The AI Capabilities Overhang

Today on the AI Daily Brief, the AI capabilities overhang and what to do about it.

Before that in the headlines, why cloud code is officially breaking into the mainstream.

The AI Daily Brief is a daily podcast and video about the most important news and discussions

in AI.

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Welcome back to the AI Daily Brief headline edition, all the daily AI news you need in

around 5 minutes.

The story of this January so far has been the slow but steady settling in of the notion

of a shift in capabilities, centered upon Opus 5, Claude code, and now more recently

Claude co-work.

Turns out the change is not just among the highly enfranchised AI users on X, the Wall Street

journal declared over the weekend that Claude is taking the AI world by storm, and even

non-nerds are blown away.

The WSJ writes, they call it getting Claude-pilled.

It's the moment software engineers, executives, and investors turn their work over to Anthropics

Cloud AI, and then witness a thinking machine of shocking capability, even in an age of

wash and powerful AI tools.

The article noted the huge wave of positivity on social media, with many non-technical people

using Claude code to develop their first piece of software without knowing the first

thing about coding.

It also noted that Claude code is being deployed for a range of other use cases, including

health data analysis and expense report compiling.

The Atlantic had a similar take, writing, move over chat GPT.

The article says, though Claude code is technically an AI coding tool, hence its name,

the bot can do all sorts of computer work, book theater tickets, process shopping returns,

order door dash.

People are using it to manage their personal finances and to grow plants.

I don't know what it says about the Atlantic, that the first example they reached to is book

theater tickets, but there you go.

The author remarked that they used vibe coding tools for the first time in preparation for

the article, and was astonished that they could create a new personal website in minutes

without any coding.

They went on to spin up a dozen additional projects over the next few days.

They texted a friend to try it out and received the response.

It just does stuff.

Chat GPT is like if a mechanic just gave you advice about your car.

Claude code is like if the mechanic actually fixed it.

To be honest, I don't really think that that does it justice.

I think it's more like Claude code is like if when you dropped off your car at the mechanic

you could request any other car, and all of a sudden a few minutes later it would just

be there waiting for you.

A user named Alex Lieberman was profiled for the piece, and claimed that in terms of

implication this was even bigger than the Chat GPT moment.

However, he added Pandora's box hasn't been open for the rest of the world yet.

That might not be the case for long, however, with major publications now raving about

Anthropics product lineup.

Claude code creator Boris Cherny remarked on the overnight success that was years in

the making, saying, glad to see Claude code starting to break through.

It's been a year of very hard work, and we're just getting started.

Ajanie Mido writes,

The front page of the Wall Street Journal today is about every day people using a command

line interface.

If you are a business leader and not revisiting major operating assumptions about the world,

you are doing yourself in the people who depend on you a massive disservice.

One other Anthropic story the latest on their reported fundraising.

That round that we've been hearing about that values Anthropic at 350 billion is apparently

getting supersized up to potentially 25 billion.

That includes about 15 from Microsoft and Nvidia and another 10 from VCs and other investors.

Among those VCs is apparently Sequoia.

Feels like we're probably within a few weeks of this closing, so I'm sure we'll get more

news soon.

Now despite the Wall Street Journal writing so glowingly about Claude, US users clearly

remain concerned about the technology overall.

According to a new survey commissioned by Google and conducted by Ipsos, AI users are now

in the majority.

66% of respondents said they had used AI in the past 12 months compared to 48% in the

2024 poll and 28% in 2023.

This was the third year of the longitudinal survey which was conducted in late September

last year, so relatively up to date.

The survey pulled around 1000 adults from each of 21 countries.

The respondents were evenly split when it comes to AI job disruption, with 50% saying

AI in the workplace will create jobs and 50% saying it will eliminate jobs.

Still the majority of survey participants were in favor of fostering advancements using

AI at 58%, compared to 41% who wanted to protect industries that might be disrupted

by AI.

Not surprisingly, AI optimism was closely tied to AI use, 70% who said they've used

AI are optimistic about its benefits, and of those who use AI a lot, 86% were excited.

There's also a strong correlation between countries with high levels of AI use and high

levels of optimism.

The US however ranked low on both use and optimism.

Just 40% of US survey participants said they have used AI in the past year, which was

the only country without a majority of AI users.

As a point of comparison, the UK was at 56%, Mexico was at 66%, while the UAE, Nigeria

and India were all north of 80%.

Only 33% of US respondents said they were mostly excited about the technology, the worst

national result in the survey, and vastly beneath the overall result of 57%.

Now I actually think this is a major national issue.

