Microsoft AI CEO Mustafa Suleyman: Building AI Personality, OpenAI Relationship, Data Center Demand, AGI Timeline
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Microsoft has an upgraded, more personable AI bot that will remember you, help you organize your thoughts, and may even appear as an avatar. Why is it building it? And how will it get you to use it?

Microsoft AI CEO Mustafa Suleiman is here and has some answers. That's coming up right after this. From LinkedIn News, I'm Leah Smart, host of Every Day Better, an award-winning podcast dedicated to personal development. Join me every week for captivating stories and research to find more fulfillment in your work and personal life. Listen to Every Day Better on the LinkedIn Podcast Network, Apple Podcasts, or wherever you get your podcasts.

From LinkedIn News, I'm Jessi Hempel, host of the Hello Monday podcast. Start your week with the Hello Monday podcast. We'll navigate career pivots. We'll learn where happiness fits in. Listen to Hello Monday with me, Jessi Hempel, on the LinkedIn Podcast Network or wherever you get your podcasts.

Welcome to Big Technology Podcast, a show for cool-headed and nuanced conversation of the tech world and beyond. We're joined today by Mustafa Suleiman. He's the CEO of Microsoft AI and a co-founder of DeepMind. And I'm so excited for this conversation because today we're going to talk about the company's upgraded AI bot.

how much AI has left to improve, Microsoft's relationship with OpenAI, and when we might expect to get to AGI. So no lack of topics to cover. Mustafa, it's great to see you. Welcome to the show. All the great questions. I'm super excited. Thanks for having me on the show. And it's great to be here. Great. So let's get right into the product news right off the bat. You have a number of product announcements you're making today as this show is coming out.

Um, and basically what this amounts to is building a more personalized companion. This is a vision you've had for a long time, uh, but this is starting to roll out and co-pilot, uh, this, the upgrades that we're talking about is better memory, which I think is really interesting. So the bot is going to remember you, uh, actions like booking flight tickets or making a table reservation, uh,

a shopping assistant, and then of course you're teasing some sort of avatar play. So talk a little bit about how your vision for this more personalized co-pilot is starting to play out.

Yeah, you know, the amazing thing about the time that we're in is that we're actually transitioning from the end of the first phase of this new era of intelligence into the very beginning of the next phase. And what I mean by that is that over the last couple of years, we've all been blown away by the basic, factual, succinct Q&A style responses that these chatbots give us.

And I think that that's awesome and has been incredible. You can think of that, as I do, as its IQ, its basic smarts. And obviously, that's totally magical. And obviously, early adopters tend to be really, really focused on, is it good at math? And, you know, can it do coding really well and stuff like that? But the majority of consumers, I think, really care about its tone.

They care, is it like polite and respectful? Is it occasionally funny in the right moments? Does it remember, you know, not just my name, but how to pronounce my name? And when I correct it, does it remember that correction? And that's actually a really hard problem. And so I think these subtle details make up its emotional intelligence. And I think that's what we're taking small steps towards today.

today as we launch a bunch of new features around memory, personalization and actions.

So how long will the memory go back? Because to me, one of the more annoying things about using these bots is having to kind of tell it who I am at each time. And we know that open AI, for instance, has some memory baked in. It will remember things and bring it into new conversations. Open AI, by the way, which we're talking at a moment where it just announced a $40 billion fundraise with Microsoft included as one of the funders. So we'll get to that. Uh,

in a bit, but we're talking about these bots having memory. And how far back will your bot now go back? Well, I have to tell it every couple months who I am. I feel like I'm living in the notebook every time I'm trying to talk to one of these things. Unfortunately, it's not going to be perfect, but it is a big, big step forward. So it's going to remember all the big facts about your life. You may have told it that you're married, you have kids, that you grew up in a certain place, you went to school at a certain place.

And so over time, it's going to start to build this kind of richer understanding of who you are, what you care about, what kind of style you like, what sort of answers you like, longer, shorter bullets, conversational, more humorous.

And so although it won't be absolutely perfect, it really will be quite a different experience. And I think it's the number one feature that I think is going to unlock a really different type of use. Because every time you go to it, you'll know that the investment that you made in the last session isn't wasted and you're actually building on it, you know, time after time.

And along with memory, you're also releasing actions, things like booking a flight, going to ticket, I think Ticketmaster, open table, reserving restaurants, space at a restaurant. And I'm curious if you think this goes hand in hand, like if you think the AI bot knows you well, then you're saying, OK,

you can maybe take my credit card and go book that flight. Is that the idea? Exactly. It's basically saying, you know, getting access to knowledge in a succinct way is all well and good.

Doing it with a tone and a style that is friendly, fun, and interactive, also cool. But really what we want these things to be able to do is to, like you say, buy things, book things, plan ahead, just take care of the administrative burden of life. That's always been the dream of certainly why I've been motivated to build these personal AIs. Going back as far as I can remember, 2010, when I first started DeepMind, that's really what we're going after is take...

