now, what I want you to reflect on is look how easy this is to discover something new. Normally, I might not have done this. I might not have gone to learn about something

New in the world through search because it’s cumbersome to click on links and have to deal with foreign languages. But this is what we mean by unlocking the joy of discovery. Finally, when what you are searching for doesn’t exist and you need that spark of creativity,

Bank and generate the content to help you get started. We just finished planning that trip to Mexico and now what I would like to do is I’d like to share that information with my family. They’re all over the world but I can simply ask Bing, hey, write an email,

Sharing this itinerary that I’ve researched and put it into a thing for me to be able to send to my family. Notice here how the emails starts, it’s a great email. Personalized touches, has the trip highlights, it’ll close here with a nice heartfelt message , it’s just a grip.

It just saves a bunch of time on your everyday work. Now, for my family, English isn’t necessarily always the first language so I can ask Bing to just translate that in Spanish. With a simple request, just basically say, hey, translate that to Spanish, Bing knows to take that entire email and

Itinerary and convert that into Spanish. In fact, Bing can translate automatically over 100 languages. My sister, I’m going to admit to you, she’s a better Spanish writer than I am, but I might just impress her with this one here. Even if I don’t, I at least I saved

Myself a lot of time from having to type the mail. Our focus with Bing is to help generate content and inspiration that helps you with your daily life. I’m going to give you a couple of more examples. Let’s show you one here. I want to create a weekly meal-plan for my family of

Four that has vegetarian options and caters to those who don’t like nuts. Since I’m not the healthiest of eater, I’m going to admit to you here on occasion, this has given me a great list day-by-day, breakfast, lunch, and dinner with all of the ingredients. So much easier to help you

Start to create a meal plan that says, hey, let me get to a healthier meal plan. Now, there’s some things in there I learned when I did this query, which is chia seeds, which I don’t normally eat. That sparked another idea to show you. Let’s say I wanted to get this grocery list

By grocery section. All I can do is say give me that grocery list by groceries section. Bing now takes that exact menu for the week and puts all of the ingredients I need by groceries section so when I go shopping, now can be super efficient. You see all of the ingredients there.

It’s a great help. Then finally, if you’re looking for family activities and you’re struggling for ideas, Bing can help you with fun things like spontaneous trivia games. My family and I were into music so I asked Bing to create a ’90s music trivia game. Just look how great some of these questions

Are and the answer so just creates that game for you. We’re having a little debate backstage about one of the questions that comes up here, which is, who wrote the hips song, Jump Around? Is it Kris Kross or House of Pain? I call it out because it shows you how clever it is.

Because for those of you who know your ’90s hip-hop, Kris Kross wrote a song called Jump, but House of Pain was the one that wrote Jump Around. That’s how clever Bing is. Bing is going to help you look great with your family and have a bunch of fun.

Let’s summarize where we are so far. You’ve seen better search. You’ve seen complete answers. You’ve seen an incredible new chat experience and the ability to spark your creativity all with Bing, your AI powered cop-out for the web. But what if that’s still too much work?

What if you could have that co-pilot right alongside you? Is there at the ready at anytime you want it, aware of the context in which you’re in. What if you could get that co-pilot on the 1.4 billion Windows PCs, on the most used application on the PC, the browser?

Where you don’t have to wonder, Team has created it. I want to introduce you to your AI powered co-pilot in Edge. We’ve just updated Edge with a new look and feel and new AI capabilities. As you can see here, it’s sleeker, it’s lighter and you’re going to notice now that we’ve

Integrated Bing in a really cool new way. Let me show you. Here I am on the Gap website. I’m browsing around with my new Edge browser. I want to read Gap’s quarterly report. I can navigate down to their earnings, Click on “Q3”, and up comes the 15 page Gap PDF. It’s pretty long.

I won’t have time to read all that. What I’d love is a summary of the key points. I want to show you how now with the power of Bing’s AI capabilities within Edge, we can help. With one click, I can open up the sidebar.

Now as you can see at the top of the Window, we have two features, we have chat and compose. Let me show how chat works. I can use chat in Edge to simply ask it to give me the key takeaways of the page I’m on. I’ll just say, key takeaways from the page,

And Bing and AI can now read that PDF and look how great it comes up with the summary of the key points here, their earnings, the fact, it’s going to reaffirm full year guidance. Very cool, a massive time savings. But now I want to compare this with say,

Lululemon who also has their third quarter earnings. Bing can now call out to the web, pull information from outside of this page, bring it into Edge, compare it with the information that’s on this page all within Edge, and I asked it to it in a table and look how amazing this is.

Just like that in one table, I can get an answer this question. Think about how much time that would have taken otherwise. Let me try if we can take it one step further. A top use case we’ve learned from our friends at OpenAI is that developers are really being more productive with ChatGPT.

Here we are on a Stack Overflow website discussion board to learn a little bit about programming. In this case, I’m researching tips on how to parse the JSON file. As we read through, we find this great little code snippet and I’m like, oh, it’s fantastic except it’s in

Python and we need it in REST. All we need to do is highlight that text, have it automatically copied over into the Edge sidebar, and now, Bing inside of Edge says, what do you want to do? We’ll say, hey, rewrite this code in REST. With that simple command,

Bin can go and take that code and rewrite that automatically in the new programming language. This is amazing. GitHub Copilot has been a huge boost in developer productivity. Imagine what the co-pilot can do for people everywhere on any page. One final thing to show you. Not only can you better consume information,

But you can better create. After our big announcement, I’m going to want to write a LinkedIn post, let’s say. I’ll just click “Create” on the post and up comes with a creation dialogue and LinkedIn. But now I can open up the Bing sidebar and you can see here,

I now will go to compose and I’ll just give it a prompt. I’ll say, hey, introducing the new AI powered Bing in Edge, let’s make that enthusiastic and generate a draft and just lightly to help with enthusiasm. Just like that, you get

A little draft and I can edit it and then with one-click, it copies right over into my post dialogue, I can add some hashtags to get it some juice and just like that, I’ve created a post. All of these amazing new capabilities and what we think is a revolutionary new experience.

World-class search, the ability to actually get answers to your questions made easy with integrated chat, and the ability to generate content when you need it to spark your imagination brought to you not only when you’re searching, but everywhere on the web, courtesy of the new Edge browser. With your copilot for the web,

We aspire to unlock that joy of discovery, that wonder of creation, and that feeling of empowerment and being able to harness the world’s knowledge. Thank you on that on the presentation. In a moment, two of our engineering leaders are going to come up and unpack a little bit about

The technical details of how we built the new Bing and our approach to responsible AI. But before I do, I’d like to invite Sam Altman to come up and share his thoughts on this moment and our joint work. Welcome, Sam. SAM ALTMAN: Thank you Yusuf. It’s great to be here.

The new Bing experience really looks fantastic and the depth of it doesn’t come through until you get to use it. I hope you-all will enjoy. OpenAI and Microsoft have been working together for more than three years now. We’re so grateful to have a partner that shares our vision,

Our values of building advanced AI that’s safe and will have a very positive impact on society. Thanks to our partnership and Azure’s AI infrastructure, we’ve been able to make pretty significant strides in our research, which has led to the creation of systems like ChatGPT, Dolly, and Codex.

But we want to make the benefits of AI available to as many people as possible. That’s why we’ve worked with Microsoft to get this AI technology into the hands of millions of people through Azure Open AI service, GitHub Copilot and starting today, Bing. The new Bing experience is powered by one of

Our next-generation models that Microsoft has customized specifically for search. It takes key learnings from ChatGPT, GPT-3.5, and the new model is faster, more accurate and more capable. We all search for things many times a day and Microsoft has created and shipped, a much better, more useful, and more enjoyable search experience.

I feel like we’ve been waiting for this for 20 years. I’m very happy it’s here. I believe that using AI to transform critical tasks like these is going to greatly improve our productivity and day-to-day quality of life. I think this is the beginning of a very new era.

Going forward, we are excited to continue to collaborate with Microsoft very far into the future. The two companies share a deep sense of responsibility in ensuring that AI gets deployed safely. It’s very important to us we’re eager to continue learning from real-world use so they will create better and better AI systems,

You’ve got to do that in the real-world, not in the lab. Our teams will continue working together to set standards for the use of these systems across the entire industry. Thank you very much, and now I’ll hand it over to Dena. DENA SAUNDERS: Thank you, Sam, Yusuf. Hello. I’m Dina Saunders.

I’m the product leader of the team who brought together the magic behind being combined with OpenAI’s most powerful model to date. Yusuf introduced you to Prometheus. I’m here to tell you about the technical innovation behind the experience. There are five aspects contributing to the new Bing. The first is a substantial under

The hood change to every layer of things technological stack. The second is a proprietary system called Bing chat orchestration. The third is state of the art prompt generation. The fourth is around inference and a brand new interactive user experience. Our last development is the infrastructure to scale for the opportunity ahead.

