AI Podcast | BlackRock

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Artificial Intelligence, or AI, is more than just a buzzword; it's a transformative force that has revolutionized industries and reshaped the way we live, work, and interact with technology. Oscar Pulido joins leaders of BlackRock to discuss how AI will impact the investing landscape of today.

The Bid – “AI And The Energy Grid: Solving for AI’s Power Needs”

Episode Description

The world remains abuzz over artificial intelligence, but rapid advancement and adoption of the technology is poised to drive a significant increase in power demand, and this demand could redefine energy consumption as we know it. Today we ask the critical question: is the energy sector equipped for the AI power revolution?

Will Su, of BlackRock's Fundamental Equities team, is one of BlackRock’s leading voices on all things energy. Will walks us through the sector’s pivotal role in the build-out and future of AI and digs into the potential investment opportunities and challenges.

Sources: “Electricity Mix” Our world in energy, January 2024; “What is U.S. electricity generation by energy source?” Energy Information Administration, “OpenAI Presents GPT-3, a 175 Billion Parameters Language Model” Nvidia, 2020; GPT-4 Details Revealed, Patrick McGuinness, 2023; Data Centers Around The World, United States International Trade Commission 2021; “North America Data Center Trends H2 2023”, CBRE 2024; “Electric power sector CO₂ emissions drop as generation mix shifts from coal to natural gas” EIA, 2021; “Electravision” JPMorgan, March 2024; “Fuel Mix” Ercot, March 2024; “Television, capturing America's attention at prime time and beyond” US bureau of Labor Statistics, September 2018.

Written Disclosures

This content is for informational purposes only and is not an offer or a solicitation. Reliance upon information in this material is at the sole discretion of the listener.

For full disclosures go to Blackrock.com/corporate/compliance/bid-disclosures

TRANSCRIPT

<<THEME MUSIC>>

Oscar Pulido: Welcome to The Bid, where we break down what's happening in the markets and explore the forces changing the economy and finance. I'm Oscar Pulido.

The world remains a buzz over artificial intelligence, but rapid advancement and adoption of the technology is poised to drive a significant increase in power, demand, and this demand could redefine energy consumption as we know it today, we ask the critical question. Is the energy sector equipped for the AI power revolution?

Today I'm joined by Will Sue from BlackRock's Fundamental Equities team. Will is one of BlackRock's leading voices on all things energy. He'll walk us through the sector's pivotal role in the build out and future of AI, as well as dig into the potential investment opportunities and challenges Will, thank you for joining us on The Bid.

Will Su: Thank you, Oscar. Great to be here.

Oscar Pulido: So, Will, we've talked about artificial intelligence on the podcast a lot, and it seems like there's no limits to the growth of this technology except the fact that it consumes a lot of energy and maybe that's the constraint. Tell us a little bit about why AI consumes so much power.

Will Su: The simple answer to that extremely complicated question is that information processing is energy, and we are processing more information today than we've ever thought of, even from just a few years ago. At its most fundamental level, computations are just moving electrons around a semiconductor chip, but when you multiply that very small electric current by trillions of calculations, the energy demand adds up very, very quickly.

I think Rob Goldstein mentioned this the concept of AI is not really anything new. The MIT AI lab was started in the late 1950s, we did have a breakthrough moment in 2017 when a team of researchers wrote a paper about the transformer, which then became the architecture for today's large language models or LLMs. Now, these models are being trained on trillions of parameters and tokens that make them high quality, high capacity, and able to contextualize the questions that they're being asked.

And just to give you an idea of how big the computational power we're talking about is here. ChatGPT4 was trained on about 70,000 Zetta flops of compute power. That's 70 trillion trillion operations per second. Mind bending numbers. And as that number grows over time, that's why we're seeing this recent interest in meeting the power demand of AI.

Oscar Pulido: Did you say Zetta flops? 'Cause I'm going to need a glossary. I think as we talk more about artificial intelligence, it feels like the terminology is new to a lot of people. And when you talk about power and the quantity, help us understand like, how much are we talking about on a global scale?

Will Su: So as anyone who tried to model this out can tell you it's very hard to have a lot of confidence for 10, 20 years down the road when you're looking at something with such exponential growth. That being said, we did build our own model because as they say, all models are wrong, but some are useful. In building this model, it's helped us understand what the key variables are and maybe how the shape of that future power demand might look like.