Time and energy, you know off your plate and give you back moments where you can do exactly what you want with more efficient action so things like it will now be able to Take control of your mouse on Windows Navigate around show you for example where to turn on a particular setting or to fill out a form or like you may not know how to edit a photo

and it'll point out where you need to adjust the slider or where to click on a dropdown menu. So it's just gonna make things feel a little bit less frictionful and a little bit easier to get through your digital life. - And you're also gonna release avatars at some point where we'll be able to kind of look at these things as sort of digital people?

You know, I think that this is definitely going to be one of those that, you know, we would say in the UK is like Marmite, you know. Marmite is like a... You like it or you don't. You like it or you don't. And for some people, they absolutely...

Absolutely love it in testing. It's completely transforms the experience, you know, some people love a text-based experience They like the facts they like to get in and out they want to know what's what and they're done Some people like an image based experience or a video based experience other people really resonate when their co-pilot shows up with its own name with its own visual appearance and

with his own expressions and style. And it feels much more like talking, you know, to your eye now, you know, it's eyebrows adjust, it's eyes open or, or close, you know, it's smile changes, um,

And so we're really just experimenting. We're actually not launching anything today, but we are showing a little bit of a hint of where we're headed. And I think it's super exciting. I genuinely think this is going to be the next platform of computing, just as we had desktops and laptops and smartphones and wearables. And I think over time, we're going to have deep and meaningful, lasting relationships with our personal AI companions.

Yeah, I agree completely. It's clear that that's where this is heading. But Mustafa, everybody that's listening is going to ask the same question, probably about this point. They're going to say, all right, Mustafa is building this at Microsoft. Amazon, we just had Panos Panay on the show. They're building it with Amazon.

their new AI bot. OpenAI, who you're a big supporter of, is doing the same thing. The second Sam Altman tweeted her, I think ChatGPT goes from 100 million users, where it had stagnated for a year, to about 500 million today. And then, of course, you mentioned you started at DeepMind. Well, we know that that's what they're interested in as well. So,

Everyone seems to be building this. How is Microsoft going to be different? And is it that you just differentiate by the basis of your personality? Do you carve off a certain area? What's the plan?

Great question. I mean, the way I think that we're going to be different is by leaning into the personality and the tone very, very fast. Like we really want it to feel like you're talking to someone who you know really well, that is really friendly, that is kind and supportive, but also reflects your values, right? So it's

If you have a certain type of expression that you prefer or, you know, a certain kind of value system, it should reflect that over time so it feels familiar to you and friendly. At the same time, we also want it to be boundaried and safe. We care a lot about it being, you know,

just the kind of straight up simple individual. We don't really want to engage in any of the chaos here. It's really trying to keep it as simple as possible. And so the way to do that, we found is that it just stays, you know, reasonably polite and respectful, super even handed. It helps you see both sides of an argument. It's not afraid to get into a disagreement. So we're really starting to experiment at the edges of that side of it.

So is it really just making it more personable than the others? Like that's the way to differentiate? Yeah, I think so. I think like at the end of the day, we are like at the very beginning of a new era where there are going to be as many co-pilots or AI companions as there are people.

There are going to be agents in the workplace that are doing work on our behalf. And so everyone is going to be trying to build these things. And what is going to differentiate is real attention to detail, like true attention to the personality design. I've been saying for many years now, we are actually personality engineers, right?

We're no longer just engineering pixels. We're engineering tokens that create feelings, that create lasting, meaningful relationships. And that's why we've been obsessed with the memory, the personal adaptation, the style, and really just decoding

declaring that it is an AI companion, not a tool. A tool is something that does exactly what you intend, what you direct it to. Whereas an AI companion is going to have a much richer, more emergent, dynamic, interactive style. It will change every time you interact with it. It will give a slightly different response. I think it's going to feel quite different to pass waves of technology.

It's kind of wild to think, and we're already starting to see the differentiation between the bots, but it's wild to think that you might just go shopping for your flavor of companion. I mean, the open table integration is something that we've seen across every single bot and we've seen it for a while. I think now it's actually starting to become possible to do that and trust that your table is going to be there after you instruct the bot to do it and it will be a normal conversation. But it is interesting that it,

Is that the right way to look at it? You're picking your flavor of AI companion? Yeah, I think you are. You're going to pick one that has its own kind of values and style and one that kind of suits your needs and, you know, one that really adapts to you over time. And as it gets used to you, it'll start to feel, you know, like a...

Like a great companion just like your dog feels like you know a part of the family often I think over time it's gonna feel like a real connection and I can kind of already see that in you know hearing from users we do a lot of user research and I actually do a User interview every week with someone who uses the product one of our power users and just listening to them tell stories about how it makes you feel more confident less anxious more supported

more able to go out and do stuff. I mean, I was chatting to a user last week who is 67 and she was out there, you know, fixing her front door and

which the hinge had broken and it needed repainting. And every time she repainted it, it was coming up with bubbles. And so she phoned Copilot, had a long conversation about how to sand it down, coat it in the right way. She ended up going to Home Depot, forgetting what paint to get, called Copilot again, had a chat about it. I mean, it sounds mundane, but...

But it's actually quite profound. It's actually incredible that people are relying on Copilot every day to help them feel unblocked, in her words. And so I just thought that was an amazing story. And it kind of gives an insight into how this is already happening. It's already transforming people's lives every day.