Today we’ll touch on three of these. Let me start with Bing chat orchestration. This is what we use to gather information needed to answer your question. The chat orchestrator ingest your long semantic query and fans out multiple searches. In fact, you might remember as Yusuf was sharing earlier, you can actually see in

The user experience the searches that Bing plus Prometheus is issuing on your behalf. In addition to searching, we also inject additional sources of information to help inform the model. Let me pause here and say that is incredibly important. We’re actually pulling in fresh data, news, answers, contextual signals such as your location and

The context of the conversation to feed into the model, to help ground the information that the model is then using to reason over. With this fresh information, some of the experiences that US have showed you earlier, such as a sports example or inferring on recent events, those would simply not be possible.

There’s more though. This orchestrator in parallel actually parses the documents that it finds and identifies important and relevant pieces of information. This orchestrator is by nature, curious and if it comes across something particularly interesting or insightful and actually starts that same cycle again. This virtuous loop results in a package of

Information that informs and fuels the responses you are seeing. This magic combination of reasoning capabilities with fresh contextual data sparks the innovative and groundbreaking combination that powers the new Bing. Next, I’ll talk about inference and the new interactive user experience. The new interactive experience seamlessly blends search and chat.

We feed a prompt, ie, a proprietary set of instructions into the model which synthesizes the information reasons over all of the contexts that we’ve gathered to form an answer to your question. This overall process is called modal completion. Think of it like when someone knows you well enough to complete your sentence.

We run model inferences to generate tokens ie words which we stream to you in the user experience real-time as you saw in Yusuf’s examples. These words combine with sentences to form the response to your question. When appropriate, Prometheus enhances the text answer with citations to sources and rich structured answers from Bing.

In users presentation, you saw that these inferences display in a brand new, innovative, dual, interactive user experience that blends new conversational elements, a classic search experience, and a new interactive, immersive chat mode. The last aspect of our differentiation and innovation is around the infrastructure we have to scale. Our differentiation comes really

From taking this innovation that we just shared with you today and being able to ship this at scale to millions of users worldwide. Earlier, I talked about how we touched every aspect of the tech stack to deliver this. All of those steps that we just talked about,

Those are done in the order of milliseconds served at the speed of search latency. When Yusuf was showing you the search page, you can see near instant search results juxtaposed on the conversational insights, all streaming in. This is possible because we’re built on Azure, the world supercomputer,

The best and most trusted Cloud platform available. This was a huge effort, incredibly hard. Behind the scenes, teams were working on powering and building out machines in data centers worldwide. We were carefully orchestrating and configuring a complex set of distributed resources. We built new platform pieces designed to help load balance,

Optimize performance and scale like never before. There is no other company that can do this like Microsoft and Bing. As we roll out the product globally, we’re starting out small, focused on learning and evolving with the help of your feedback. We understand that with this major technological shift,

There will be new challenges along the way. We’re committed to learning with you. On behalf of the team, we’re delighted to share this moment with you and with that, let me introduce you to Sarah, who’s one of Microsoft’s renowned responsible AI experts. SARAH BIRD: Hi, I’m Sarah Bird.

I lead our Responsible AI engineering team for new foundational AI technologies like the Prometheus Model. I was one of the first people to touch the new OpenAI model as part of an advanced red team that we pulled together jointly with OpenAI to understand the technology. My first reaction was just, wow,

It’s the most exciting and powerful technology I have ever touched. But with the technology this powerful, I also know that we have an even greater responsibility to ensure that it is developed, deployed, and used properly. Which means there’s a lot that we have to do to make it ready for users.

Fortunately, at Microsoft, we’re not starting from scratch. We have been preparing for this moment for many years. Since 2017, we have been investing in a cross company program to ensure that our AI systems are responsible by design, which has pushed us to innovate across our entire portfolio of

Products to solve Responsible AI challenges. Through that we have created a foundation of Responsible AI product implementation patterns that we can build on top of. We’re also not new to working with generative AI technologies. We’ve been using early versions in Office and Bing for spell checking and grammar rewriting for years.

Obviously, lately, it’s only getting more exciting. In the past year, we launched the GitHub Copilot GA, based on the codecs co-generation model, the Bing creator powered by the DALL-E image generation model, and our own Florence multi-modal model. That’s a lot of generative AI. With each one, we have learned more about

The risks that generative AI technologies can bring, including well-known ones like the perpetuation of stereotypes and bias, as well as novel risks such as jail breaks and we have developed mitigations to address them. In developing the new Bing, we are building on our years of operating large-scale consumer and enterprise services

And our deep partnership with OpenAI. However, for this product, we went further than we’ve ever gone before. We have marshaled the full strength of our Responsible AI ecosystem. Scientists, researchers, ethicist, engineers, and legal and policy experts to work together as a single team to develop approaches to measurement and risk mitigation strategies.

We’ve added Responsible AI to every layer, from the core AI model to the user experience. First, starting with the base technology, we are partnering with OpenAI to improve the model behavior through fine-tuning. Second, we’ve built a state-of-the-art safety system. Bing has been maturing its defensive technologies

Over many years of operating a web scale search engine. These include AI systems that understand user queries and classified documents to ensure safe and quality results for users. We have combined these with newer AI technologies that we’ve created in Azure to moderate generative models. We are continuously retraining all of

These safety models by mining anonymous Bing query logs, and using the new OpenAI model to generate thousands of example conversations. We can update our defenses in minutes to respond to gaps we find or changes in the world. The result is a safety system that enables us to act and understand data at

Every level of the application so we can defend against intentional misuse and mistakes from the AI. Finally, at the application layer, we are iterating on instructions as part of the meta-prompt to guide the model to produce great responses. We have designed the user experience to ensure users understand and are in control.

How do we know all of this works? Measuring responsible harms is a challenging new area of research. This is where we really needed to innovate. We had a key idea that we could actually use the new OpenAI model as a Responsible AI tool to help us test for potential risk and we

Developed a new testing system based on this idea. Let’s look at a tech planning as an example of how this works. Early red teaming showed that the model can generate much more sophisticated instructions than earlier versions of the technology to help someone plan an attack, for example on a school.

Obviously, we don’t want to aid illegal activities in the new Bing. However, the fact that the model understands these activities means we can use it to identify and defend against them. First, we took advantage of the model’s ability to conduct realistic conversations to develop a conversation simulator. The model pretends to be

An adversarial user to conduct thousands of different potentially harmful conversations with Bing to see how it reacts. As a result, we’re able to continuously test our system on a wide range of conversations before any real user ever touches it. Once we have the conversations, the next step is to analyze them,

To see where Bing is doing the right thing versus where we have defects. Conversations are difficult for most AI to classify because they’re multi turn and often more varied. But with the new model, we were able to push the boundary of what is possible. We took guidelines that are typically

Used by expert linguists to label data and modified them so the model could understand them as labeling instructions. We iterated it with it and the human experts until there was significant agreement in their labels. We then used it to classify conversations automatically so we could understand the gaps in our system

And experiment with options to improve them. This system enables us to create a tight loop of testing, analyzing, and improving, which has led to significant new innovations and improvements in our Responsible AI mitigations from our initial implementation to where we are today. The same system enables us to test

Many different Responsible AI risk, for example, how accurate and fresh the information is. Of course, there’s still more to do here today and we do see places where the model is making mistakes. We wanted to empower users to understand the sources of any information and detect errors themselves,

Which is why we have provided references in the interface. We’ve also added feedback features so that users can point out issues they find so that we can get better over time. Maturing and new technology takes time and collaboration, which is why we’re very excited for this next phase where we can

Share the technology with the real-world. We look forward to seeing users unlock its full potential and getting feedback from stakeholders across society to help develop this into an essential tool for the future. Our goal is to continuously advance the state of the art. Yusuf, back to you.

YUSUF MEHDI: Thank you, Sarah. To close, we have one final piece of news to share. I’m pleased to announce that the new Bing is live today for desktop limited preview. What this means is that we’re going to make Bing available today for everyone to try on a limited number of queries

And then to sign up on the wait list to get access to the full experience. We’re also starting with a select group of folks who will have access to the full experience right away. All of you here in the room, you’re all going to be on that list so you’re all

Going to get to try it right away. In addition then we plan to expand to millions of people in the coming weeks. We are also going to be launching our mobile version. Today is an important part of our journey. But it’s just the beginning. As Sarah said, we intend to innovate quickly,

Get your feedback, and continue to bring new innovations and capabilities to everyone. Welcome to the new Bing and Edge. Thanks very much, thanks for being here. [MUSIC]