And the punchline is, we think there could be up to 1000 terrawatt hours of incremental electricity demand for AI by 2030, and that would be about 3% of global electricity. And keep in mind that the internet today already consumes 2 to 3% of global electricity for things like data centers, networking transmissions and increasingly for blockchains. In aggregate you could see total internet demand, including AI, make up 6 to 7% of global electricity demand by 2030.

Oscar Pulido: And how is the world going to manage that power demand because it's incremental on top of what is already the demand for power, right?

Will Su: Right. I think we can first dig a little bit into what is driving that AI demand. There's really three roughly equal buckets in our 2030 outlook.

One is for training. So that's the power that it takes to train these very large models. And again, just to give you an idea of the scale in 2022 Chat GPT-3 came out. It was trained on 175 billion parameters and 300 billion tokens. And the amount of energy it took to train could power about 90,000 US homes for a year.

Now you fast forward to 2023 when Chat GPT-4 came out, that model was reportedly trained on 1.8 trillion parameters and 13 trillion tokens. And the energy it took to train that could power 2.5 million U.S. homes for a year, and these models are getting bigger by the day.

And the good news there is with each generation of semiconductors, each generation becomes about 50% more power efficient. So, it takes half the amount of power for one calculation. It's not enough to offset just how quickly the models are getting bigger, and then remember, more players are entering this game, globally, not just in the US but also in Europe and Asia. So, you add it all together and training really represents the bulk of the power growth that we see for AI in the coming few years.

The second bucket for demand is something called querying. So that's when consumers, businesses, and other computers start to ask questions to these trained large language models. And in our model, we think you could see up to 30 billion AI queries per day by 2030. For comparison today, we make about 10 billion internet searches per day. But you have to remember that not all queries are created equally, right? A text-based query takes about the same amount of power as an internet search, but an AI generated photo takes up to 30 times more power, and a 60 second AI generated video takes up to 7,000 times more power than a text query. And video is big, it's 57% of all internet traffic today. So how the consumer adapts to AI video is really one of the key variables that'll determine just how much energy we're going to require to power AI.

And then the third bucket is really for data center operations, mainly for cooling, because when you're doing trillions of calculations per second, these chips run really hot.

So yes, 1000 terrawatt hours by 2030. That is a big number. I think it's a challenging task to meet that demand, but not an impossible one.

Oscar Pulido: And maybe you can expand there because you shared a lot of numbers. you said the word trillions a couple times. the percentage increases that you've cited, particularly when you talked about how we use artificial intelligence to query, was quite large. So, what role do renewables play in this energy demand? I'm thinking about things like wind solar, are they the major component or are there other, sources of energy that we're going to rely on?

Will Su: So, renewables are by far the fastest growing source of power generation. In the last 20 years. They've gone from almost nothing to 13% of global power generation. And they will continue to grow at a very fast pace.

Without a doubt, renewables are going to play a big part, in powering AI, but also in powering this overall theme of electrification of our energy systems. Now renewables have one really big drawback when it comes to powering AI, which is intermittency. Right? Let's zoom into the Ercot grid in Texas, which is the largest wind market and the second largest solar market in the U.S.

So, it has a lot of renewables, and if you just zoom in on a typical day, the solar power tends to peak out between 8:00 AM and 7:00 PM when the sun's shining. And the wind peaks when the wind speeds are the highest, which is usually from midnight to 7:00 AM when you wake up. Peak demand really happens in the hours of 8:00 PM to midnight. That's when people are at home relaxing, watching TV, streaming, checking their social media. And you'll see that during that period, natural gas demand really increases to meet that gap that can't be met by wind and solar.

And this is probably a good time to talk about nuclear, which people don't think of a lot, but it's actually today the largest source of carbon free power generation. It makes up about 9% of global power.

But I think as governments around the world start to realize how much electricity growth there's going to be, there's starting to be a change in thinking. And in countries like South Korea, Japan, Italy, and here in the U.S. you're seeing regulators extending previously planned shutdowns of nuclear plans, and even in some cases, allowing them to restart after they've already been shut. So definitely don't count nuclear out in this low carbon way to power AI going forward.