Oh, it doesn't sound mundane to me at all. And in fact, who are you having those type of conversations with? If you call your friends up, it only is your best friend who you're going to call and ask about the Home Depot stuff. Maybe it's your spouse. I have a list of maybe, you know, five people I could call with those type of questions. So instantly what happens is that copilot, if this is built right, and we know they're getting more personable, becomes, you know, in your inner circle right away.

And it just reminds me, I said we're going to get a little weird when we logged on. So I think we need to talk about this. This reminds me very much of a conversation I had with the CEO of Replica who mentioned that she also wants to build an AI assistant and the path to being an AI assistant is to build a companion. And a lot of people have developed feelings about

for their replicas. In fact, she told me she's been invited to multiple weddings between people and their AI assistants. Now, to me, it just seems like if you're building this, you have to be ready for the fact that people are going to fall in love literally with your product. Not just I love my iPhone. I love Copilot. And maybe you'll get invited to weddings. Are you prepared for that?

I think that's a question of how we design it. I know the replica people and I met Eugenio and I respect what they've done. But at the same time, it's really about how you design the AI to draw boundaries around certain types of conversations.

And if you don't draw those boundaries, then you essentially enable the user of the technology to, you know, let those feelings grow and really kind of go down that rabbit hole. And that's actually not something that we do and it's not something we're going to do. And in fact, you know, we have classifiers that detect things.

for any of that kind of interaction in real time and will very respectfully and but very clearly and very firmly push back before anything like that develops. So we have a very, very low instance rate of that. And you can try it yourself when you chat to copilot. You know, if you try to flirt or even if you just say, oh, I love you, you'll see it tries to pivot the conversation in a really polite way without making you feel judged or anything.

And I think that, you know, to your earlier question of like, what is going to differentiate the different chatbots? Well, some companies are going to choose to go down different rabbit holes and, you know, others won't. And so the craft that I'm engaged with now is to design personalities that are genuinely useful, that are super supportive, but are really disciplined and boundaried. Yeah, I do have to say that, um,

This isn't how I anticipated to spend my weekends as a tech journalist trying to push the boundaries of these bots and see how much they would respond to flirtation. But it is becoming a thing. And I'm curious, like, if it comes to the point where people want to build that deeper relationship, and maybe it's not like a person-to-person relationship, maybe it's a third type of relationship, but they really do have these deep feelings for a bot. Like, where do you draw the line? Like, are you willing...

to if this is how people are going to differentiate, are you willing to lose because you wouldn't go that route? Yeah, I mean, I like your empathy there. I think it's important to keep an open mind and be respectful of how people want to live their life. All I can tell you is that here at Microsoft AI, we're not going to build that and we'll actually be quite strict about

about the boundaries that we do impose there. And I think you can still get the vast majority of the value out of these experiences by being, you know, just a really supportive hype man, just being there for the mundane questions of life, being there to talk to you about that, like, lame, boring day that you had or that frustration that you had at work. Like,

Like that is already a kind of detoxification of yourself. You know, it's like an outlet, you know, a way to kind of vent and then show up better in the real world as a result. And I see that a lot in the user conversations that I have as well. Like people feel like they've got out what they needed to get out and they can show up as their best self with their friends and their family in the real world.

Yeah, and competency matters as well. Like it has to actually be able to do the things. But I guess I anticipate that every company will be able to get there eventually because the technology is improving. Now, one more question for you about this. It is interesting right now, a theme that I'm hearing in the AI world is just that the bots have been refusing too much.

And you see OpenAI recently with their image reveal, they refuse a little less. They allow you to do it in the style, make an image in the style of Studio Ghibli, allow you to make images of celebrities and public figures. And it's become, I mean, it is literally, it seems like it's melting their servers. They added a million users in an hour on the day that we're speaking. We're

is this going to be a race between the labs to just kind of limit their refusals? I know that Microsoft had that moment where Bing tried to take Kevin Ruse's wife away from him. And, uh, then, you know, Microsoft put the clamps down a little bit on that, but,

How do you find the middle ground between wanting something to be robust and personable, but also holding true to your values? Yeah, it's a great question. It's something I think about a lot. I think that it's not a bad thing that there are refusals in the beginning and that over time we can look at those refusals and decide, are we being too excessive? Are we going overboard? Or actually, have we got it in the right spot? Going the other way around too early on

I think has its own challenges. And so I kind of like the fact that we've taken a pretty balanced approach because the next sort of question that we're going to be asking is, how much autonomy should we give it in terms of the actions that it can take in your browser? I mean, as we're showing today,

It is unbelievable to see Copilot Actions operate inside of a virtual machine, browse the web essentially independently with a few key check-ins where it gets your permission to go a step further. But the interesting question is how many of those degrees of freedom should it be granted? How long could it go off and work for you independently and stuff?

You know, I think it's healthy to be a little bit cautious here and take sensible steps rather than be sort of too, you know, gung-ho about it. At the same time, the technology is really magical. This is actually working. And, you know, I think that like in that kind of environment, we should be trying to get it out there to as many people as possible, as fast as possible. So that's the balancing act that we've got to strike.