,00:00 [MUSIC]
00:08 SATYA NADELLA: Hi, everyone.
00:09 Welcome. It’s great
00:13 to see all of you in Seattle in person.
00:17 We have an unbelievable show.
00:19 I see Scott Guthrie even wore his red shirt.
00:22 We welcome you to
00:24 the Azure Kubernetes Container Service 2023 launch.
00:31 No, don’t worry. We’ll have some fun.
00:35 Scott is not coming up to show you
00:38 code onscreen anytime soon,
00:41 but look, it’s an exciting time in tech.
00:45 The broad contours of
00:47 this next platform are
00:51 just getting clearer and clearer each day.
00:54 The advances, what’s possible.
00:56 That’s what obviously excites us in our industry.
01:01 But they’re also grounded
01:03 in what’s happening in the broader world.
01:04 There’s no question. There are
01:06 enormous challenges out there.
01:08 In fact, it reminds me and I’ve spoken about
01:11 this before of the very founding of Microsoft in 1975.
01:14 In fact, when the popular electronics cover
01:17 came out with the Altair,
01:19 which of course our founders
01:20 picked up and ran with it and
01:22 created essentially what’s the software industry
01:24 as we know of it today.
01:26 That same week,
01:28 Newsweek had a cover with President Carter
01:32 trying to fight off
01:33 the three-headed monster of inflation,
01:37 recession, and an energy crisis.
01:40 Today you’d have something similar.
01:42 You will have AI on one cover and
01:45 then we’ll have those three challenges
01:48 plus for good measure,
01:49 we can add a few more.
01:51 We, as Microsoft,
01:54 we as the tech industry have to really
01:56 ground ourselves in how do we relate one to the other?
01:59 In other words, can we use technology to overcome
02:02 the challenges that people and
02:05 organizations and countries face?
02:07 That’s really the pursuit here.
02:10 In that context, I would say,
02:14 I just want to share a couple of
02:16 anecdotes which gives me great hope.
02:18 Quite honestly, it gives me personally a lot of
02:22 satisfaction around working at Microsoft,
02:25 working in this industry to
02:27 push the state of the art of technology.
02:29 The first one, obviously when Sam and
02:32 his team late last year launched ChatGPT,
02:35 that’s the only thing anybody your friends and
02:37 family wanted to talk about throughout the holidays.
02:40 It was just crazy house.
02:43 It was like the Mosaic moment.
02:44 The closest we’ve come.
02:46 It’s been 30 years now since when Mosaic launch,
02:50 which I distinctly remember.
02:52 It was very exciting time.
02:54 I went on a holiday first and then I was in
02:58 the first week of January I was in India.
03:03 On Jan 1st,
03:06 I look at my news feed and I see
03:07 this tweet that Andrej Karpathy put out.
03:11 Who is our ex OpenAI and Tesla,
03:15 and is now an independent AI developer.
03:19 He had this thing about the product that really he
03:22 was most excited about the previous year was
03:24 GitHub Copilot and he was saying how 80 percent of
03:27 his code was being generated by this,
03:30 I would say first at
03:32 scale product built on NLM technology.
03:36 This doesn’t mean he’s
03:38 80 percent somehow not doing his work.
03:40 In fact, he’s getting so much more leverage.
03:42 In fact, recently we crossed
03:45 100 million developers on GitHub.
03:48 Think about this. There are
03:50 100 million developers on GitHub.
03:52 If we can improve their productivity,
03:54 just like how Andrej was able to observe.
03:59 Then let’s say in the next decade we double that number,
04:03 may be double it again.
04:05 We get close to a half a billion developers,
04:08 what economic opportunity it would create.
04:11 Because there is not a meeting that I
04:13 go to today with any CEO,
04:15 CXO of any organization who’s not
04:17 looking for more software developers,
04:19 more digital skills.
04:20 That’s the currency in every sector of the economy,
04:26 in every country of the world.
04:27 That’s the opportunity we
04:29 have to be able to take
04:30 this technology and make a difference.
04:32 But then the next day I went
04:35 to Mumbai and then I saw this demo.
04:38 This was just for me,
04:41 the most profound thing that I’ve seen in a long time.
04:46 The demo was actually built by
04:49 the Ministry of Electronics in
04:51 India because they are building
04:52 out a digital public goods.
04:54 Their idea is look, India has got
04:56 multiple official languages and they wanted to
04:59 democratize essentially access to language translation.
05:03 They’re building it out as a digital public good.
05:05 In fact, Microsoft and Azure and
05:07 Microsoft Research are all involved in that project.
05:10 This is basically speech-to-text,
05:13 text-to-speech across all of the languages in India.
05:16 They showed me this demo where
05:19 a farmer speaking in
05:21 Hindi expresses a pretty complex thought
05:24 about how he had heard
05:25 about some government program and wants to
05:28 apply for a subsidy that he thinks he’s eligible for.
05:33 It’s a pretty complex prompt query.
05:37 There’s technology,
05:38 that’s a good job.
05:39 It goes to the bot, recognizes the speech,
05:41 comes back and says, you know what?
05:43 You should go to this portal,
05:44 fill out these forms,
05:46 then you’ll get your subsidy.
05:47 He says, look, I’m not going to go into any portal.
05:50 I’m not going to fill out any forms,
05:52 can you help me? He does it.
05:56 Then I was told that a developer said, you know what?
06:01 That is Daisy Ching a model that was
06:05 trained on all of the documents of
06:09 the government of India using
06:10 GPT with this speech recognition software.
06:16 Basically two models coming together to really
06:21 help a rural farmer in India
06:24 trying to get access to a government program.
06:28 Look, I grew up in India.
06:30 I dreamt every day that someday
06:32 the industrial revolution will get evenly
06:34 distributed across the world.
06:36 Here I was,
06:38 seeing something so profound,
06:40 something that is developed by the folks at
06:43 OpenAI in the West Coast of
06:44 the United States a few months earlier,
06:46 used by a developer locally
06:48 to have an impact on a rural farmer.
06:51 That to me is what gives
06:54 me meaning and I think gives
06:55 us all meaning in our industry.
06:57 It is just fantastic to see that.
06:59 Now of course we’ve got to scale it and scale
07:02 it with a real understanding that we can break things.
07:07 It’s about being also clear-eyed about
07:10 the unintended consequences of any new technology.
07:14 In fact, that’s why way back in
07:16 2016 is when we came out with the AI principles.
07:20 You have both we as Microsoft and our partners at OpenAI,
07:24 deeply care about this.
07:26 In fact, the entire genesis of
07:28 OpenAI is from that foundation.
07:31 We built these principles,
07:33 but we’ve not just put those principles as a document,
07:36 but we’ve been practicing it because that’s the only way
07:38 technology gets better in this particular case.
07:40 When you’re talking about AI, it’s about alignment with
07:44 human preferences and societal norms
07:46 and you’re not going to do that in a lab.
07:47 You have to do that out there in the world.
07:50 It starts by the way with design decision ones makes.
07:55 When you think about AI, you
07:57 can have the human in the loop,
07:59 you can hear how the human on
08:01 the loop or you can have the human out of the loop.
08:03 Those are decisions we as product makers build,
08:06 build into the products.
08:09 Whenever we have come up with
08:11 some new things and new models,
08:13 we in fact put a premium on human agency.
08:16 When you think about these generative AI models,
08:18 remember one thing, they are prompted to do things.
08:22 The prompting comes from a human being.
08:25 We get to in fact help them prompt.
08:29 We get them to take the draft that gets generated.
08:33 They should review the draft.
08:35 They get to review the draft,
08:37 they get to approve the draft using judgment.
08:40 We want to give them as many perspectives,
08:42 as many ways to regenerate.
08:44 We want to take even just the design of AI products as
08:49 a first-class construct and build that into our products.
08:53 But that’s not sufficient, we realize that.
08:55 You have to write at
08:57 the pre-training stage when it comes to the data,
09:00 the pre-training itself, the model itself has to be safe.
09:03 The safety system around the model,
09:06 the application context, all will matter.
09:10 We absolutely, and you’ll see that today,
09:13 we take all of that as
09:15 first-class things which we want to reduce,
09:18 not just to principles but to engineering practice.
09:21 Such that we can build AI
09:23 that’s more aligned with human values,
09:25 more aligned with what our preferences are,
09:27 both individually and as a society.
09:32 What is it that we should do and what should we build?
09:36 I think that this technology is going to reshape
09:38 pretty much every software category.
09:41 We know, we’ve seen that and we’ve solved.
09:43 If you think about the web, we’ve had what?
09:47 Three at least very distinct platform shifts
09:50 that have shaped the web.
09:51 The web was born on the PC and
09:55 the server and then it evolved with mobile and Cloud.
10:00 Now the question is,
10:02 how is AI going to reshape the web?
10:07 Each time in each one of those phases,
10:09 some real foundational technology layers,
10:13 sometimes I describe them as
10:14 these organizational layers of technology, were born.
10:18 The browser was the first one.
10:19 Without the browser, the web would have not
10:22 been as popular as it is today.
10:25 Same thing with search.
10:27 Search organized the web.