Oscar Pulido: So, it sounds like the, the demand is so significant that it is causing even some sources of energy that in the past that felt like, were becoming less of a priority to reenter the focus. Ultimately what you've said is there's a lot of different sources of energy that are going to help, power the AI demand. You mentioned nuclear gas, but also renewables. And if I could focus you on the US for just a second, artificial intelligence is not just the US topic, but it is the part of the world where the build out is really gaining a lot of momentum and therefore, how is the U.S. thinking about the power supply for artificial intelligence?

Will Su: we really should talk about one of the biggest unsung triumphs in the energy transition so far, which is the U.S. Power grid has decarbonized itself by a third. Over the last 20 years, and about 60% of that came in the form of cheap and abundant natural gas as a result of the shale revolution that allowed us to substitute out much more polluting coal.

You saw a coal share in the last 20 years drop from 50% to 16%. Natural gas went up from 19% of U.S. Power generation to 42. The other 60, the other 40% came from renewables. So, renewables, again, grew from almost nothing 20 years ago to 14% of the US power grid today. So, there's already a really strong track record of partnerships between natural gas and renewables to combine and help us decarbonize.

Now, when you think about AI, and you think about data centers. The U.S. has about one third of the total data center capacity in the world, and I'm very confident that share will grow over time because we have the leading technology companies that are leading this AI revolution. And then we are also blessed with abundant resources, both traditional and renewable.

If you look at a map of where these data centers are located in the U.S., you'll see that they're mostly in these big clusters that are located close to population centers. So almost half of all data centers in the U.S. are in Virginia. They're almost all in this six square mile tiny area called Data Center Alley near Arlington.

There's other big clusters like Hillsborough, near Portland, Oregon. there's also growing clusters around Ohio, and you'll see a problem if you juxtapose that map onto one where the renewable resources are best in this country. The source of greatest solar radiation is in the southwest U.S., so that's places like Southern California, Nevada, New Mexico, and where the wind speeds are the highest are down the middle of the U.S. In the windy corridor that goes from the Dakotas down to Northern Texas.

And they don't really overlap with where the data centers are located today and where the most growth is likely to happen in the coming years. And then to make matters worse, this country's really falling behind in making long distance transmission investments. We're making one eighth the mileage of new transmission lines than we did 10 years ago.

That's a result of a number of regulatory and economic challenges with interstate infrastructure, and this is where natural gas is going to come in. It's a proven, mature technology. It's much cleaner than coal. It plugs easily into different grids, so it shapes my view that I think at least half, if not more of the incremental power for AI in the U.S. will come from natural gas and the balance will mostly be met by new renewable developments.

Oscar Pulido: Data Center Alley doesn't sound as glamorous as like Silicon Valley, but it seems like it's also very important. Let's come back to your role as an investor. You spend your day thinking about companies to invest in, and if you follow the markets over the last couple years, it's been all about technology. But we're having a discussion about the energy space, and so presumably that means there's investment opportunities in the energy sector. Where are those?

Will Su: Absolutely. So, as a value minded income investor, I have thought for a long time that energy is an undervalued sector because the market under appreciates both the volume and the duration for which the world needs oil and gas for the decades to come.

And I think this recent focus on how do we power AI just shines yet another spotlight on how power hungry our world really is. And over time, I think that will help this sector rerate higher. Now, aside from that, I think the energy sector actually might be one of the most underappreciated beneficiaries for all the technological gangs that'll come with better generative AI.

Some of the world's largest supercomputers are actually owned by large energy companies. Why? Because they perform a number of very computationally intensive tasks. Things like asset optimization, algorithmic trading, four D seismic imaging for new resource discoveries.

And I'll give you one specific example, which is the industry is using more and more of what's called a digital twin. So, this is like a virtual replica of a real-world asset, something like a refinery or an offshore platform. It's just got so much data inside of it that you can do a lot of really interesting and exciting things. Things like predictive maintenance, fixing things before they break, things like stress, testing them for severe weather events or identifying methane leaks and reducing emissions that way. So, I think there's more than one way to win with energy when it comes to the theme of AI that's greatly underappreciated by the market today.

I think the other sector that deserves some airtime here is utilities. So, utilities are a yield driven high dividend paying sector that's been somewhat out of favor in the last few years in a rising rate environment. But as the U.S. Grid goes from not having much growth for the last 20 years to needing to grow one to 2% per year going forward, there's a big opportunity for these utilities.