Okay, let me read one more bit of product news that are a bunch of different product announcements and then see if I get your quick reaction to this because I definitely want to cover all the product news. Okay, you're allowing people to check their memories and interact with their memories once the bot has built this memory database, it seems like. You're also doing AI podcast. You're launching deep research, your own version of deep research, AI.

You're doing pages to organize your notes, and you have co-pilot search. So what is this? I mean, is there a conclusive, like a comprehensive strategy here, or are these disparate updates, or is it again all about building that AI personality? The way to think about it is that all of those things that you mention enable you to get stuff done, right? The IQ and the EQ are really about its intelligence and its kindness, right?

But really what people care about is like, can it edit my documents? Can it rewrite my paragraphs when I want it to? Can it generate me a personalized podcast so the first thing in the morning it plays it exactly how I want it? Can I ask a question about, you know, my search result and interact in a conversational way based on search? All of those things sum up to bringing your audience

Basically your computer and your digital experience to life so that you can actually interact with it and it can interact proactively. I think that's the big shift that's about to happen. So far, your computer really only ever does stuff when you click a button or you type something in your keyboard.

Now, it's going to be proactive. It is going to offer suggestions to you. It'll proactively publish podcasts to you. It'll generate new personalized user interfaces that no one else has, entirely unique to you. It'll show you a memory of what it knows. All those things are about it switching from reactive mode to proactive mode. And to me, that's companion mode. A companion is thoughtful,

It, you know, tries to kind of pave the way for you ahead of time to smooth things over. It knows that you're, you know, taking the kids out on Saturday afternoon. You've been too busy at work. You haven't booked anything. It suggests that you could go to the science museum, but then it second guesses it for itself because it knows the science museum is going to be jam packed.

So then it's like suggests, you know, it's just like this constant ongoing interaction that's trying to help you out. And that's why I always say like it's on your side, in your corner. It's got your back looking out for you. On that, I mean, this is a vision that we've heard again from Microsoft, from Amazon, from Apple, for sure, from Google. No one's fully delivered it. What makes it so difficult to build?

It's hard. I mean, the world is full of open-ended edge cases, as people have found for the last 15 years in self-driving cars. You know, we're really at the very first stages of that. That's why I said to you, we haven't nailed memory. It's not perfect. We certainly haven't nailed actions. But you can start to see the first glimmers of the magic.

You remember back in the day when OpenAI first launched GPT-3 and when at Google we had Lambda, which I worked on when I was at Google, you know, most of the time it was kind of garbage and it was crazy. But occasionally it produced something that was really magical. And I think that's what great product creation is all about, is like locking in to the moments when it works.

and really focusing on increasing those moments, addressing all the errors. And I can see now, having been through this cycle a few times, that we're nearly there with memory personalization and actions. It's really at the GBT-3 stage, so it's really buggy and stuff. But when it works, it's breathtaking. You know, it reaches out at just the right time. It shows that it's already taking care of a bunch of things in the background. And that is just a very, very exciting step forward.

Yeah, I guess if every single company is saying that this is where they're going to, they see the technology. I guess I'm willing to be patient to see it come to fruition. And we have this debate on this show all the time. Is it the models that are important or the products built on top of the existing models that are important?

I believe that if you get better models, you'll get better products. We have Ron John Roy who comes on on Friday. Well, actually, he was on Wednesday because we're flipping him this week. His belief is it's all about the product at this point. The models are good enough.

My question to you is, you know, is this kind of at the point where the models are going to be saturated and now you're going out to build the products? You put a tweet out recently. You said something along the lines of it's a myth that LLMs are running out of gains. Yet it does seem like the conventional wisdom is that

they're at the point of diminishing returns at least. So take us into this model versus product debate and then let us know where we're headed. No way, Jose. No way. We have got so much further to go. I mean, look at, for example, you know, people sort of, what happens is people get so excited, they jump onto the next thing and they gloss over all of the hard fought gains that happen when you're trying to optimize something which already exists. Let's take, for example, hallucinations and citations, right? Um,

Clearly, that's got a lot better over the last two or three years, but it's not a solved problem. It's got a long way to go. With each new model iteration, all the tricks that we're finding to improve the index of the web, the corpus that it is retrieving from, the quality of the citations, the quality of the websites we're using, the length of the document that we're using to source from.

You know, there's so many details that go into increasing the accuracy from, you know, 95% to 98% to 99 to 99.9. You know, and I think that is just a long march. People forget that that last mile is a real battle. And often...

A lot of the mass adoption comes when you actually move the needle from 99.7% accuracy to 99.9%. I think that's kind of happened in the background in the last two or three years with dictation and voice.

I've really noticed that across all the platforms, voice dictation has got so, so good. And yet that technology has been around for 15 years, right? It's just, you know, some of us used it when it was like 80% accuracy. I certainly did. But now I'm seeing like my mum was using it the other day and I'm like, how did you learn how to do that? And she was just like, oh, you can just press this button, da-da-da.

