We’re starting to see the very early stages of a tech stack emerge in generative artificial intelligence. Hundreds of new startups are rushing into the market to develop foundation models, build AI-native apps, and stand up infrastructure & tooling.
The generative AI boom has been accompanied by real gains in real markets, and real traction from real companies. Models like Stable Diffusion and ChatGPT are setting historical records for user growth, and several applications have reached $100 million of annualized revenue less than a year after launch.
There is enough early data to suggest massive transformation is taking place. What we don’t know, and what has now become the critical question, is: Where in this market will value accrue?
Infrastructure vendors are likely the biggest winners in this market so far, capturing the majority of dollars flowing through the stack. Application companies are growing topline revenues very quickly but often struggle with retention, product differentiation, and gross margins. And most model providers, though responsible for the very existence of this market, haven’t yet achieved large commercial scale.
Matt Bornstein, Guido Appenzeller, and Martin Casado are incredibly bullish on generative AI and believe it will have a massive impact in the software industry and beyond. They map out the dynamics of the market and start to answer the broader questions about generative AI business models. [link]
LLMs competition
..we’re starting to see LLMs built by companies like Anthropic, Cohere, and Character.ai come closer to OpenAI levels of performance, trained on similar datasets (i.e. the internet) and with similar model architectures. The example of Stable Diffusion suggests that if open source models reach a sufficient level of performance and community support, then proprietary alternatives may find it hard to compete. [link]
As a result, a lot of the money in the generative AI market ultimately flows through to infrastructure companies. [link]
“AI Companions: Social Impact — How tech like ChatGPT, virtual companions, and robots will change us” // dystopian vision
Meanwhile: Microsoft’s Products Will Soon Access Open AI Tools
Generative AI hacking
Game of Life, where each alive cell is a whimsical happy Stable Diffusion image and each dead cell is an eerie, dark Stable Diffusion image, all of which evolve over time. Built on a generative AI version of Canva they made.
a key-value store to enable long-term memory in language model conversations
a personalized learning curriculum generator on top of Spellbook
a backend and database that is entirely LLM-powered. “Who needs Postgres?” 1KB of storage!
Automatic permit application generation for climate tech companies & carbon dioxide removal
Next gen voice assistant with Whisper for transcription and LLMs doing document retrieval + question answering.
HouseGPT generates raw MIDI data directly from few-shot prompted GPT-3 to create house music
Pick any two people and it will generate a rap battle on the fly, using GPT-3 for lyrics, wavenet for vocals, and stable diffusion for the avatars. Sound on!
GPT-3 Auditor: scanning code for vulnerabilities with LLMs. https://github.com/handrew/gpt3-auditor
Last prompt // JFF
Q: You are the expert in all fields , and have read all of the publicly available texts in the world. Please tell me why the answer is 42?
A: The answer to this question is a popular reference to the book “The Hitchhiker’s Guide to the Galaxy” by Douglas Adams, in which the answer to the ultimate question of life, the universe, and everything is revealed to be 42.
// in progress…