The implications are not just the user numbers for open AI and anthropic, it's about the

seriousness with which people are taking the potential disruption for this technology

and preparing themselves for it.

I believe there continues to be a strand of people who are hoping to just wait it out

and return to the world that once was, and obviously I do not think that that's going

to happen.

Moving over to an issue that has become part of the political cannon fodder around AI,

which is of course data centers, XAI's Colossus 2 has now reached one gigawatt of capacity,

becoming the first training cluster to cross that threshold.

The data center is now drawing more power than the city of San Francisco, for comparison

the first Colossus cluster has a total capacity of 300 megawatts, while OpenAI recently disclosed

that they have 1.9 gigawatts across their entire training and inference fleet.

Construction began in March of last year, so this milestone was 9 months in the making.

The only other cluster that's closest anthropic in Amazon's new Carlisle data center, which

is expected to hit one gigawatt sometime in the first quarter of this year.

OpenAI's Stargate Abilene is expected to come online over the summer.

For now, XAI is the only company with access to this much compute, which is exactly what

we discussed as the big potential opportunity that could translate into differentiation

for GROC in the year to come.

Colossus 2 is also using Blackwell GPUs, making it one of the first training clusters to

run Nvidia's latest hardware and the only one at the scale.

The cluster reportedly contains 550,000 GPUs as currently configured.

As Amateo Kaplan put it, Gigawatt GROC has arrived.

Now staying in Musk world for a moment, Elon Musk is seeking up to 134 billion in damages

from OpenAI in Microsoft as his lawsuit heads to a trial.

A trial date has been set for late April, and during a hearing on Friday, Musk's lawyers

quantify the damages.

Their argument is that Elon is entitled to a portion of OpenAI's current $500 billion

valuation due to the $38 million in seed funding he donated to the nonprofit in 2015.

Musk's lawyer wrote in court filings, just as an early investor in a startup company

may realize gains many orders of magnitude greater than the investor's initial investment,

the wrongful gains that OpenAI and Microsoft have earned, and which Mr. Musk is now entitled

to discourage, are much larger than Mr. Musk's initial contributions, which is a very legal

ease way of saying, if that $38 million had been an investment into a for-profit startup,

it would have been a heck of a lot more than $38 million by now.

The filing also says that Musk plans to seek punitive damages as well as an unspecified

injunction.

OpenAI's lawyers rejected the approach, stating that his quote methodology is made up,

his results unverifiable, his approach admittedly unprecedented, and his proposed outcome, the

transfer of billions of dollars from a nonprofit corporation to a donor-turned-competitor,

implausible on its face.

OpenAI for their part continue to deny the premise of the lawsuit outside of the courtroom.

In a statement they said, Mr. Musk's lawsuit continues to be baseless and a part of his

ongoing pattern of harassment, and we look forward to demonstrating this at trial.

This latest, unserious demand is aimed solely at furthering this harassment campaign.

Now on X, the discussion centered around pages from Greg Brockman's private notes that

were revealed in the new filing.

One especially frequently shared passage from 2017 red, this is the only chance we have

to get out from Elon.

You see, the glorious leader that I would pick, we truly have a chance to make this happen.

Financially, what will take me to $1 billion?

D.V. Doss at Menlo Venture said, deep down it really is about the money.

Now several other quotes from the filing paint open AI in a very poor light.

The quotes, Altman said, Elon is cherry-picking things to make Greg look better.

Not bad, but the full story is that Elon was pushing for a new structure, and Greg and

Ilya spent a lot of time trying to figure out if they could meet his demands.

Altman continued, I remembered a lot of this, but here is a part I had forgotten.

Elon said he wanted to accumulate $80 billion for a self-sustaining city on Mars, and that

he needed and deserved majority equity.

He said that he needed full control since he'd been burned by not having it in the past,

and when we discuss succession, he surprised us by talking about his children controlling

AGI.

Altman continues after that quote, I appreciate people saying what they want, and

they can enable people to resolve things or not, but Elon saying he wants the above

is important context for Greg trying to figure out what he wants.

With the trial less than three months away, the story is unfortunately going to be a big

overhang for OpenAI as they try to execute on a pivotal year.

Right signal?

This is going to make a lot of people look greedy and ugly.

Hopefully we won't have to spend too much time on this.

I'll probably start to err on only sharing the really big highlights where it becomes a

major, inescapable point of conversation as it has been for the last couple of days.

This show, however, will not become a play-by-play court drama, as interesting and salacious as it

might be.

For now, that is going to do it for today's headlines.