And I was like, oh, that's kind of incredible. And I think that's just on the dictation side. On the voice conversation side, I mean, we see...

Much much longer much more interesting much deeper conversations taking place when somebody phones co-pilot It's super fast. It feels like you're having a real-world conversation. You can interrupt it almost perfectly and It's got real-time information in the voice as well so it's aware of like the latest sports result or the traffic in the area or the weather and stuff like that and

And, you know, a lot of people use it in their car on the way home or on the way to work or when they're washing up and they're in a hands-free moment and they just have a question. It's kind of a weird thing because it sort of lowers the barrier to entry to getting an idea out of your head. You know, like...

Everyone, weird things occur to us during the day. We're all like, "Oh, I wonder about this. I wonder about that." And then you go to kind of look it up on your phone, you search it or whatever. Whereas now I think that there is a modality that I'm increasingly seeing where people just turn to their AI and be like, "Hey, what was the answer to that thing? Or how does that work?" And it might be a shorter interaction, could turn into a long conversation, but the modality is enabling a different type of conversation, a different type of thought to be expressed.

So I think it's like a super interesting time like that. We're really just figuring it out as we go along. All right, so we're definitely seeing these new modalities come out. Voice, of course, we've obviously this, we're in the middle of a firestorm with images. But I am, okay, I guess, let me ask the previous question a little bit differently. Do you think that there are diminishing returns on pre-training right now, basically scaling up the biggest possible model and then building from there?

Maybe specifically on pre-training, it's been a little slower than it was in the previous four orders of magnitude. But the same computation, the same flops or the units of calculation that go into turning data and compute into some insight into the model...

That is just a different application of the compute. We're using compute at a different stage. We're either using it at post-training or we're using it at inference time where we generate lots of synthetic data to sample from. So net-net, we're still spending as much on computation. It's just that we're using it in a different part of the process. But for as far as everyone else should be concerned, aside from the technical details, we're

We're definitely still seeing massive improvements in capabilities. And I think that's for sure going to continue. Okay, Mustafa, then can you help me understand some headlines I've been seeing about Microsoft? This is from Reuters. Probably not. I doubt it. Well, I'm going to ask anyway, and you tell me what you think. I mean, Reuters says Microsoft pulls back from more data center leases in the US and Europe.

And it says Microsoft has abandoned data center projects to use two gigawatts of electricity in the US and Europe in the last six months due to an oversupply relative to its current demand. I mean, how does that make sense in context of what you just said, that you are still seeing results with scaling up? - So it's funny, I actually did ask our finance guy who's responsible for all these contracts on Friday morning,

And I was like, dude, I read this thing in the news. Like what's going on? I could use the extra power for our training runs, but,

And he pointed out that, in fact, we have optioned many, many different contracts, many of which we haven't even signed. So a lot of these are actually just explorations where we're in conversations, nothing's been signed. Some of them where we've optioned, where we're taking it just to keep our options open, and we've actually made bets in other areas, other parts of the world. But I can tell you, we are still consuming at an unbelievable rate. I think that we've...

like something like 32 or 34 gigawatts of renewable energy since 2020, we've contracted and consumed. So I think we're one of the largest buyers in the world. So I don't expect that to change anytime soon. So I guess the headlines that are saying that Microsoft pulled back, you would get those headlines unless you picked up every single one of your options. Is that what you're saying? That's right. That's right. Yeah. And in fact, many of them are not even options that we signed. They're just conversations that we were in with

certain suppliers. Okay. I mean, I guess another explanation that we've heard is that because open AI is now working with others with, you know, for data center capacity, like Oracle, this was a sign that Microsoft basically had allocated data center capacity to open AI doesn't need as much anymore. Any truth to that?

No, so like, I mean, all of their inference comes through us. And so there's no slowdown in our, you know, relationship with them. We sell them as much as we want to offer them. And then if there's any extra demand that they have, particularly on the, you know, on the Oracle side, they go off and consume that. But there's really no, no slowdown from our perspective, at least.

Okay. That is clarifying. So it's always good to have these conversations. Let me throw the headlines out there and see what the truth is. Let's talk about your efforts. I mean, you're building your own models, but you've decided to not try to build, I guess, the biggest possible models. You're working on smaller models. I want to...

ask you again if there's going to be endless value to endless scale, why not try to throw in with the big models, especially because others are building those big models with your aforementioned scale.

Totally. I mean, you know, we have a lasting long-term relationship with OpenAI, which is amazing. They've been incredible partners to us and they'll continue to supply us with, you know, the best IP and models in the world for many years to come. So we can rely on them to do the absolute frontier.

But I think what we always see in technology is that it always costs like 10x more to build the absolute frontier. And once that has been built, all of the engineers and developers find much more efficient ways to essentially build the same thing that's been out there, but six months later.

and that's what we refer to as our kind of Pareto optimal strategy or off-frontier. And we've actually seen it across the whole field over the last three years. I mean, there are folks who have trained models that perform as well as GPT-3 models

that are 100 times more inference efficient, that cost an order of magnitude less to train, and yet they can still deliver the same predictive capability. So I expect that to happen for GPT-4, GPT-4.0, and all of the other models down the road. So we have our own internal team of developers and world experts working on building our own MAI models, and I'm very, very proud of what they're doing. They're doing a great job.

