@levie: There’s still so much opportunity in the diffusion of AI into the real world. Most enterprises are going to need a ton …

There’s still so much opportunity in the diffusion of AI into the real world. Most enterprises are going to need a ton of support to be able to apply the model breakthroughs to their workflows. Intelligence alone is not enough to transform most processes because you need to bridge that intelligence with real world feedback loops. That requires connecting to various enterprise systems, getting the right data to the AI, enabling humans to make decisions at different steps in a process through the right UX, having workflows that improve the underlying data and models over time, dealing with regulatory and compliance challenges, and more. The way you implement AI agents for doing client onboarding in a bank is entirely different from contract review in a legal team. In life sciences, financial services, legal, manufacturing, and many other critical industries, AI is only valuable if it makes contact with the real world in a contextual way. The way that interaction is going to happen is through an applied AI layer. Some of that will come from the labs directly, but lots of the opportunity will necessarily come from independent companies that can go deep in each industry. And counter to some beliefs, this need isn’t reduced even as AI model capability improves over time. In fact, the better the models get, the more ambitious you can be in the workflows you can automate, which generally requires even more of this applied layer. Tons of opportunity right now.