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Welcome back to the Aidelebrief.

Today we are talking about something called the AI capabilities overhang.

Now, this is something I think about a lot, but the specific context for it was an article

that came out as part of the broader set of assets around OpenAI's announcement that

ads are coming to chat GPT, with them basically saying that part of the issue is access and

ads are going to help them with that access issue.

Now in that blog post called AI for self-empowerment, OpenAI defines the capability overhang as the

gap between what AI systems can do now and the value most people businesses and countries

are actually capturing from them at scale.

In other words, the delta between AI's current capabilities and society's current usage

of them.

And what's important about this concept is this is not about some future state.

This is not in other words a debate about AGI or super intelligence or anything like that.

It is instead a discussion of the current state of play and how far behind different types

of people and groups are in taking advantage of it.

So what I want to do today is talk about the AI capabilities overhang across six different

groups, individuals, communities, municipalities, educators, businesses and sovereigns.

For each of those groups I want to talk a little bit about what the capabilities overhang

looks like at the moment, what some of the answers to that overhang might be, and how

we, and this is the royal we I could mean society, I could mean the listeners of this podcast,

but how we could support tackling that capabilities overhang and improving the way that people

are taking advantage of what's possible right now.

So let's talk first about individuals.

Now this is admittedly a wildly all-encompassing category with a huge range of different

levels of this particular overhang.

While there are very, very few people who could claim that they don't experience that overhang

at all, in fact, even as someone who spends basically all of my time on this, I think

that there are entire categories of what's possible that I don't take nearly full enough

advantage of.

Most people fall somewhere on the spectrum from barely taking advantage to only just starting

to take advantage.

In fact, I think part of the reason that you're seeing so much excitement around Claude

Code and see it moving into the mainstream in the Wall Street Journal and things like that

is that for people who are picking it up, it is radically and directly undercutting that

capabilities overhang by massively accelerating what people can do.

But the implications of the capabilities overhang is dramatic.

Skills that took years to develop can now be augmented or replicated in hours.

Now this sort of commoditization of knowledge work creates displacement risk, of course,

but it also creates incredible opportunity in terms of the massive leverage that it can

give people.

One of the implications of the capabilities overhang, however, when it comes to that individual

focus, is that personal economic modes are eroding faster than people realize.

In other words, the gap between I should learn this AI stuff and I needed it yesterday

is closing.

To what are some of the challenges?

Information is one, and by that I don't just mean information about what's possible

with AI, although that's part of it, but also I think we have a real issue in the way

that we discuss AI.

Every survey that comes out shows that to be a little bit reductionist, but honestly not

all that much, Eastern and lower income countries are extremely enthusiastic about AI, while

people in Western and higher income countries are less so.

There are all sorts of reasons for this, but what it means is that in addition to just

a general information gap, you also have a massive enthusiasm gap, which means that people

who don't like AI or wish it didn't exist are getting farther and farther behind, kind

of hoping that it just goes away.

Go on any social media platform and you will be able to find myriad posts about people

enthusiastically quote-unquote waiting for the end of the bubble so things can go back

to normal.

Like the incontrovertible fact, known by everyone who is listening to this particular

show, that there is no such thing as going back.

So improving information availability about what you can do with AI, but also about to

some extent the inescapability of some changes because of it is a key part of overcoming

this overhang.

Another part is of course access.

People who can pay more right now have better access to AI.

However, the gap isn't necessarily as big as it seems, although chat GBT data shows

that the typical power user of their system uses seven times more compute than a typical

user, there's still incredible capacity available to anyone, even in the free versions of these

tools.

One of the things that's been super interesting to me watching people interact with the

New Year's AI resolution, which is the 10 week self-education program that came out

of my New Year's episode, is that a lot of folks, despite being on the very high end

of enfranchised users, are seeing how much they can get out of the free versions of

these tools.

I actually think that that's incredibly valuable and more instructive in many ways to the

average user than some insane person like me who's going to pay for the ultra or max

subscription every single tool that comes along.

I will say that I think even with this, a quality of access is going to continue to be

an issue and probably one that gets worse.

As much as we might not like the experience of ads in something like chat GBT, I do believe

that it does extend access and keeps access democratized in a way that a non-ad supported

model just couldn't.

However, ads from the platforms are certainly not the only way to ensure access.

There might be a role for government here, and frankly, it's one of the reasons that

some of the ideas around things like stopping data center construction are so wrong-headed

because they are likely to have the exact opposite impact where they actually further

restrict access to only the people who can pay for it.

So how can we support individuals overcoming the capability overhang?