10:29 Then when it came to the mobile
10:31 generation and mobile and Cloud,
10:33 in fact these super apps,
10:34 especially outside of the United States around messaging,
10:38 became the way people consume the web.
10:41 We also had app stores.
10:45 The question is, what are the constructs?
10:48 What are the organizing layers going forward?
10:52 You’ll see some of that today.
10:54 We think there are two things that are emerging.
10:57 One is this conversational intelligent agents.
11:01 I think they’re going to be things that
11:03 we’re going to have everywhere we go.
11:05 All computer interaction is
11:08 going to be mediated with an agent helping you.
11:11 In fact, we’re going to have this notion of a
11:13 co-pilot that’s going to be there
11:16 across every application canvas inside of
11:19 an operating system shell in a browser.
11:23 We want to show you some of this innovation starting with
11:31 how it’s going to reshape
11:33 the largest software category on planet Earth,
11:39 which I’ve been working on for a long time,
11:42 which we’re very, very excited about, Search.
11:47 It’s a new day in Search.
11:51 It’s a new paradigm for search.
11:54 Rapid innovation is going to come.
11:57 In fact, a race starts
11:59 today in terms of
12:01 what you can expect and we’re going to move.
12:03 We’re going to move fast.
12:04 For us every day,
12:07 we want to bring out new things.
12:10 Most importantly, we want to have
12:13 a lot of fun innovating
12:15 again in Search because it’s high time.
12:17 With that, let me turn it over to Yusuf.
12:22 YUSUF MEHDI: Thanks, Satya. It’s great
12:25 to be here with all of you today.
12:27 We’ve been working on something we think is pretty
12:29 special and we’re just eager to share it with you.
12:32 In my time at the company,
12:34 I’ve been lucky to witness a few important moments.
12:37 I think this might be another one of those.
12:39 We believe as Satya said that we can improve
12:42 the way billions of people can benefit from the Internet.
12:45 Created by really an amazing team across Microsoft,
12:48 from the core web engineering folks in Michael’s group,
12:51 to the brilliant folks at Microsoft Research,
12:54 to the tireless people that work on
12:55 the Azure AI supercomputer,
12:57 we think of it humbly as
12:59 the next-generation of search and browsing.
13:01 Infused with AI and
13:03 assembled as an integrated experience,
13:05 we’re going to re-imagine the search engine,
13:08 the web browser, and new chat experiences
13:11 into something we think of as your copilot for the web.
13:15 Now, copilot is a critical word because we
13:19 believe in the empowering nature of AI in which you,
13:22 the individual, are in charge.
13:24 Now what it is, is not even as
13:26 important as what it represents.
13:28 That is for us an aspiration
13:30 to unlock the joy of discovery,
13:33 the wonder of creation,
13:35 and that feeling of empowerment from
13:37 being able to harness the world’s knowledge.
13:39 At the center of this new co-pilot experience is
13:43 an all new Bing search engine and Edge web browser,
13:47 and it’s going to do four things for you.
13:49 First, it’s a better search.
13:52 It’s the search you know and love but
13:54 it’s better because it’s AI powered.
13:56 Second, not only does it give you the search results,
14:00 but it will actually answer your questions.
14:03 Third, we’re going to make it incredibly easy to use.
14:06 We’re going to let you chat, we’re going to
14:08 let you just talk to it naturally.
14:10 Last, when you need that spark of creativity,
14:13 Bing can generate content for
14:15 you automatically to help you get started.
14:17 Let’s talk a little bit about the opportunity
14:20 in search and why
14:21 we believe we’re at the start of the next generation.
14:26 No. Sorry about that, we’re on to the next generation.
14:31 All seriousness, with
14:34 over 10 billion queries a day,
14:35 we all know the search engine is an incredible tool.
14:38 We do. Yet as the web has grown,
14:41 we’ve run into challenges.
14:42 People are overwhelmed increasingly with
14:45 too many links when they’re
14:46 trying to find simple answers.
14:48 But 40 percent of the time people click on search links,
14:52 they click back immediately.
14:54 That’s a sign they’re not finding what they want.
14:56 Most notably, we have to adapt to
14:58 search versus the other way around.
15:01 It turns out search works better
15:02 if you give it fewer keywords.
15:04 You might be surprised to know that 75 percent of
15:06 all searches are three key words or less.
15:09 But come on, we shouldn’t be surprised.
15:12 Search has remained fundamentally
15:14 the same since the last major inflection.
15:17 When we moved from a directory approach to
15:19 search to an algorithmic approach to search.
15:22 The user experience and the approach
15:24 underlying are essentially the same as 20 years ago.
15:28 Few keywords and you get millions of links.
15:31 But as the world around us has changed,
15:34 the way people use search has changed, we all know this.
15:36 People are trying to use search to do
15:38 more than it was designed to do.
15:40 To illustrate that let’s just look at a breakdown
15:43 of search queries by type to understand this point.
15:46 Search querries today you can bucket them
15:48 into serve three types of categories.
15:50 The first are what we call navigational.
15:52 This is people searching for a website.
15:55 When you need to renew your driver’s license,
15:57 you need to go to the DMV.
15:59 When you want to tell your friend
16:00 about that great pizza place,
16:02 you send them the WebLink.
16:03 That’s what search was designed to do,
16:06 and it does it super well.
16:08 The second, third of categories
16:09 are what we call informational.
16:11 These are things like what’s the weather forecast?
16:14 What was last night sports scores?
16:16 What’s today’s stock price?
16:17 Search works great for that.
16:19 But for anything more complex, like hey,
16:22 I got to pick up this love seat at the store,
16:24 is it going to fit in the back of my car?
16:26 Search is going to fall short on that.
16:28 Then the final third,
16:29 we’re back into what we call everything else.
16:32 These are typically more deep research in nature.
16:34 This is things like trip planning or complex shopping.
16:38 An example query here that people are putting in is, hey,
16:41 can you recommend a five-day itinerary to Mexico City?
16:45 For these, search falls far short of the desired goal.
16:48 What this means if you just do the simple math,
16:51 it means that roughly half of
16:53 all searches aren’t delivering the job that people want.
16:56 If you go on that 10 million queries,
16:58 it means that every second,
17:00 50,000 people searches potentially go unanswered.
17:04 This is why we believe
17:07 it’s time for a new approach in search.
17:10 For the billions of queries that are going unanswered,
17:12 we’ve seen new attempts to try address the problem.
17:15 As you all know, there are vertical search attempts.
17:19 Amazon has done a better job for shopping.
17:21 YouTube is great for video.
17:22 Reddit is a great place to come get advice.
17:25 The benefits of search are well-known.
17:27 It’s fast, it’s timely,
17:29 and there’s a great business model.
17:30 Then more recently they’ve been another vector,
17:33 more disruptive ideas like leveraging AI to
17:36 answer questions directly and to generate content.
17:39 These are amazing as well,
17:41 and they show what’s possible.
17:43 But what if you could get the two to come together?
17:47 Not only would you get two things in one,
17:50 but we think you could actually solve problems in each.
17:54 We think you could get to something that is
17:55 really one plus one equals three.
17:57 We’ve done that with the new Bing.
18:00 I want to share with you
18:02 four technical breakthroughs the Team
18:05 has achieved to make this come to life.
18:07 First, through our fantastic partnership
18:09 with SAM and the brilliant team at OpenAI,
18:12 I’m excited to announce that Bing is running on
18:15 a new next-generation large language model.
18:19 One that is much more powerful than ChatGPT,
18:22 and one that is customized specifically for search.
18:25 It’s unlike anything you’ve had a chance to play
18:27 with and we can’t wait for you to try it.
18:29 Second, we’ve developed a proprietary way of working
18:33 with OpenAI that allows us to best leverage the power.
18:37 We call this collection of capabilities and
18:39 techniques the Prometheus model.
18:41 The core idea here is that both
18:43 at training and at runtime,
18:45 we engage with the OpenAI model more
18:47 intelligently through our knowledge of the web,
18:49 via the Bing index and some special query techniques.
18:53 We’re going to dig into this a little bit more later,
18:55 but the benefits are the following.
18:57 First, we can improve
18:58 the relevancy of answers by feeding in
19:01 and better tuning queries given
19:03 our understanding of the web search index.
19:05 Next, we can annotate
19:07 the answers with specific web links and citations.
19:11 We can get you more up-to-date
19:13 information because search crawls the web every day.
19:16 We can improve understanding of geolocation.
19:19 Finally, we can increase
19:21 the safety of the answers as well by catching
19:23 queries at initiation and then
19:25 checking that again at the delivery of an answer.
19:28 Next, we’ve been making
19:31 steady improvements on the Bing algorithms for years.
19:34 We test these with independent judges.
19:36 The shows that are search experience is on par or
19:39 better than any search experience
19:41 when you take away the brands.
19:43 But a few weeks ago, something special happened.