It'll come after an initial period of heavy investments now, which utilities will win depends very strongly on what regulatory regime and what geography they operate in.

Oscar Pulido: And it's interesting just to hear you talk about energy and utilities. I'm reminded we spoke to your colleague Carrie King, who reminded us that while it has been a very tech-driven market, in the last couple of years, there are opportunities that are starting to appear. And you're zooming in on the energy and utility sector as a function of artificial intelligence and power demand. But for an investor who is looking at this space, what should they be considering as they think about investing?

Will Su: The energy sector contributes about 10% of the S&P 500's net income, but it makes up less than 4% of the index by market cap. And I think that valuation disconnect is driven by this persistent, and in my view, misplaced fear that this sector has no long-term growth. Because I think as we sit here talking about breakthrough technologies like generative AI, it is important for us to remember that there's many different poles for incremental energy demand in this world, and all or nothing approach to energy just isn't going to work.

We have to find ways to help the traditional energy sources become cleaner and more responsibly sourced. At the same time, we scale up our renewables portfolio together, and only together will they be able to power the world forward in a pragmatic energy transition.

Oscar Pulido: Right, the world is evolving, where the demand for energy will come from is changing. With the number of statistics that you've been able to cite about the energy sector and artificial intelligence, where does this passion come from? How did you get interested in this space?

Will Su: Oscar, I'm having flashbacks to 16 years ago when I started my career at a large investment bank in the equity research department, and my recruiter said, you can either join the internet team or the energy team. And I had no hesitation. I said, energy, it's supply-demand driven. It's quantitative. The world needs this stuff. And you fast forward to today, and I think the internet index has outperformed energy by about 1,100%. But if you gave me a time machine to go back, I will make the same choice over again.

This job has taken me to really exciting places all over the world. Offshore Norway, the Permian Basin in Texas, the Bakken in North Dakota, or deep into the Amazon jungle in Guyana. That's a country that's going to go from the second poorest in South America to having the same GDP per capita as Brazil in less than a decade because of their resource development. So, it's been a really thrilling ride so far and I look forward to more of what's to come.

Oscar Pulido: We're glad you made that decision 16 years ago and that you would make it again, if you went back in time. Thanks for sharing all this insight on the energy sector, on artificial intelligence, and thank you for doing it here on The Bid.

Will Su: Thank you, Oscar,

Oscar Pulido: Thanks for listening to this episode of The Bid. If you've enjoyed this episode, check out our episode with Rob Goldstein and Lance Bronstein. Where they discuss AI through a COO lens and what business leaders are considering as AI is advancing.

<<SPOKEN DISCLOSURES>>

This content is for informational purposes only and is not an offer or a solicitation. Reliance upon information in this material is at the sole discretion of the listener.

For full disclosures go to Blackrock.com/corporate/compliance/bid-disclosures

MKTGSH0524U/M-3571844

AI and the energy grid: Solving for AI’s power needs

Will Su, of BlackRock's Fundamental Equities team, is one of BlackRock’s leading voices on all things energy. Will is walks us through the sector’s pivotal role in the build-out and future of AI and digs into the potential investment opportunities and challenges.

The Bid Ep 164. GenAI From a COO Lens

Episode Description:

Join host Oscar Pulido as he explores the transformative power of AI and its impact on the financial services industry. Rob Goldstein, Chief Operating Officer of BlackRock, and Lance Braunstein, Head of Aladdin Engineering, share their optimistic perspectives on Gen AI and the evolution of technology over the past year. They discuss how AI is reshaping work patterns, empowering individuals through natural language interfaces, and revolutionizing client expectations. Discover how AI can be harnessed at the industry level to enhance productivity, leverage data, and drive better investment outcomes, while still emphasizing the crucial role of human supervision. With a focus on talent development and the democratization of data, they envision a future where AI augments human capabilities, making organizations more efficient and individuals more adaptable.

Written Disclosures in Episode Description:

This content is for informational purposes only and is not an offer or a solicitation. Reliance upon information in this material is at the sole discretion of the listener.

For full disclosures go to Blackrock.com/corporate/compliance/bid-disclosures

TRANSCRIPT:

<<THEME MUSIC>>

Oscar Pulido: Welcome to The Bid, where we break down what's happening in the markets and explore the forces changing the economy and finance. I'm your host, Oscar Pulido.

