AI Hype Meets Harsh Reality of Supply
It is a good time to be in the business of making AI chips
and servers. But even red-hot demand can’t make supply magically appear.
Advanced Micro Devices saw first-quarter revenue surge 80% year over year in
its data-centre segment that sells chips used to power artificial-intelligence
services. The company’s projection for the second quarter implied 95%
year-over-year growth for that key segment. But Wall Street was expecting
robust numbers, having propelled AMD’s stock price up 77% over the past 12
months ahead of the report. Hence, even the company boosting its full-year
projection for AI-chip sales by 14% fell short of some more lofty expectations.
AMD’s shares dropped roughly 9% on Wednesday. Sky-high expectations really hurt
Super Micro Computer, known as Super micro. The company makes specialized AI
servers using chips from AMD and more widely from Nvidia, and its growth has been
on a tear, with first-quarter revenue of $3.85 billion triple from a year ago.
But that fell about 3% below Wall Street’s target for the company’s third quarter
that ended in March. Super micro’s stock, which more than tripled in value
since the start of this year, fell 14% on Wednesday. Both companies noted in
their earnings calls on Tuesday that supply constraints are weighing on sales.
“So there’s no question at all that if we had more supply, we have demand for
that product,” AMD Chief Executive Lisa Su said of its MI300 chips. Super micro
CEO Charles Liang noted supply shortages for its latest liquid-cooling systems,
which are much in demand. Those shortages are expected to be temporary. Super
micro nudged up its aggressive revenue target for the fiscal year ending in
June to a midpoint of $14.9 billion, more than double what it made last year.
But Super micro has a capital-intensive business model and said Tuesday that it
may need to raise more capital if demand keeps picking up. The AI gold rush isn’t
cheap, even for those supplying the picks and shovels.
Sam Altman says helpful agents are
poised to become AI’s killer function
Open AI’s CEO says we won’t need new hardware or lots more
training data to get there.
- James
O'Donnellarchive page
A number of moments from my brief sit-down with Sam Altman
brought the OpenAI CEO’s worldview into clearer focus. The first was when he
pointed to my iPhone SE (the one with the home button that’s mostly
hated) and said, “That’s the best iPhone.” More revealing, though, was the
vision he sketched for how AI tools will become even more enmeshed in our daily
lives than the smartphone.
“What you really want,” he told MIT Technology
Review, “is just this thing that is off helping you.” Altman, who was
visiting Cambridge for a series of events hosted by Harvard and the venture
capital firm Xfund, described the killer app for AI as a “super-competent
colleague that knows absolutely everything about my whole life, every email,
every conversation I’ve ever had, but doesn’t feel like an extension.” It could
tackle some tasks instantly, he said, and for more complex ones it could go off
and make an attempt, but come back with questions for you if it needs to.
It’s a leap from OpenAI’s current offerings. Its leading
applications, like DALL-E, Sora, and ChatGPT (which Altman referred to as
“incredibly dumb” compared with what’s coming next), have wowed us with their
ability to generate convincing text and surreal videos and images. But they
mostly remain tools we use for isolated tasks, and they have limited capacity
to learn about us from our conversations with them.
In the new paradigm, as Altman sees it, the AI will be
capable of helping us outside the chat interface and taking real-world tasks
off our plates.
Altman on AI hardware’s future
I asked Altman if we’ll need a new piece of hardware to get
to this future. Though smartphones are extraordinarily capable, and their
designers are already incorporating more AI-driven features, some entrepreneurs
are betting that the AI of the future will require a device that’s more purpose
built. Some of these devices are already beginning to appear in his orbit.
There is the (widely panned) wearable AI Pin from
Humane, for example (Altman is an investor in the company but has
not exactly been a booster of the device). He is also rumored to
be working with former Apple designer Jony Ive on some new type of
hardware.
But Altman says there’s a chance we won’t necessarily need a
device at all. “I don’t think it will require a new piece of hardware,” he told
me, adding that the type of app envisioned could exist in the cloud. But he
quickly added that even if this AI paradigm shift won’t require consumers buy a
new hardware, “I think you’ll be happy to have [a new device].”
Though Altman says he thinks AI hardware devices are
exciting, he also implied he might not be best suited to take on the challenge
himself: “I’m very interested in consumer hardware for new technology. I’m an
amateur who loves it, but this is so far from my expertise.”
On the hunt for training data
Upon hearing his vision for powerful AI-driven agents, I
wondered how it would square with the industry’s current scarcity of training
data. To build GPT-4 and other models, OpenAI has scoured internet archives,
newspapers, and blogs for training data, since scaling laws have long shown
that making models bigger also makes them better. But finding more data to
train on is a growing problem. Much of the internet has already been slurped
up, and access to private or copyrighted data is now mired in legal
battles.
Altman is optimistic this won’t be a problem for much
longer, though he didn’t articulate the specifics.
“I believe, but I’m not certain, that we’re going to figure
out a way out of this thing of you always just need more and more training
data,” he says. “Humans are existence proof that there is some other way to
[train intelligence]. And I hope we find it.”
On who will be poised to create AGI
OpenAI’s central vision has long revolved around the pursuit of
artificial general intelligence (AGI), or an AI that can reason as
well as or better than humans. Its stated mission is to ensure such a
technology “benefits all of humanity.” It is far from the only company pursuing
AGI, however. So in the race for AGI, what are the most important tools? I
asked Altman if he thought the entity that marshals the largest amount of chips
and computing power will ultimately be the winner.
Altman suspects there will be “several different versions
[of AGI] that are better and worse at different things,” he says. “You’ll have
to be over some compute threshold, I would guess. But even then I wouldn’t say
I’m certain.”
On when we’ll see GPT-5
You thought he’d answer that? When another reporter in the
room asked Altman if he knew when the next version of GPT is slated to be
released, he gave a calm response. “Yes,” he replied, smiling, and said nothing
more.
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