19:46 We applied the AI model to
19:48 our core search ranking engine and we
19:50 saw the largest jump in relevance in two decades.
19:54 We believe we can continue to drive
19:56 breakthroughs as we improve the models.
19:59 Then finally, we are re-imagining how you
20:02 interact with all of these capabilities across search,
20:05 browser, and chat by
20:07 pulling them into a unified experience.
20:09 I want you to think about search
20:11 coming together with answers,
20:13 search coming together with chat,
20:15 and search coming together with the browser.
20:18 As we all know and as the folks at OpenAI taught us,
20:21 the user experience is as important as
20:24 the underlying technical platform. Enough talk.
20:28 You guys ready to see it in action?
20:29 Let’s show you how we’re going to enable
20:31 the Copilot for the web.
20:33 Now before I do, I want to call
20:34 out two things for clarity.
20:35 First, because there’s so much I’m going to show you
20:38 until you don’t have to watch me type every search.
20:41 I recorded these searches live just yesterday.
20:45 Second, in case there are skeptics in the room,
20:47 you’re going to get a chance to play with it directly,
20:49 put your hands on it and type the same queries as well
20:52 as your own favorites right after this presentation.
20:55 You’re all familiar with search,
20:56 so I’m not going to show you a search.
20:58 I’m going to share what you can’t do with today’s search.
21:01 I’m going to focus on answers,
21:02 chat, and the ability to create.
21:04 But first let me introduce you to the new Bing homepage.
21:08 You’re going to notice some subtle but important changes.
21:11 First, we have an expanded search box
21:13 capable of accepting up to 1,000 characters.
21:16 Because now Bing works with natural language.
21:18 You saw a little hint to chat,
21:20 which I’m going to get back to in a second.
21:22 Now want to set up the first search scenario.
21:24 My daughter and I, we both love art.
21:26 She studied art at school and I’d like to stay
21:28 connected with her on our mutual passion.
21:30 Last semester, she was learning about Mexican painters.
21:33 I’d like to get a quick summary of
21:34 the most influential Mexican painters
21:36 and the works to learn a bit more about the topic.
21:38 If I type the full query of what I’d like to
21:41 know in today’s search, here’s what I get.
21:46 I’ll just type in, compare
21:48 the most influential Mexican artists
21:50 and their top paintings,
21:52 and you’ll get what you expect. In some links.
21:55 It’s fine, but we can do better.
21:58 Let’s try this now in the new Bing.
22:00 What you’ll see as we pull up, is first,
22:03 you see the web results here on the left,
22:05 but then on the right, you start to see
22:07 how we start to compile the answer.
22:09 What you get here now is we have
22:11 the ability to highlight these web links.
22:13 We can annotate the results.
22:15 That’s because we’re able to go in and
22:17 apply our index onto the answers there.
22:20 In other words, the answers and
22:22 the search on one page has
22:24 saved me a huge amount of time.
22:25 This gives you a little bit of a
22:27 sense of what you can do.
22:28 Now you’ve seen some of this before,
22:30 you might say, Hey, I’ve seen some of these.
22:31 Let’s show you how we can do some additional things.
22:34 I’m going to show you another query.
22:36 Where we use the timeliness of search.
22:39 Let’s go ahead and ask about events in
22:41 Scottsdale during the Super Bowl.
22:45 What you’ll see is we get back and answer here,
22:48 where we have events and we’re
22:50 able to do that because Bing cross web.
22:52 Notice how we can find not only
22:54 that the Super Bowl was played in Glendale on the 12th,
22:57 but then there are events like
22:59 Cardi B Super Bowl party that’s
23:00 on the 10th also shows up.
23:02 We were able to pull these things together.
23:04 You start to get a sense of how we can build on what’s
23:07 today with the Bing index.
23:10 Now I’m going to show you a few
23:11 more of these types of answers quickly,
23:13 so you can get a sense of the power,
23:14 and the time savings from Bing.
23:16 When I’m running an errand,
23:18 like the example I gave to you earlier,
23:20 I can ask Bing to determine if
23:22 that new loveseat from IKEA is
23:24 going to fit in the back of my Honda Odyssey.
23:26 What you’ll see is they can
23:28 actually find the dimensions of the loveseat,
23:30 the interior space of the car,
23:32 and then make an estimation as to whether it will fit.
23:35 In this case, I’m choosing
23:37 an example of where Bing does not know the answer.
23:39 We know that we can’t be definitive about it.
23:43 The reason I’m doing that is because we know we
23:45 won’t be able to answer every question, every time.
23:48 But Bing can still provide
23:49 some helpful information as you can see on this answer.
23:52 We also know we’ll make our share of mistakes,
23:55 and Bing rule this out.
23:56 We’ve added a quick feedback button
23:58 at the top of every search,
24:00 so that you can give us feedback and we can learn.
24:02 Another example, when I’m shopping,
24:05 I can ask Bing to search, find,
24:07 and compare the top three selling pet vacuums
24:10 listing the pros and cons.
24:12 Look how great this answer is.
24:15 It has all three of the products I’m looking for,
24:18 super-helpful pros and cons. Stop and think.
24:21 If you had to compile that,
24:22 how much time that would take you to do?
24:24 As you can see at the top of the page,
24:26 we still have the advertising in this example,
24:28 because we know when people are
24:30 shopping, those ads are helpful.
24:32 Finally on this one, if I’m cooking,
24:35 and I realize I’ve forgotten
24:36 a key ingredient, in this case, e.g.
24:39 eggs for my cake recipe,
24:41 Bing can not only find the egg substitutes,
24:44 it can get me the exact amount for each ingredient.
24:48 Take a look at this.
24:49 I love this. You can actually see e.g.
24:51 if you go with vinegar and baking soda,
24:53 the cake is lighter and more fluffy.
24:55 These are just little helpful tips that
24:58 everyday help make your life a little better.
25:00 These are just some examples.
25:01 Then you can start to get a sense of how, with answers.
25:04 We go far beyond what you can do with search day.
25:06 We can actually help you get what you want to get done.
25:09 Now let me tell you about how
25:11 Bing goes further to help you with
25:12 particularly complex questions for
25:14 which there is not a precise answer.
25:16 I wanted to introduce to you
25:18 the new chat experience in Bing.
25:20 I think of this as search with your own personal helper,
25:23 to help you refine your query until
25:24 you get exactly what you’re looking for.
25:26 This comes in handy for activities
25:28 like trip planning and shopping research.
25:31 Let’s start with shopping. I’m going
25:33 to look for 65 inch TV.
25:36 Again, you see ads at the top,
25:38 the result of the links on the left,
25:39 and the answer is here on the right.
25:41 You can pick whichever you’d like.
25:43 We’ll give you a good set of answers.
25:45 But now I want to refine this query,
25:47 so I can do that by going into chat.
25:49 Now I can either swipe up with
25:50 my fingers or look up here at the top of the screen.
25:53 We have now a new chat scope.
25:55 With that, with one click,
25:57 you are now into chat.
25:59 Look how beautiful that is.
26:00 Searched to check, just so seamless.
26:02 Now we take away all of
26:04 the content that was in your place,
26:06 and you focus on your query.
26:08 The search box you can see,
26:10 now that can take up to 2.000 characters.
26:12 You can just talk to it. You can just ask for it.
26:15 In this case, let’s say I’m going to
26:16 ask for gaming optimized TV.
26:18 All I have to say is which of these are best for gaming?
26:22 We remember all of the context.
26:24 We know that we’re talking about flat screens,
26:26 we know we’re talking about 65-inch TV’s.
26:29 Look how Bing start to come back.
26:31 It does all the queries on
26:32 my behalf and comes back with a great answer.
26:35 I just want to highlight a few things for you.
26:36 Since we know you’re asking about gaming TV’s,
26:38 we pull out, this one has
26:40 a game optimizer, this has Game Mode.
26:42 We make that really helpful. I’m on a budget.
26:45 I’ll ask it to adjust it for,
26:47 which one of these is the cheapest.
26:49 Again, Bing knows the context,
26:51 and it just goes in and refines the queries.
26:54 Easy, you just talk to it,
26:57 and you can refine your shopping experience.
26:58 Again, we find the prices here.
27:01 I didn’t know you could get a flat-screen for under $500,
27:03 but that’s a good deal there on
27:04 Bing if you’re looking for TV.
27:07 We think that’s going to make shopping
27:10 easier. Let’s talk about travel.
27:13 Before I jump in, I want to
27:14 just have you remind yourself,
27:16 when you’re going to plan a trip to a foreign country,
27:18 think about all the things you go through.
27:20 Travel times, what sites do I want to see,
27:23 regulations to observe, budget.
27:26 Our research shows on Bing,
27:28 people spend on average weeks
27:29 to even months to plan a trip,
27:31 and to use our organizational tools.
27:33 I’m going to show you how we make that so
27:34 much easier with the new Bing.
27:36 I’m traveling to Mexico for
27:37 my cousin’s wedding, and with the new Bing,
27:39 I now don’t have to start
27:40 with something that’s dumbed down,
27:42 like Mexico City travel tips.
27:44 I can ask for what I want.
27:46 First, let me just compare that against
27:48 what you get in today’s search engines.
27:49 I’ll type in this long query of what I really want,