The advent of AI has radically altered the landscape of work, reshaping the fabric of industries and prompting a monumental shift in how tasks are executed, and decisions are made within the financial services industry. AI has induced both awe and apprehension. The financial world stands on the precipice of an AI driven transformation where the balance between machine intelligence and human ingenuity heralds a new era of possibilities, challenges, and responsibilities.

Joining me today is Rob Goldstein, BlackRock's, Chief operating Officer, and Lance Bronstein, head of Aladdin engineering, BlackRock's Portfolio Management software. Rob and Lance will help us consider the issues facing business operators. From how to harness this technology to amplify human capabilities, redefine roles, upskill the workforce and recalibrating approaches to risk management and client interactions.

Lance and Rob, thank you for joining us on the podcast,

Rob Goldstein: Awesome. Great to be here.

Lance Braunstein: Thank you.

Oscar Pulido: Lance, this is your first time, I think you're what we refer to as a longtime listener, first time caller. And Rob, it turns out a little fun fact is that you were actually the first guest on the first ever Bid podcast that we recorded, the topic was around FinTech, the sort of intersection between finance and technology, so it's very appropriate to have you back.

Rob Goldstein: I actually assumed I was coming to get my royalty checks. Is that not what's happening here?

Oscar Pulido: We know you've been busy, so we took a little bit of time in welcoming you back. That was about five years ago, you didn't spend a lot of time talking about AI on that episode at the time, but a lot's changed. It's 2024 and AI is top of the list of topics that we've been addressing on the podcast, and this is a really great opportunity to hear from two business leaders at BlackRock about how it's impacting the business.

So, Rob, maybe I can start with you. I'd love to hear your perspective on Gen AI, and just how it's evolved over the past year because it seems like things are evolving quickly.

Rob Goldstein: Taking a bunch of steps back, AI as a concept is not a new concept. In fact, sometime in the 1950s MIT started its AI lab. So as a broad concept, AI's been around for a long time.

So, it's January 2024, but if you really think about it, from the period of time, more or less of Davos last year, so in January 2023 till now was actually, in my opinion, one of the most extraordinary times in the history of technology.

And there were major, major, major step functions in terms of technology, but more importantly, it's less that there's sort of new math. It's this confluence of data, compute power methods that have existed for a long time all coming together in a way that effectively has enabled or really started the transformative journey to enable English to be how people interact with computers.

People have grown accustomed to interacting with computers in certain ways, they've grown accustomed to interacting with them, with a mouse, with a keyboard, through your phone, with your thumbs. But for the first time, there's enough data, there's enough compute power, there's enough technology to fit models that enable you to talk to a computer, and to have it talk back to you. That capability, that step function is actually, in my opinion, one of the most transformative technology step functions we will see in our lifetime, this is going to really change how people think of technology.

Oscar Pulido: I'm glad you mentioned that AI is not A new concept. It's popular now, but that it's something that's been around for decades, and we actually talked about that on a few episodes, last year with some of our investment leadership. People like Jeff Shen and Brad Betts, who talked about, Dr. Steven Boyd and, the AI labs that we've set up. I'm also fascinated that you've been in the industry and with BlackRock for 30 years, very close to technology, and that you're saying in the past year is some of the most transformational change that you're seeing. So, how does that impact the financial services industry. You're the COO for BlackRock so you're the pacesetter for change. so, what are financial services company doing to try and stay up with that change?

Rob Goldstein: It's actually a super fascinating question because when you go to meetings and start talking about this stuff, people want to start talking about humanity, robots, when are the robots taking over humanity. So often I'm the one saying that's super important, but we need to focus on this through the lens of being in our jobs in a company.

The way I like to think about it, this whole concept of language and English being the way people interact, is a very different way technology is used and it's a way that really impacts work patterns. It's a way that really impacts how companies view productivity, efficiency, those broad concepts.

I'll give you a couple of examples. Lance and I were, leading a group of people as we presented this to the board. We wrote a presentation, and in the presentation, we spoke about a variety of the aspirations that we had for BlackRock, but the key theme is that all of the technology tools we build, people should be able to just type in what they want the tool to do, and the tool should be able to do that. That's number one.

