Quotesby GlyphSequoia Capital leaders on AI, quotes with sources
22 quotes from Julien Bek, Pat Grady, Sonya Huang, David Cahn
- AI has crossed the threshold where it can do most of the intelligence work autonomously and leave the judgement to humans.
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- But if you sell the work, every improvement in the model makes your service faster, cheaper, and harder to compete with.
- The next $1T company will be a software company masquerading as a services firm.
- The work budget in any profession dwarfs the tool budget, and autopilots capture the work budget from day one. The higher the intelligence ratio in any field, the sooner autopilots will win.
- Every quote from Julien Bek
- AGI is the ability to figure things out. That’s it.
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- An AI that can figure things out has some baseline knowledge (pre-training), the ability to reason over that knowledge (inference-time compute), and the ability to iterate its way to the answer (long-horizon agents).
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- If there’s one exponential curve to bet on, it’s the performance of long-horizon agents. METR has been meticulously tracking AI’s ability to complete long-horizon tasks. The rate of progress is exponential, doubling every ~7 months.
- Today, your agents can probably work reliably for ~30 minutes. But they’ll be able to perform a day’s worth of work very soon – and a century’s worth of work eventually.
- Every quote from Sonya Huang
- Dwarkesh Patel’s recent podcast interviews with Richard Sutton, Andrej Karpathy, and Ilya Sutskever are a demarcating line; the new consensus is that the AGI window will be in the 2030s, at earliest.
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- In 2026, we’re going to see the emergence of a $0 to $1B club.
- My prediction, especially coming off of the successful Gemini 3 launch and hype around TPUs, is that the TSMC constraint could become material in 2026.
- On the one hand, it will be a year of delays, first in data center buildouts, many of which will fall behind schedule, and second, in the AGI timeline. At the same time, AI adoption will continue its relentless rise.
- Every quote from David Cahn
- AI’s $200B question is now AI’s $600B question.
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- But we need to make sure not to believe in the delusion that has now spread from Silicon Valley to the rest of the country, and indeed the world. That delusion says that we’re all going to get rich quick, because AGI is coming tomorrow, and we all need to stockpile the only valuable resource, which is GPUs.
- GPU computing is increasingly turning into a commodity, metered per hour. Unlike the CPU cloud, which became an oligopoly, new entrants building dedicated AI clouds continue to flood the market. Without a monopoly or oligopoly, high fixed cost + low marginal cost businesses almost always see prices competed down to marginal cost (e.g., airlines).
- Every quote from David Cahn
- Nonetheless, these early signs of success don’t change the reality that a lot of AI companies simply do not have product-market fit or a sustainable competitive advantage, and that the overall ebullience of the AI ecosystem is unsustainable.
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- Rather, workflows and user networks seem to be creating more durable sources of competitive advantage.
- We did not anticipate the extent to which end user demand would outstrip GPU supply. The bottleneck to many companies’ growth quickly became not customer demand but access to the latest GPUs from Nvidia.
- Every quote from Pat Grady
- In generative AI, we have reached a modern marvel, our generation’s space race.
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- Last year, we anticipated it would be nearly a decade before we had intern-level code generation, Hollywood-quality videos or human quality speech that didn’t sound mechanical. But a quick listen to Eleven Labs’ voices on TikTok or Runway’s AI film festival makes it clear that the future has arrived at warp speed.
- Every quote from Sonya Huang
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