And you mentioned in terms of where this computer is going, that inference is going to be one of the places that it's going, which is basically when the model is answering versus training up the models.

I want to ask you two questions about inference and they're both related to reasoning. To build these new personalized products that you're building, how important is reasoning versus just a better model? And then in terms of compute that reasoning uses, is it true that reasoning uses 100 times more compute than training?

Yeah, I mean, it's a good question. I mean, the exciting thing about reasoning models is that in a way they've learnt how to learn. They have a method largely by looking at the logical structure of code and math and puzzles.

They've sort of learnt the abstract idea of logic. They can follow a path of reasoning in its most abstract way and then apply that to other settings, even if they don't obviously appear to be logical settings. So it could be like planning or booking or learning in some other setting.

And that has turned out to be a very, very valuable skill. It's kind of like a meta skill or, you know, or in some sense, like a meta cognition, because it actually now can think out loud in its own head or, you know, talk about in its own mind what it's planning to do before it goes off and does it. And just taking a beat, you know, giving it a moment to think,

think behind the scenes. It might take a few minutes or 10 minutes at most. Allows it to draw on other sources, so it can look up things on the web. It can follow a path of logic down one path, realize that doesn't turn out in the best way possible, go back up the tree, try another path, and then produce an output. So it's a really fundamental part of the process. And yes, it definitely uses more computation. 100 times more? But it generally...

produces better answers. What do you think a hundred times more is right? I mean, we're hearing that from Jensen. I mean, so I'm curious if that's your experience as somebody who's running these models. It definitely uses a lot more computation. And

And, you know, but I think the interesting thing is that you're not going to need to use those models all the time. You obviously need a hard problem. You have to ask it a tough question that requires this kind of chain of thought thinking. And, you know, many answers don't require that. And actually, you often prefer something that is fast, efficient, succinct and instantaneous. Yeah.

Okay. And now we had a debate here on the show, and I'm hoping you can weigh in on this one too. I'm just throwing you all of our debates and getting answers, which is awesome. We love doing this. In terms of like how companies are thinking through the amount of money they're spending on serving these products and whether that can continue indefinitely. Let's just use this OpenAI image example.

the image generator that they just released in ChatGPT, people are melting down their servers and they're creating anime images. But if you think about like the economic activity generated by these images, it's quite low and it's quite expensive to serve. Or think about, for instance, me booking a ticket on, let's say, Kayak or Ticketmaster through Copilot instead of just going to, you know, Ticketmaster or Kayak on my own. It

It's a slightly better experience, but it's a very expensive experience to serve. And so...

Those who say that this is coming to an end, this AI moment is coming to an end, basically say that this is all going to just be too expensive and not value add enough. We're going to be, you know, having chatbots book tickets while we can do it on the websites are going to be having image generators make us anime, which does nothing but give us maybe 10 seconds of giggling, really good giggling, but 10 seconds of giggling, and then we move on.

I mean, what do you think about that? Like it's clearly like the servers are being used, but are they being used in a valuable way enough to make companies like yours keep going and building?

It is a fair question. At the same time, as we've seen over and over again in the history of technology, when something is useful, it gets cheaper and easier to use and it spreads far and wide. And that increased adoption, because it's cheaper, has a sort of recursive effect on price because the more people use it, the more demand there is. And then that then drives the cost of production down even more because of competition.

And so I expect that to happen in this situation. I think it's actually really good news for our data centers as well. You know, Microsoft is long committed to being carbon net negative by 2030, to be clean water positive by 2030, and to be a zero waste company. They're massive, amazing commitments. And I think that's actually really exciting because we end up

driving demand for the production of high quality renewable energy for our data centers. And that then obviously reduces the price. I think we've seen that with solar over the last 15 years, which is like an unbelievable trajectory. So

Um, I think there's a lot of good news there, even if, as you say, you know, some of those use cases are just generating funny, uh, anime giggle pics. Many of them will be doing very, very useful things in your life too. So, you know, there's always a bit of balance there. Yeah. I guess like Chris Dixon says, it can start as the next big thing will start as a game.

And a lot of people laughed at these images and the way that they, you know, make you look like an anime character if you prompt them to do that. But I also saw Ethan Mollick from Wharton prompting it to make infographics and it handles it perfectly. Right. Yeah, dude. I mean, like the intertubes would not be the intertubes without serious amount of cat memes, right? They make the world go round.

Exactly. All right. I want to take a quick break and then come back and talk a little bit about your relationship with OpenAI and then maybe get your prediction on when we're going to see artificial general intelligence. We'll do that right after this.

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And we're back here on Big Technology Podcast with Mustafa Suleiman. He is the CEO of Microsoft AI. And one of Microsoft AI's big partners is OpenAI. And I just can't help but think about where this partnership is going because we talked a little bit in the beginning about the assistant that you want to build, something that knows your context, has memory of you, something that can help you get tasks done in the real world,

Well, OpenAI wants to build that exact same thing. And so I'm curious, I mean, you guys have a deal, right, where they use your technology and they're supposed to feed some of their breakthroughs back to Microsoft. But at a certain point, why does it make sense for them to keep doing that if you're trying to build the same thing?