Number two is we produce a lot of client reports. performance evaluations, credit write-ups, prospectuses, whatever it is. That first draft why can't that be done by a computer? Normally the work pattern would be someone would then take that away and four days later you'd get a draft of the letter. Why can't, right after that meeting, we get a draft of a letter that's from a computer and then we all comment on it.

So, what we did for the board presentation is we wrote a PowerPoint presentation explaining what we were going to do, the strategy, the risks, all of those components, everything you would imagine. Then, we actually fed it to ChatGPT within what we call a walled garden, basically our own version of effectively running the ChatGPT models, but within our own infrastructure, so we're not leaking any information. So, we took that presentation, put it through the model, and we said write a 1000-word executive summary, because in addition to submitting a PowerPoint presentation, we also would submit a, an executive summary more in like Microsoft words, something that's more, literal than a deck.

I got the memo coming out of it, and I gave it to two people who are among the most critical people in terms of looking at memos. One was Larry Fink, and one was Martin Small, our CFO. Martin came into my office and Martin said, I don't know why you didn't mention this, it's missing this, the tone's a little, you should be more confident in what we've done. And I was like, “Oh, Martin, it was written by a computer.” He was like, “Oh, really?” He had no idea. And then with Larry, it was the same thing. “Hey, the tone of this is off.” And I said, Larry, it was written by a computer. We could set that tone.

I could have said, Here's a PowerPoint presentation, here's 10 memos. Give me a memo in a thousand words that summarizes this PowerPoint presentation in the tone of these other memos.

And I think if you look at it through the lens of A COO, the productivity that unlocks is beyond imagination. If you look at it through the lens of a normal person in terms of helping you in daily life through being able to talk to a computer and have the computer talk back to you, it really is a remarkable, transformative opportunity.

Oscar Pulido: And that word productivity, the two of you are senior leaders and any time saved is very helpful, but it helps people across an organization. The example you just gave time saved and being able to invest it elsewhere. And Lance, you sit at the forefront of the technology platform that BlackRock runs and what has what Rob has discussed around the evolution of gen AI mean for an organization that has a tech platform that employs engineers, what do those engineers do now when the gen AI tools can do the kind of stuff that Rob described?

Lance Braunstein: Before I get to that, let me riff on the idea that this is really expansive. So, when we say that this will impact productivity across job families, we mean that quite literally. We talked about executive presentation, getting to a first draft of a PowerPoint, a Word document. But imagine getting to a first draft of an application. Having a software engineer, not start with a blank slate, but say, do the thing that is like this other thing that we've done before, or an analyst summarizing broker, documents or a salesperson summarizing all of the interaction notes. The idea here is that this democratization of data and models really is expansive across the enterprise. It's every job family, HR professionals, legal professionals, compliance professionals will work differently. How does this impact the technology world? in a couple of ways. So, if you have a technology platform, it will change the way that you think about the user interface and the user experience.

First, the standard will become a chat interface, exactly what Rob was describing, which is an English language, natural language interface to the computer rather than code or rather than complex application navigation.

Second, the way that you think about your information architecture, this is the way that information and data interrelates changes. So instead of having to navigate four different applications to determine my risk to book a trade, now I can simply ask a chat interface like 'Tell me what my risk is and on the strength of that risk rebalance my portfolio in the following ways.' That changes the navigation paradigm in a pretty profound way.

And then finally, I think this notion of democratization of data and models is really powerful. The idea that more people will participate in a broader set of data-driven decisions than they have historically. And I'm not talking about data scientists, and I'm not talking about PhDs. I'm talking about every single person involved in the investment life cycle now will have more data at their fingertips than they ever have before. That is hugely powerful.

So, if you are at the helm of a technology platform, thinking about the interface, thinking about the democratization of data, thinking about your information architecture, changes.

Oscar Pulido: I have two kids, I'm listening to you both talk and you're describing this world where, things seem a little bit easier. Like I can get to a more advanced part of the work or the project sooner. And when I think about my kids, part of how they learn is trial and error. They learn from mistakes that they make, and we learn from our mistakes. So, is the environment that you're both painting one where it's different in terms of how you develop talent because they don't get to learn as much from their mistakes? And maybe I'm not thinking about it, right, but what does that mean for talent development in an organization?