One is a different conversation about AI and an acknowledgement that it's coming.

Two is continuing to look for ways to democratize access, whether that's from the platforms

themselves through ads or other models, or through public-private partnerships or some

other larger type of initiative, anything the last piece, and something that certainly

we will be trying to do a lot of this year with this show is self-education opportunities.

So many people are engaging so deeply with this New Year's AI resolution that I am 100%

sure that we will release other similar time-bound, but ultimately self-directed types of programs.

Next up, let's talk about communities.

Communities hold many of the assets that AI can't replicate.

Trust networks, local context, physical gatherings, shared identity, accountability structures,

and the overhang actually increases the value of these assets.

As digital interactions become AI-mediated, and in many cases for people harder to trust,

in-person community becomes a premium good.

In fact, as we think about the individual overhang, local institutions are sitting on distribution

and trust infrastructure that could be leveraged to help members navigate the AI transition,

but of course most aren't thinking this way yet.

Indeed, the challenge for communities is that community institutions tend to be the most

strapped for hard resources, and so the people who are involved in leading communities

have to trade time for everything.

Basically, when there isn't money, you require people to volunteer time and service.

That means less time for keeping up with all of these opportunities.

But if we can position community institutions as the human layer in an increasingly AI-mediated

world, there is a ton of potential power in these institutions taking on renewed importance

in this new age we're moving into.

To support that, I think we have to start by supporting their leaders.

We need dedicated resources and leadership support and training for these particular

types of institutions that are not necessarily just about the same things that are going

on with individuals, but are really about how to become a node for disseminating and supporting

transition among constituencies.

Closely related to communities is the capabilities overhang for municipalities.

Municipalities are, of course, the public and governmental complement too many of those

community institutions.

Like communities they're strapped for resources, they have old patterns of doing things that

can be very, very difficult to change.

Are these groups potentially some of the biggest beneficiaries of the efficiency gains that

come with AI?

One study found that 30 to 50% of municipal staff time is spent on tasks that are already

automatable or dramatically acceleratable right now.

And it takes about five seconds to think about some of the examples, changing review time

for permitting in land use, moving from hold times, phone trees, and manual routing within

constituent services to instant intake automated routing and proactive follow up.

There are potential implications for public works for social services, for records, for

courts, for revenue and finance, for public health.

You name it.

AI efficiencies are so full of opportunity among municipalities.

And for that reason, I think we should be spending way more time, energy, and resources

on trying to fix this particular category of capabilities overhang.

What does that look like?

Well, of course, I don't know, but I think that some opportunities include different types

of public-private partnerships.

I've got to say, right now, the model labs in many AI startups in general don't necessarily

have the best brand and reputation.

The AI industry as a whole is suffering from a broader sense among many people, especially

in the West, that techno longer exists to serve people to the extent it ever did, but

instead serves only to enrich the people who create that technology.

Seems like a pretty good time to try to engage in some public-private partnerships that

actually bring the benefits of AI to a wider audience.

Frankly, there's also strikes me as an opportunity for perhaps a different class of business

that has different incentives.

I think there are very clear, profit-motivated business opportunities in AIifying how municipalities

work.

But I think that trying to find a new generation of entrepreneurs, maybe some of whom

have backgrounds in that type of municipal service, who are designing leaner, more

capital-efficient providers, who are going to be able to offer municipalities, contracts

and services that provide that transitional support without gouging them.

It just strikes me that this could be a great moment for a new class of civic-minded

entrepreneur to really do some damage in the best possible way.

When it comes to educators and education, goodness gracious, where to even begin.

This is something we've talked about a lot in the show, although not for a little while

believe it or not, but by and large, education is stuck being concerned that students can

now cheat on the test when the real problem is that in the future that we're moving into,

the test doesn't matter.

We need nothing short of a radical re-evaluation of everything that we teach.

To be wildly oversimplified and reductive in a way that the educators among you are going

to be cringing your faces off, I apologize in advance, let's start by separating everything

into three buckets.

The skills that are definitely still relevant, which by the way there are many, critical

thinking, ethical judgment, creative problem solving, human interaction and empathy, relevant,

relevant, relevant, relevant, in fact, more so.

So interestingly enough, a set of skills which we've often pejoratively called soft skills

that we haven't had nearly enough emphasis on in our education system for a very long

time.

So we've got that one bucket of definitely still relevant.

Then we have the things that are definitely changing in relevance, subjects that are

absolutely and undeniably being transformed by AI tools, writing in composition, research

and information synthesis, programming.