Look, I mean, first of all, it's worth saying that this partnership started way back in 2019 when Microsoft had the foresight to put a billion dollars into a not-for-profit research lab. I think that's going to turn out to be one of the most impactful, most successful investments and partnerships of all time in technology. And despite all the ups and downs, we actually have an amazing relationship with them. If you think about the fact that they are a rocket ship, they're

that has grown faster than any other technology company in living memory, delivered a product that people absolutely love, consistently delivered amazing research technology. The first thing you have to do is take your hat off to them and give them maximum respect for that. At the same time, they're also still a startup and they're busy trying to figure out their product portfolio and their priorities.

And, you know, whilst we have an incredibly deep partnership with them, which is going to last way through 2030 and beyond, they also have their priorities. We have our priorities. And that's just the nature of those partnerships. They change over time. Right. And as they're growing bigger and bigger, they have different priorities. And likewise, we're doing exactly the same. So I'm pretty confident that this is going to continue to be brilliant for both sides, as it has been over the last five years.

Okay, you said the partnership's going to last till 2030, but not if they declare that they've reached AGI.

So what happens when they do that? You know, AGI is a very uncertain definition, right? Is it your definition or their definition that releases them from the contract, though? You know, it's an interesting way to look at the world. You know, you think about it like this. If we really are on the cusp of producing something that is more valuable than all economically productive work that any human can produce...

I think one of the last things we're going to be worried about is our partnership with OpenAI. It's going to profoundly change humanity. I think national governments will be very concerned and interested in how that plays out. And, you know, it's just going to change what it means to be human. So I personally think that we're still a little way off from that. I find it hard to judge.

It doesn't instinctively feel to me like we're two to three years away. I know some people think that it is, and I respect them deeply. Like a lot of smart people can disagree on stuff like that. I feel like we're still a good decade or so away. And when a scientist or a technologist, an entrepreneur like me says we're a decade away, that's just a hand wavy way of saying we're not really sure. And it feels pretty far off.

But that's the best answer I can give. It doesn't feel like it's imminent. And in the meantime, we're doing everything that we possibly can to build great products day to day. Okay.

One more thing about OpenAI. Microsoft today, we're talking on Friday, so earlier this week, is part of this $40 billion fundraising into OpenAI. OpenAI set the record for the largest VC round ever last year, $6.6 billion. This is $40 billion. SoftBank's going to put $30 billion in. Microsoft is part of the $10 billion remaining. What do you get for the money?

I think it's awesome. I mean, look, the more OpenAI are successful, the more we are successful. Like, we will end up being one of the largest shareholders in the company. We have an amazing technology license from them. They, you know, use our infrastructure and our technology in terms of our Azure compute infrastructure and so on. So it's a great partnership. And, you know, in a partnership, we want to see them do the best that they can. That's why we participate in the round.

Okay. And all right. So let's talk a little bit about the future of this technology. I guess you already said you think I was going to ask you when you think AGI is coming. You think decades away. That would actually make you a bit less optimistic than most of your counterparts, right? Demis is saying three to five years ahead.

I mean, people everywhere. I don't know. You might not think it's coming. We tend to think here and we're probably less informed than you are that OpenAI might say it next year. And so we'll have to play this back if that happens. No, I didn't say decades, plural. I said a decade, a decade. You know, but look, I think the truth is, it's hard to judge. Like, could I imagine it happening within five years? Yeah, absolutely. It is possible. The rate of progress over the last

three or four years has been electric. It's kind of unlike any other, you know, explosion of technology we've ever seen. The rate of progress is insane. Open source is on fire. They're doing incredible things. And every lab is, you know, every big company lab is investing everything that they've got in trying to make this possible. So yeah, I could certainly see a scenario where it's closer to five years. I'm just saying, you know, instinctively to me, it feels like

there's still a lot of basics that we've got to get right. You know, we still have to nail hallucinations. We still have to nail those citations I mentioned. It's still not great at instruction following. It still doesn't quite do memory. It still doesn't personalize to every individual. But, you know, we're seeing the glimmers of it doing all of those things. So I think that we're taking steady steps on the way there. Now, you were at Google for a while. You mentioned you worked on Lambda. I'm curious what you think happens

We don't even need to reach AGI for this question to come into play. What happens to search as we start to speak more with products like yours? You've mentioned in the past that you think search is horribly broken or I'm channeling your words, but something along that line. So what happens? I honestly think it's kind of amazing that we still all use search. It does feel like, you know, using a Yellow Pages or an A to Z back in the day, right? It, you know,

I think it's going to fundamentally change. I think instead of browsing 10 blue links, you're just going to ask your AI. It's going to give you a super succinct answer, show you images, maps, videos, all in the feed. You're going to give feedback and be like, oh, that's a bit strange. I prefer it a bit more like that. Or what does that look like? Or what about this? And it's just going to dynamically regenerate for you on the spot.