Lance Braunstein: First, I think it's what Rob said a minute ago, this notion of getting to a first draft sooner. Part of the power of these large language models is prompting the model often in a very precise way. So, like when Rob talked about tone, you could create the initial draft and then go back and say, I'd like it to be in the tone of this other document, or I'd like you to refine this into a set of bullet points, et cetera, et cetera.

So, in terms of development and learning, the idea that you could get to that first draft of your term paper of your science project faster by harnessing more data and more models, I think is a powerful learning tool. That is not cheating and getting to the Wikipedia of result sooner, it is actually harnessing more information.

Then the interactivity that you have with that first draft or with the model, I think is another learning opportunity. So, the ability to prompt in an increasingly precise way to me, drives a greater analytic mindset. Rob and I talk about this notion that we all are going to become developers, when you think about the human computer interface becoming a prompt in English, that means all of us are writing code. We may not think of it as code, those prompts may not look like code, they may look like an English language sentence, but they're code. And they will generate code in some cases. So, the precision with which you have to prompt the computer increases over time. So that learning to be more precise, more analytic, more data-driven, is a talent opportunity. It's a learning and development opportunity.

Rob Goldstein: Lemme just add, we try very hard to be tech optimists and it's amazing how many things through the years you could point to as given this new technology, this means humanity's going to become much more stupid and humanity is doomed. But I'll give a couple of examples through my own personal lens.

So, my dad was a financial advisor my dad growing up would work almost every night, but at nine o'clock, he would stop working because it was not polite to call people at home, after nine o’clock, and once email came about, if you get an email at nine o'clock and you don't answer it by like 10 o'clock, you're considered rude.

So, everything just adapted, and if anything, expectations change. It created a huge productivity boom in theory. As opposed to having to FedEx documents, you can now email documents, that's a productivity boom. But it didn't seem like the amount of work went down, just expectations changed. And I think what happens with technology is as it empowers this new productivity and these productivity step functions, it brings with it changing expectations.

People can look at these technologies through different lenses. I look at it through the lens, I think there's going to be a giant productivity boom. I think there's going to be a giant expectations boom. And I think that how people get smart will change. I don't exactly know how, but I know that humans are very adaptable. Technology's a tool that actually makes them even more adaptable. And I think that combination, I have confidence that people are going to get smarter, not less smart.

Oscar Pulido: You've given examples of the productivity boom, right? You mentioned the board presentation and the memo and, but now you just talked about the boom in expectations, and you touched on your dad being a financial advisor. That's a very client-oriented profession as most of financial services is. So, talk a bit more about how does this change what clients. Expect now that generative AI is more interwoven in business.

Rob Goldstein: Absolutely. And, if you zoom out for a second at the state of the industry, on the wealth side, most clients have websites or apps that they could access. They could see things in real time, but the truth is you get reporting once a month. And on the institutional side, it's equally the same, if not even more so once a month.

Oscar, if I said to you in the year 2030, do you get reporting, once a month? I think you'd be, hmm, I don't think so. Ultimately, you could imagine, every day, every hour, every trade, whatever, if you want a summary of your portfolio and how it's changed, you have access to one. I think it's going to be very hard to fulfill that expectation with people. I think it's going to be very easy to fulfill that expectation with technology.

And that is why that English component, the ability to talk to the computer in English and have the computer talk to you in English, that is why that is a whole new unlock with regard to technologies that will be profoundly impactful in terms of the Day-to-Day lives of people, in ways that are unimaginable.

Oscar Pulido: You both mentioned this point a couple times, so worth reiterating that the language that you use to interface with computers has been coding languages for many years. But what you're saying is that now it's English is that language to interface with the computer and the coding goes on in the background, but by, having that shift, more people can interact with the machines that are increasing productivity in businesses or the economy.

Lance Braunstein: Yeah, that's correct. the question often comes up because we've lowered the barrier to the human computer interface, do professions like software engineering, software development, system engineering, data analytics go away? I believe the answer is A hard no. Not only do they not go away, but the burden that we put on our servers, on our computers, as we expand the aperture of the user base- in this case, the prompt engineers, who is every human who will interface with a large language model- actually grows the burden on resilience, scale performance security increases.

So, the need for really talented engineers who could construct the backends. of all of these systems that now have quite an elegant low barrier to entry as a co-pilot or a chat, I think that need grows over time. Now I am like Rob, a tech optimist and pragmatist, I am thinking the hard next 12 to 24 months, there are jobs to be done, they will be enabled by these generative AI technologies and these models, but they are jobs that we could predict.