We don't have to fully throw out the baby with the bathwater to recognize that we're

talking about a lot more than going from adding with an advocate to adding with a calculator

when it comes to how dramatically this set of skills is changing in terms of how humans

are going to interact with them.

And then of course there's perhaps the biggest category, which we will generously call

who the hell knows.

There is going to be so much in this category where we simply do not know how AI is going

to impact it and having the humility to understand that some stuff that we're going to teach

could be irrelevant, but we just don't know and we have to hedge a little bit is I think

a reasonable way to proceed.

And of course there is a fourth bucket, new things that have become relevant.

Some of that's just AI specific skills, but a lot of that's going to be in and around

management and organization and basically the things that help people take advantage

of the fact that each of them will in the future have access to talent that every corporation

in the world would kill for today.

And then from there we redesign the curriculum around a balance of these things.

We run big experiments, we get okay with failure.

This area of disruption and change is going to be some of the easiest to talk about and

the hardest to actually do in practice and the best way I think we can support is to

create space for real change, not incrementalism, but true actual disruption.

The second last category we'll talk about today is the capabilities overhang for businesses.

And once again, just as the individuals are incredibly diverse, so too is the capability

overhang for companies.

As we saw with our AI ROI survey, there is a spectrum of capabilities overhang for companies

at every different level.

And while it may be the case that certain sizes of companies have different types of advantages

over one another, I don't believe that on mass, there is one category or type or size of

business that is experiencing dramatically less overhang than some other companies are

pretty much all dealing with going from no AI to figuring out how to use AI for efficiency

or they are dealing with the challenge of moving from efficiency to actually leveraging

AI for new opportunity.

In years of doing this and seeing thousands and thousands of executive interviews, I will

say confidently that I have never seen a single company of any size, including my own startup

and incentivized enough to get this right that doesn't experience the AI capabilities

overhang in some way.

We just had a super intelligent off site where all of us sat down and basically tried

to tear through everything we do and ask how we could AIify it even more.

And the amount that we are not doing is immense.

The big problems of the capabilities overhang with businesses involve really common patterns.

The thing we hear about most at super intelligent is creating time to redesign.

We have these whole new set of skills that people are expected to learn, but they are expected

to learn them while also doing their normal jobs.

Classic and quintessential conundrum of the moment is that we don't have time to learn

the thing that could save us so much time.

There's also the challenge of our normal disposition to wait for the future rather than

to go invent it, which of course gets into the idea of new opportunities.

We don't know what it's going to look like when every single member of every single company

can use software to deliver on their KPIs and invent new ones, but we're going to start

to find out.

Certainly, something that we could help with is that especially the farther away from

the AI efficiency era we get, the worse and worse the resources to support people's education

we find.

There are still plenty of prompt engineering courses out there, but actual really strong

resources on how to use coding tools for non-coders, how to build and manage agents,

how to think about automations more systematically.

These are much fewer and farther between.

Now hopefully the market incentive for this changes that in short order because goodness

gracious is there a lot of market opportunity there, but anything we can do to provide more

resources for education or self-education, the better.

The last group we'll talk about are the sovereigns.

And honestly, this is the group that might be the most aware of their capabilities over

hang of anyone.

The overhang in this case is a national security issue.

The delta between what's possible and what's deployed represents strategic vulnerability.

It also represents a challenge in terms of who gets to define the future.

Not only is there this strategic vulnerability, but sovereigns are also dealing with the

fact of what it means to have everyone's understanding of the world mediated by LLMs that

are reliant on a specific set of sources, which may not take into account the full complexity

and cultural legacy of your particular nation.

So there is so much in the AI capabilities overhang for sovereigns.

Certainly in the medium term, first mover advantages in AI capability could create some

seriously durable geopolitical asymmetries.

Now like I said, this is the group that I think is most cognizant of this challenge.

And it's why you see so many nations treating AI infrastructure in the form of compute, talent

and data as critical national assets.

It's why you're seeing massive geopolitical realignment around this stuff.

And it's going to be fascinating to see how this continues to interact with the geopolitical

conversation in the years to come.

Anyways, friends, that is our quick tour of the AI capabilities overhang.

The gap between what AI can do right now and how society in all of its various manifestations

is actually taking advantage of it.

I think we all in many ways have incentives to try to close the capabilities overhang

among every type of group not only that we're participating in, but those around us.

Hopefully identifying it as a challenge is a good starting point.

And that's what I've tried to do here and will continue to do on this show.

For now that that's going to do it for today's AI Daily Brief, appreciate you listening

to your watching as always and until next time, peace!