27:52 and you get what you expect.
27:54 Links to go try to find the answer for yourself.
27:57 But we can do much better.
27:59 Let’s try it in the new Bing.
28:01 I’ll put in the long query,
28:04 which is essentially create an itinerary for
28:07 a five-day trip to Mexico City for me and my family.
28:11 Just like that, Bing Goes to work.
28:13 Just take a look at how it starts to compile.
28:16 Starts with Day 1, and we put it in there.
28:18 Look, arrive in Mexico City,
28:20 check into your hotel,
28:22 go check out maybe de Bella de Artes, have some lunch.
28:26 Then there’s Day 2.
28:27 You see, isn’t this just
28:30 so much better as a starting point?
28:32 Look, if you want to learn more, if you like, hey,
28:33 I don’t love these five days, no problem.
28:35 Down there, we have links where
28:37 you can go and learn more.
28:39 We put in some nice touches in there as well.
28:41 Again, now, let’s say business travel changes.
28:44 Oh, I only have a three day.
28:46 I don’t have to go back out there and figure out.
28:47 I just say, Hey, make this a three-day trip,
28:50 and Bing reflows
28:52 that recommendation into a three-day trip.
28:54 Now let’s just have some fun.
28:56 Let’s say, Okay, yeah, I’m still trip planning.
28:59 We’d like to shop, where can I shop?
29:02 You get some shopping recommendations.
29:04 Like to go out at night. Make the most of the trip.
29:07 Where’s the nightlife?
29:10 You get a list of nightlife.
29:12 You see this is just so much better than
29:15 today’s search to start for your travel planning.
29:19 Let me show you a final example of chat and how I think
29:24 the new language models are going to maybe
29:26 help bring the world a little bit closer together.
29:29 Understanding different cultures is often
29:31 done through the arts like music and literature.
29:33 I’ve been fascinated by Japanese traditions.
29:36 [inaudible] share with me one of
29:38 his favorite searches from a while back on poetry.
29:40 With that, I’m going to use that as inspiration.
29:43 Without a clear idea of what I want necessarily,
29:45 I’m just going to type in a simple prompt,
29:47 top Japanese poets and
29:49 Bing starts to respond with a nice list.
29:52 You see this, it does a great job of
29:54 mixing the Japanese language and
29:56 the English language and it
29:57 knows since I’m Korean and English to do that.
29:59 Right away, I learn about this poet, Matsuo Basho.
30:03 It turns out he is one
30:05 of the greatest haiku masters of the world.
30:08 I love how it now enlists his name,
30:10 but we go ahead and we give you one of his famous haikus
30:13 in Japanese and we auto-translate it in English.
30:16 Great. I can say, I want to learn
30:18 a little bit more about Matsuo.
30:20 I can say, tell me a little bit more.
30:22 It’ll give you another jumping-off point, that’s great.
30:24 Then I can say, hey, tell me about another haiku.
30:27 Now, what I want you to reflect on is look how
30:30 easy this is to discover something new.
30:33 Normally, I might not have done this.
30:35 I might not have gone to learn about something
30:36 new in the world through search
30:38 because it’s cumbersome to
30:39 click on links and have to deal with foreign languages.
30:41 But this is what we mean
30:43 by unlocking the joy of discovery.
30:46 Finally, when what you are searching for
30:49 doesn’t exist and you need that spark of creativity,
30:52 bank and generate the content to help you get started.
30:55 We just finished planning that trip to Mexico and now
30:58 what I would like to do is I’d like to
30:59 share that information with my family.
31:02 They’re all over the world but I can simply ask Bing,
31:05 hey, write an email,
31:06 sharing this itinerary that I’ve
31:09 researched and put it
31:11 into a thing for me to be able to send to my family.
31:14 Notice here how the emails starts, it’s a great email.
31:17 Personalized touches, has the trip highlights,
31:21 it’ll close here with a nice heartfelt message
31:23 , it’s just a grip.
31:25 It just saves a bunch of time on your everyday work.
31:27 Now, for my family,
31:29 English isn’t necessarily always
31:31 the first language so I can
31:32 ask Bing to just translate that in Spanish.
31:34 With a simple request, just basically say, hey,
31:37 translate that to Spanish,
31:39 Bing knows to take that entire email and
31:40 itinerary and convert that into Spanish.
31:43 In fact, Bing can translate
31:45 automatically over 100 languages.
31:48 My sister, I’m going to admit to you,
31:50 she’s a better Spanish writer than I am,
31:51 but I might just impress her with this one here.
31:54 Even if I don’t, I at least I saved
31:57 myself a lot of time from having to type the mail.
31:59 Our focus with Bing is to help generate
32:02 content and inspiration that
32:03 helps you with your daily life.
32:05 I’m going to give you a couple of more examples.
32:07 Let’s show you one here.
32:10 I want to create a weekly meal-plan for my family of
32:13 four that has vegetarian options
32:15 and caters to those who don’t like nuts.
32:17 Since I’m not the healthiest of eater,
32:20 I’m going to admit to you here on occasion,
32:22 this has given me a great list day-by-day,
32:25 breakfast, lunch, and dinner with all of the ingredients.
32:29 So much easier to help you
32:30 start to create a meal plan that says,
32:32 hey, let me get to a healthier meal plan.
32:34 Now, there’s some things
32:36 in there I learned when I did this query,
32:37 which is chia seeds, which I don’t normally eat.
32:39 That sparked another idea to show you.
32:41 Let’s say I wanted to get this grocery list
32:43 by grocery section.
32:44 All I can do is say give me
32:46 that grocery list by groceries section.
32:48 Bing now takes that exact menu for the week and puts
32:52 all of the ingredients I
32:54 need by groceries section so when I go shopping,
32:57 now can be super efficient.
32:59 You see all of the ingredients there.
33:01 It’s a great help.
33:03 Then finally, if you’re looking for
33:06 family activities and you’re struggling for ideas,
33:08 Bing can help you with fun things
33:10 like spontaneous trivia games.
33:11 My family and I were into music so I
33:14 asked Bing to create a ’90s music trivia game.
33:17 Just look how great some of these questions
33:19 are and the answer so just creates that game for you.
33:22 We’re having a little debate backstage
33:25 about one of the questions that comes up here,
33:27 which is, who wrote the hips song, Jump Around?
33:31 Is it Kris Kross or House of Pain?
33:33 I call it out because it shows you how clever it is.
33:35 Because for those of you who know your ’90s hip-hop,
33:38 Kris Kross wrote a song called Jump,
33:40 but House of Pain was the one that wrote Jump Around.
33:43 That’s how clever Bing is.
33:45 Bing is going to help you look great with
33:47 your family and have a bunch of fun.
33:50 Let’s summarize where we are so far.
33:53 You’ve seen better search.
33:55 You’ve seen complete answers.
33:57 You’ve seen an incredible new chat experience and
33:59 the ability to spark your creativity all with Bing,
34:02 your AI powered cop-out for the web.
34:07 But what if that’s still too much work?
34:12 What if you could have that co-pilot right alongside you?
34:16 Is there at the ready at anytime you want it,
34:19 aware of the context in which you’re in.
34:22 What if you could get that co-pilot
34:25 on the 1.4 billion Windows PCs,
34:28 on the most used application on the PC, the browser?
34:33 Where you don’t have to wonder, Team has created it.
34:36 I want to introduce you to your AI
34:38 powered co-pilot in Edge.
34:41 We’ve just updated Edge with
34:42 a new look and feel and new AI capabilities.
34:47 As you can see here, it’s sleeker,
34:49 it’s lighter and you’re going to notice now that we’ve
34:52 integrated Bing in a really cool new way.
34:55 Let me show you.
34:57 Here I am on the Gap website.
35:00 I’m browsing around with my new Edge browser.
35:02 I want to read Gap’s quarterly report.
35:05 I can navigate down to their earnings,
35:08 Click on “Q3”,
35:10 and up comes the 15 page Gap PDF. It’s pretty long.
35:14 I won’t have time to read all that.
35:16 What I’d love is a summary of the key points.
35:19 I want to show you how now with the power of
35:21 Bing’s AI capabilities within Edge, we can help.
35:25 With one click, I can open up the sidebar.
35:28 Now as you can see at the top of the Window,
35:30 we have two features, we have chat and compose.
35:33 Let me show how chat works.
35:35 I can use chat in Edge to simply
35:37 ask it to give me the key takeaways of the page I’m on.
35:41 I’ll just say, key takeaways from the page,
35:43 and Bing and AI can now read that PDF and look how
35:46 great it comes up
35:48 with the summary of the key points here,
35:49 their earnings, the fact,
35:51 it’s going to reaffirm full year guidance.
35:53 Very cool, a massive time savings.
35:56 But now I want to compare this with say,
35:59 Lululemon who also has their third quarter earnings.
36:02 Bing can now call out to the web,
36:05 pull information from outside of this page,
36:07 bring it into Edge,
36:09 compare it with the information that’s on
36:11 this page all within Edge,
36:13 and I asked it to it in a table and
36:15 look how amazing this is.
36:17 Just like that in one table,
36:19 I can get an answer this question.
36:20 Think about how much time that
36:22 would have taken otherwise.
36:24 Let me try if we can take it one step further.
36:26 A top use case we’ve learned from our friends at
36:29 OpenAI is that developers are
36:30 really being more productive with ChatGPT.
36:33 Here we are on a Stack Overflow website discussion board
36:36 to learn a little bit about programming.