Rob Goldstein: If we were having this conversation pre covid, the technology that we would be talking about was autonomous driving. And it was like, why would your kids get a driver's license? Don't buy a new car. Everything is going to be autonomous driving.

Then if you think about what happened, you basically had a once in a hundred years, scenario, where two people couldn't get into the car with each other unless they were in the same family pod. So, if ever there was a time for autonomous driving to take over, it would've been then. Instead, what happened was driving trucks wound up being so in demand that in certain countries, they had to call up their National Guard to actually drive trucks because it became a matter of national security and national infrastructure.

And I think as you listen to the subtext of what Lance and I are saying here the subtext is, this isn't about the computer alone, it's about the person being much more empowered, much more productive by the computer, but the person in a very similar scenario to autonomous driving, still being part of that process, still being the critical control, still looking at what the computer is doing. I think where people get confused is they look at a world with no people, we look at a world with people who are enabled to be better by the power of the technology.

Oscar Pulido: You've both touched on the fact that you're both tech optimists and I think, it's always good to end and pragmatists. but always good to end on an optimistic note. I think as we talk about any topic. So, I'd love to just get your thoughts on, the next year or two, what lies ahead, like what haven't you discussed that gives you even more optimism about ai, in a business setting?

Rob Goldstein: I have a vision that I believe will come true. Which is right now there's this concept of the prompt engineer, no one knew what that was a year ago, now it's going to be the job of the future. I have a different perspective on it, I'm very fortunate, I have two children. One of them is graduating this year of college, and one of them is a sophomore in college. And I think for my daughter Sadie, who's a sophomore in college by the time she graduates, I believe two things. One, the concept of a prompt engineer won't really exist. And two, whatever it was supposed to do, she will naturally know how to do from being in college for the next two years. This goes back to your question about training, sometimes you're training yourself and you don't even know it. I think a lot of what we're talking about here is just going to be natural. It's going to be in the water, and we won't even know it.

Lance Braunstein: And I would just extend that Getting everybody into generative ai, teaching them the concepts, teaching them the prompting. Is going to enhance our ability to just run a better investment process to be a better technology company. The thing that excites me in this next year, and I am really thinking about from now, is getting people more into ai. Getting people like hands-on into co-pilots and chat assistance and enabling them to get to that first draft that we described earlier, faster with higher quality. That's thing one. I think thing two is there will be a number of jobs that we want to automate, that we want to create greater automation.

And again, not in the, not to, to the exclusion of the human supervisor, but getting those rote tasks to a greater place of automation, I think is immediate and exciting for me. So more of us becoming sort of gen AI enabled and empowered. And more of us doing the highest value work rather than the rote tasks that is near and present and super exciting for me.

Oscar Pulido: And it sounds like more people becoming students of technology,

it sounds like the evolution in AI is going to push everybody in that direction. And guys, I want to thank you for, joining us, on the podcast as almost the professors of technology that we will look to, I'm sure down the road. Again, Rob, Lance, thanks for joining us.

Rob Goldstein: Great. Thank you.

Lance Braunstein: Thanks.

Oscar Pulido: Thanks for listening to this episode of The Bid. If you've enjoyed this episode, check out our two-parter on AI featuring Brad Betts and Jeff Shen, where we look at the history of investing in ai, and potential future applications in finance. Subscribe to The Bid wherever you get your podcasts. Subscribe to The Bid wherever you get your podcasts.

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This content is for informational purposes only and is not an offer or a solicitation. Reliance upon information in this material is at the sole discretion of the listener.

For full disclosures go to Blackrock.com/corporate/compliance/bid-disclosures

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AI from a COO perspective

Join host Oscar Pulido as he explores the transformative power of Generative AI and its impact on the financial services industry. Rob Goldstein, Chief Operating Officer of BlackRock, and Lance Braunstein, Head of Aladdin Engineering, share their optimistic perspectives on Gen AI and the evolution of technology over the past year.

The release of ChatGPT has driven an explosion of excitement and attention around the topic of AI. See how we’re using these technologies to enhance our ability to analyze datasets and forecast investment outcomes within BlackRock Systematic.

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