The AI Moment Arrives with ChatGPT
On November 30th, OpenAI introduced chatGPT—a wildly performant language model—to the world. The large language can be asked to do most anything, and does a lot of it quite well. It can serve as a tutor, an editor, a writer, a coder, and a therapist. Though it has limitations—the model will confidently “lie” and has no embedded formal logic—it’s clear the release struck a chord: more than a million users have signed on in its first week, and OpenAI’s compute infrastructure has shown signs of strain.
ChatGPT demarks an AI inflection point. We believe that AI software will grow to a $14 trillion market by 2030 on the basis of its ability to force-amplify knowledge workers, but chatGPT is so clearly capable of delivering productivity enhancements across so many knowledge work categories that our forecast is likely to prove too conservative. Given that OpenAI has an even more powerful language model—GPT4–rumored for an early 2023 release—suggests that we are merely at the end of the beginning for groundbreaking AI: we believe these models will pervade our lives in profoundly interesting ways, and they are likely to do so quickly.
Generative AI Tops the App Store
Meanwhile, AI image generation tools have broken through into the mainstream, topping the App Store charts. When Lensa AI let users create AI generated avatars trained on their own selfies it increased revenue 100-fold to top $1 billion annualized. It is not alone: 3 of the top 4, 4 of the top 8, and 5 of the top 10 downloaded free apps on iOS feature AI image generation features.
It’s not clear that any of these particular companies will be able to transform this flash of popularity into a durable competitive advantage, but it is interesting that start-ups were able to hit the generative AI commercialization window ahead of more well-resourced incumbent social media companies. The computational cost to generate AI images may make it economically infeasible for ad-supported business models. As Lensa AI has demonstrated, however, customers will happily pay for custom model trained on their own personal data. It will be interesting to see how business models evolve as AI costs continue to decline.
A Fusion First
For the first time in history scientists seem to have created a nuclear fusion process that emits more energy than is required to keep it running. Scientists have been working to demonstrate proof-of-concept in nuclear fusion power—the same reaction-type the powers the sun—since the 1950s; this result, from Lawrence Livermore National Lab, seems to finally deliver the technical goods and so brings the promise of an abundant clean-energy future closer to reality.
Net power generation, while important, is not enough. For a technical milestone to prove tractable the technology pathway needs to accommodate scaling and manufacturability. Venture dollars have been chasing the opportunity with $2.8 billion invested over just the last 12 months. We would expect to see additional announcements over the next couple of years that further clarify potential commercialization timelines.
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