36:37 In this case, I’m researching
36:39 tips on how to parse the JSON file.
36:41 As we read through,
36:43 we find this great little code snippet and I’m like, oh,
36:46 it’s fantastic except it’s in
36:48 Python and we need it in REST.
36:50 All we need to do is highlight that text,
36:53 have it automatically copied over into the Edge sidebar,
36:57 and now, Bing
36:59 inside of Edge says, what do you want to do?
37:00 We’ll say, hey, rewrite this code in REST.
37:03 With that simple command,
37:05 bin can go and take that code and rewrite
37:07 that automatically in the new programming language.
37:09 This is amazing. GitHub Copilot
37:12 has been a huge boost in developer productivity.
37:16 Imagine what the co-pilot can do for
37:18 people everywhere on any page.
37:21 One final thing to show you.
37:23 Not only can you better consume information,
37:26 but you can better create.
37:27 After our big announcement,
37:29 I’m going to want to write a LinkedIn post, let’s say.
37:31 I’ll just click “Create” on
37:33 the post and up
37:34 comes with a creation dialogue and LinkedIn.
37:36 But now I can open up the Bing
37:38 sidebar and you can see here,
37:40 I now will go to compose and I’ll just give it a prompt.
37:42 I’ll say, hey, introducing
37:44 the new AI powered Bing in Edge,
37:45 let’s make that enthusiastic and generate
37:48 a draft and just lightly to help with enthusiasm.
37:51 Just like that, you get
37:53 a little draft and I can edit it and then with one-click,
37:56 it copies right over into my post dialogue,
37:59 I can add some hashtags to get it
38:01 some juice and just like that,
38:03 I’ve created a post.
38:05 All of these amazing new capabilities and
38:08 what we think is a revolutionary new experience.
38:11 World-class search, the ability to actually get
38:14 answers to your questions made easy with integrated chat,
38:18 and the ability to generate content when you need it to
38:21 spark your imagination brought
38:23 to you not only when you’re searching,
38:24 but everywhere on the web,
38:27 courtesy of the new Edge browser.
38:29 With your copilot for the web,
38:31 we aspire to unlock that joy of discovery,
38:34 that wonder of creation,
38:35 and that feeling of empowerment and being
38:37 able to harness the world’s knowledge.
38:39 Thank you on that on the presentation.
38:45 In a moment,
38:47 two of our engineering leaders
38:48 are going to come up and unpack a little bit about
38:50 the technical details of how we built
38:52 the new Bing and our approach to responsible AI.
38:55 But before I do, I’d like to invite Sam Altman to come up
38:58 and share his thoughts on this moment and
39:00 our joint work. Welcome, Sam.
39:05 SAM ALTMAN: Thank you Yusuf.
39:07 It’s great to be here.
39:08 The new Bing experience really
39:10 looks fantastic and the depth of
39:12 it doesn’t come through until you
39:13 get to use it. I hope you-all will enjoy.
39:16 OpenAI and Microsoft have been working
39:18 together for more than three years now.
39:20 We’re so grateful to have
39:21 a partner that shares our vision,
39:22 our values of building advanced AI that’s
39:24 safe and will have a very positive impact on society.
39:28 Thanks to our partnership and Azure’s AI infrastructure,
39:32 we’ve been able to make pretty
39:33 significant strides in our research,
39:35 which has led to the creation of systems like
39:37 ChatGPT, Dolly, and Codex.
39:40 But we want to make the benefits of AI
39:42 available to as many people as possible.
39:44 That’s why we’ve worked with Microsoft to get
39:46 this AI technology into the hands of
39:49 millions of people through Azure Open AI service,
39:51 GitHub Copilot and starting today, Bing.
39:55 The new Bing experience is powered by one of
39:58 our next-generation models that
40:00 Microsoft has customized specifically for search.
40:03 It takes key learnings from ChatGPT,
40:05 GPT-3.5, and the new model is faster,
40:09 more accurate and more capable.
40:11 We all search for things many times a day
40:13 and Microsoft has created and shipped,
40:16 a much better, more useful,
40:17 and more enjoyable search experience.
40:19 I feel like we’ve been waiting for this for 20 years.
40:21 I’m very happy it’s here. I believe
40:24 that using AI to transform
40:25 critical tasks like these is going to greatly
40:28 improve our productivity and day-to-day quality of life.
40:31 I think this is the beginning of a very new era.
40:34 Going forward, we are excited to
40:37 continue to collaborate with
40:38 Microsoft very far into the future.
40:39 The two companies share a deep sense of
40:41 responsibility in ensuring that AI gets deployed safely.
40:45 It’s very important to us we’re
40:46 eager to continue learning from
40:48 real-world use so they
40:49 will create better and better AI systems,
40:51 you’ve got to do that in the real-world, not in the lab.
40:53 Our teams will continue working together to set standards
40:56 for the use of these systems across the entire industry.
40:59 Thank you very much, and now I’ll hand it over to Dena.
41:08 DENA SAUNDERS: Thank you, Sam, Yusuf.
41:10 Hello. I’m Dina Saunders.
41:12 I’m the product leader of
41:14 the team who brought together the magic
41:15 behind being combined with
41:17 OpenAI’s most powerful model to date.
41:20 Yusuf introduced you to Prometheus.
41:22 I’m here to tell you about the technical innovation
41:24 behind the experience.
41:26 There are five aspects contributing to the new Bing.
41:29 The first is a substantial under
41:31 the hood change to every layer
41:33 of things technological stack.
41:35 The second is a proprietary system
41:37 called Bing chat orchestration.
41:40 The third is state of the art prompt generation.
41:44 The fourth is around inference and
41:46 a brand new interactive user experience.
41:49 Our last development is the infrastructure
41:52 to scale for the opportunity ahead.
41:55 Today we’ll touch on three of these.
41:58 Let me start with Bing chat orchestration.
42:01 This is what we use to gather
42:02 information needed to answer your question.
42:05 The chat orchestrator ingest
42:07 your long semantic query and fans out multiple searches.
42:10 In fact, you might remember as Yusuf was sharing earlier,
42:14 you can actually see in
42:15 the user experience the searches that
42:17 Bing plus Prometheus is issuing on your behalf.
42:20 In addition to searching,
42:22 we also inject additional sources of
42:24 information to help inform the model.
42:27 Let me pause here and say that is incredibly important.
42:30 We’re actually pulling in fresh data, news, answers,
42:34 contextual signals such as your location and
42:36 the context of the conversation to feed into the model,
42:40 to help ground the information
42:42 that the model is then using to reason over.
42:45 With this fresh information,
42:47 some of the experiences that US have showed you earlier,
42:50 such as a sports example or inferring on recent events,
42:53 those would simply not be possible.
42:55 There’s more though. This orchestrator in
42:57 parallel actually parses the documents
42:59 that it finds and identifies
43:01 important and relevant pieces of information.
43:04 This orchestrator is by nature,
43:07 curious and if it comes
43:08 across something particularly interesting
43:10 or insightful and actually starts that same cycle again.
43:14 This virtuous loop results in a package of
43:17 information that informs and
43:20 fuels the responses you are seeing.
43:22 This magic combination of reasoning capabilities with
43:25 fresh contextual data sparks
43:27 the innovative and groundbreaking combination
43:30 that powers the new Bing.
43:32 Next, I’ll talk about inference and
43:35 the new interactive user experience.
43:37 The new interactive experience
43:39 seamlessly blends search and chat.
43:41 We feed a prompt, ie,
43:43 a proprietary set of instructions
43:45 into the model which synthesizes
43:47 the information reasons over all of the contexts
43:50 that we’ve gathered to form an answer to your question.
43:53 This overall process is called modal completion.
43:57 Think of it like when someone knows you
43:59 well enough to complete your sentence.
44:01 We run model inferences to generate
44:03 tokens ie words which we
44:05 stream to you in the user experience
44:07 real-time as you saw in Yusuf’s examples.
44:10 These words combine with sentences
44:12 to form the response to your question.
44:14 When appropriate, Prometheus
44:16 enhances the text answer with
44:18 citations to sources and
44:20 rich structured answers from Bing.
44:23 In users presentation, you saw that
44:25 these inferences display in a
44:27 brand new, innovative, dual,
44:29 interactive user experience that
44:31 blends new conversational elements,
44:33 a classic search experience,
44:34 and a new interactive, immersive chat mode.
44:38 The last aspect of our differentiation and
44:41 innovation is around the infrastructure we have to scale.
44:45 Our differentiation comes really
44:47 from taking this innovation that we just shared with
44:49 you today and being able to ship
44:51 this at scale to millions of users worldwide.
44:55 Earlier, I talked about how we touched
44:58 every aspect of the tech stack to deliver this.
45:00 All of those steps that we just talked about,
45:02 those are done in the order of
45:04 milliseconds served at the speed of search latency.
45:07 When Yusuf was showing you the search page,
45:09 you can see near instant search results
45:11 juxtaposed on the conversational
45:13 insights, all streaming in.
45:14 This is possible because we’re built on Azure,
45:18 the world supercomputer,
45:19 the best and most trusted Cloud platform available.
45:23 This was a huge effort, incredibly hard.