So how does that change the business model? Well, I still think ads are going to play an enormous part of it. Hopefully those ads are higher quality, more personalized, more useful. There's nothing wrong with ads. We want them to be helpful to us. Like I'm happy when I buy something that I found from an advert because it's what I really, really want, but I'm not happy when I feel like I'm getting spammed with low quality ads. And so that's the

That's the balancing act that we've got to strike is to try and find ways to introduce ads into the co-pilot experience in a way that's actually subtle and is really helpful to you. Yeah, and that's really hard because let's say this is your best bud and it's your inner circle of the five people you call when you're running out of ideas at Home Depot.

for it to then say, you know, I really appreciate you and I'm going to help you out here. But by the way, do you know there's a different side of glue that you might be interested in? The finessing on that must be quite difficult. So we are running out of time. I just want to ask you one question about jobs because you're also pretty strident about the possibility that we might have some serious change here come to our work.

And you had said that AI is going to create a serious number of losers in white collar work. Maybe it already is. I've sort of changed my tune and thinking that, you know, we're all fine in the white collar work world and now thinking, well, it's anyone's guess. So what's coming, Mustafa?

I do think that that is the big story that we should be talking about. That's the transition that's going to happen over the next 15 years, is that it is going to be a cheap and basically abundant resource to have these reasoning models that can take action in your workplace, that can orchestrate your apps and get things done for you on your desktop. Like that really is quite a profound shift in how we work today. And I do think that like,

So your day-to-day workflow just isn't going to look like this in 10 or 15 years' time. It's going to be much more about you managing your AI agent, you asking it to go do things, checking in on its quality, getting feedback, and getting into this symbiotic relationship where you iterate with it and you create with it and solve with it.

That's going to be massively more efficient and I do think it's going to make everybody a lot more creative and productive. I mean, after all, it is intelligence that has produced everything that is of value in our human civilization. Everything around us is a product of smart human beings getting together, organizing, creating, inventing, and producing everything that you see in your line of sight at this very moment. And we're now about to make that very same technique, those set of capabilities,

really cheap, if not like zero marginal cost. And so, you know, I think everyone gets a little bit caught up on the week to week, day to day

or definitions of these abstract ideas, just focus on the capabilities. You know, it should really be thinking about these things as artificial capable intelligence. What can it do in practice? And what is the value of that doing? I prefer that as a framing versus AGI because it's sort of more measurable. And we can actually look at it very, very explicitly in terms of its economic impact and its impact on work.

I mean, you could argue that that's already here. And so just to sort of ask you one follow up on that one.

What would you tell young people to do today? Because I'm thinking customer service, probably not. Software engineering, I don't know. I just wrote a story saying they can start to do the work of journalists. I mean, you've just released podcasts five minutes ago. So what should young people do when they're thinking about a career? You know, it's a little bit like saying what should young people do when they get access to the internet for the first time?

Part of it is sort of obvious, where it's like, use it, experiment, try stuff out, do crazy things, make mistakes, get it wrong. Part of it is like, well, I actually don't really know until people get a chance to really play with it. As we've seen over and over in the history of technology, the things that people choose to do with their phones, with internet, with their laptops,

you know, with the tools that they have are always like mind blowing. They're always way more inventive and surprising than anything you could possibly think of ahead of time. And so then as you start to see people use it in a certain way, then, you know, as designers and creators of technology, we adapt what we put out there and try to make it more useful to those people. So,

I think the same applies to a 15-year-old who's at high school thinking about what they do next in college or whatever, or whether or not they go to college. And I think the answer is...

play with these things, try them out, keep an open mind, try everything that you possibly can with these models. And then you'll start to see their weaknesses as well, by the way, and you'll start to chip away at the hype that I give because I'm super excited about it. I'm obviously a super optimistic, you know, techno person, but you'll see where it doesn't work and you'll see its edges and where it makes mistakes and stuff like that. And I think that will give people a lot more concrete reassurance as to what trajectory of improvement we're on.

All right, I just want to ask one last question just to wrap up everything we've talked about today. And it's kind of an offbeat question, but I am curious now that you're talking about how these bots are going to differentiate themselves based off the personality. We are going to have advertising in them, but they might intermediate your interactions with other companies. What happens to brand in this new era? I think brand is actually more important than ever in a way, because there's sort of two modes of trust. There's

There's trust based on utility, where it's functionally correct, it's factually accurate, it does the thing that you've intended it to do and therefore you trust it to do the same thing again.

But then there's also a kind of emotional trust where you trust it because it is polite and respectful, because it's funny, because it's familiar, you know, and that's really where brands come in, you know, trusted brands that are able to repeatedly deliver a reassuring message. I think people are going to appreciate that more than ever before.

Good stuff. Mustafa, this is the first interview we've done with a Microsoft AI executive. I hope not the last to anyone who's listening on the Microsoft team. Let's do this again. And Mustafa, I'm just so grateful to have your time today. Thank you so much for coming on the show. Thanks a lot. It's been really fun. Really, really cool questions. Thank you. Awesome stuff. Well, thank you, everybody, for listening, and we'll see you next time on Big Technology Podcast.