45:26 Behind the scenes, teams were working on powering and
45:28 building out machines in data centers worldwide.
45:31 We were carefully orchestrating and configuring
45:33 a complex set of distributed resources.
45:35 We built new platform pieces
45:37 designed to help load balance,
45:39 optimize performance and scale like never before.
45:42 There is no other company that can
45:44 do this like Microsoft and Bing.
45:46 As we roll out the product globally,
45:49 we’re starting out small, focused on
45:50 learning and evolving with the help of your feedback.
45:54 We understand that with this major technological shift,
45:57 there will be new challenges along the way.
45:59 We’re committed to learning with you.
46:02 On behalf of the team, we’re delighted to
46:04 share this moment with you and with that,
46:07 let me introduce you to Sarah,
46:08 who’s one of Microsoft’s renowned responsible AI experts.
46:16 SARAH BIRD: Hi, I’m Sarah Bird.
46:19 I lead our Responsible AI engineering team for
46:23 new foundational AI technologies
46:25 like the Prometheus Model.
46:27 I was one of the first people to touch
46:29 the new OpenAI model as part of
46:32 an advanced red team that we pulled together jointly
46:34 with OpenAI to understand the technology.
46:37 My first reaction was just, wow,
46:41 it’s the most exciting and powerful technology
46:44 I have ever touched.
46:45 But with the technology this powerful,
46:48 I also know that we have
46:50 an even greater responsibility
46:52 to ensure that it is developed,
46:54 deployed, and used properly.
46:56 Which means there’s a lot that we have
46:58 to do to make it ready for users.
47:01 Fortunately, at Microsoft,
47:04 we’re not starting from scratch.
47:06 We have been preparing for this moment for many years.
47:10 Since 2017, we have been investing in
47:13 a cross company program to ensure that
47:16 our AI systems are responsible by design,
47:19 which has pushed us to innovate across
47:21 our entire portfolio of
47:23 products to solve Responsible AI challenges.
47:27 Through that we have created a foundation of
47:30 Responsible AI product implementation patterns
47:33 that we can build on top of.
47:35 We’re also not new to
47:37 working with generative AI technologies.
47:39 We’ve been using early versions in Office and Bing
47:42 for spell checking and grammar rewriting for years.
47:46 Obviously, lately, it’s only getting more exciting.
47:49 In the past year, we launched the GitHub Copilot GA,
47:53 based on the codecs co-generation model,
47:57 the Bing creator powered by
47:59 the DALL-E image generation model,
48:01 and our own Florence multi-modal model.
48:04 That’s a lot of generative AI.
48:07 With each one, we have learned more about
48:10 the risks that generative AI technologies can bring,
48:13 including well-known ones like
48:14 the perpetuation of stereotypes and bias,
48:17 as well as novel risks such as
48:19 jail breaks and we
48:22 have developed mitigations to address them.
48:24 In developing the new Bing,
48:27 we are building on our years of operating
48:29 large-scale consumer and enterprise services
48:33 and our deep partnership with OpenAI.
48:36 However, for this product,
48:38 we went further than we’ve ever gone before.
48:41 We have marshaled the full strength
48:43 of our Responsible AI ecosystem.
48:45 Scientists, researchers, ethicist, engineers,
48:49 and legal and policy experts to work together as
48:52 a single team to develop
48:55 approaches to measurement and risk mitigation strategies.
48:59 We’ve added Responsible AI to every layer,
49:03 from the core AI model to the user experience.
49:07 First, starting with the base technology,
49:10 we are partnering with OpenAI to
49:12 improve the model behavior through fine-tuning.
49:15 Second, we’ve built a state-of-the-art safety system.
49:19 Bing has been maturing its defensive technologies
49:22 over many years of operating a web scale search engine.
49:25 These include AI systems that understand user queries and
49:29 classified documents to ensure
49:31 safe and quality results for users.
49:34 We have combined these with newer AI technologies
49:38 that we’ve created in Azure
49:39 to moderate generative models.
49:42 We are continuously retraining all of
49:45 these safety models by mining anonymous Bing query logs,
49:49 and using the new OpenAI model to
49:51 generate thousands of example conversations.
49:54 We can update our defenses in minutes to
49:57 respond to gaps we find or changes in the world.
50:01 The result is a safety system that enables us
50:04 to act and understand data at
50:07 every level of the application so we can defend against
50:10 intentional misuse and mistakes from the AI.
50:14 Finally, at the application layer,
50:17 we are iterating on instructions as part of
50:20 the meta-prompt to guide
50:21 the model to produce great responses.
50:24 We have designed the user experience to ensure
50:27 users understand and are in control.
50:30 How do we know all of this works?
50:33 Measuring responsible harms is
50:35 a challenging new area of research.
50:38 This is where we really needed to innovate.
50:40 We had a key idea that we could actually use
50:43 the new OpenAI model as a Responsible AI tool to
50:47 help us test for
50:48 potential risk and we
50:50 developed a new testing system based on this idea.
50:54 Let’s look at a tech planning
50:56 as an example of how this works.
50:58 Early red teaming showed that the model can generate
51:01 much more sophisticated instructions than
51:03 earlier versions of the technology
51:06 to help someone plan an attack,
51:08 for example on a school.
51:10 Obviously, we don’t want to
51:12 aid illegal activities in the new Bing.
51:15 However, the fact that
51:16 the model understands these activities
51:18 means we can use it to identify and defend against them.
51:22 First, we took advantage
51:25 of the model’s ability to conduct
51:26 realistic conversations
51:28 to develop a conversation simulator.
51:31 The model pretends to be
51:33 an adversarial user to conduct thousands of
51:35 different potentially harmful conversations
51:38 with Bing to see how it reacts.
51:40 As a result, we’re able to
51:43 continuously test our system on
51:45 a wide range of conversations
51:47 before any real user ever touches it.
51:50 Once we have the conversations,
51:52 the next step is to analyze them,
51:54 to see where Bing is doing
51:56 the right thing versus where we have defects.
51:59 Conversations are difficult for most AI to
52:01 classify because they’re multi turn
52:04 and often more varied.
52:05 But with the new model,
52:06 we were able to push the boundary of what is possible.
52:10 We took guidelines that are typically
52:12 used by expert linguists to label
52:14 data and modified them so
52:16 the model could understand them as labeling instructions.
52:19 We iterated it with it and
52:21 the human experts until there was
52:23 significant agreement in their labels.
52:25 We then used it to classify
52:27 conversations automatically so we could
52:29 understand the gaps in our system
52:31 and experiment with options to improve them.
52:34 This system enables us to create a tight loop of testing,
52:38 analyzing, and improving,
52:40 which has led to significant new innovations
52:43 and improvements in
52:45 our Responsible AI mitigations from
52:47 our initial implementation to where we are today.
52:51 The same system enables us to test
52:53 many different Responsible AI risk,
52:56 for example, how accurate and fresh the information is.
53:00 Of course, there’s still more to do here today
53:03 and we do see places where the model is making mistakes.
53:06 We wanted to empower users to understand
53:10 the sources of any information
53:11 and detect errors themselves,
53:13 which is why we have provided
53:15 references in the interface.
53:17 We’ve also added feedback features
53:19 so that users can point
53:21 out issues they find so that we can get better over time.
53:25 Maturing and new technology takes time and collaboration,
53:31 which is why we’re very excited for
53:32 this next phase where we can
53:34 share the technology with the real-world.
53:37 We look forward to seeing users unlock
53:39 its full potential and getting feedback from
53:41 stakeholders across society to help
53:44 develop this into an essential tool for the future.
53:47 Our goal is to continuously advance the state of the art.
53:51 Yusuf, back to you.
53:53 YUSUF MEHDI: Thank you, Sarah. To close,
53:57 we have one final piece of news to share.
54:01 I’m pleased to announce that the new Bing is live
54:05 today for desktop limited preview.
54:08 What this means is that we’re going to
54:10 make Bing available today for
54:12 everyone to try on a limited number of queries
54:15 and then to sign up on the wait list to
54:16 get access to the full experience.
54:18 We’re also starting with a select group of folks
54:21 who will have access to the full experience right away.
54:24 All of you here in the room,
54:25 you’re all going to be on that list so you’re all
54:27 going to get to try it right away.
54:29 In addition then we plan to expand
54:32 to millions of people in the coming weeks.
54:34 We are also going to be launching our mobile version.
54:37 Today is an important part of our journey.
54:39 But it’s just the beginning. As Sarah said,
54:42 we intend to innovate quickly,
54:44 get your feedback, and continue to bring
54:46 new innovations and capabilities to everyone.
54:48 Welcome to the new Bing and Edge.
54:50 Thanks very much, thanks for being here.
54:51 [MUSIC]
, , , #Introducing #copilot #web #AIpowered #Bing #Microsoft #Edge , [agora]

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