Quote of the day by ex-OpenAI chief scientist and SSI co-founder Ilya Sutskever: 'AI will keep getting better and the day will come when AI will do all the things that we can do' — a staggering prediction about a future superintelligence
THE SO WHAT
When someone with Sutskever's history says AI will do “all the things that we can do,” they're normalizing full-scope automation as a planning assumption, not a sci‑fi edge case. Treat this as a forcing function to map which of your current human-only workflows you’d actually want to keep that way.
READ THE SOURCE
MORE FROM THE WIRE
Applied AIAnthropic is operating a lab that conducts biology experiments
An AI lab running its own wet lab collapses the distance between model capability and real-world bio experimentation—governance, not just safety research, now has to live inside the same org chart as the tools. If you operate in bio or adjacent risk domains, assume leading labs will be direct R&D actors, not just model vendors, and update your dependency and oversight map accordingly.
Applied AIAI Hallucination Nearly Triggers US Military Operation
An LLM hallucination getting anywhere near triggering a military operation is the clearest proof yet that AI outputs are already wired into consequential decision loops. If you run systems in defense, critical infrastructure, or finance, you need hard constraints on where model output can flow—not just better prompts or training.
Applied AILeaked presentation: OpenAI expects negative free cash flow of $278B from 2026 to 2030 and projects its revenue will grow from $36B this year to $350B in 2030
A projected $278B negative free cash flow against a $36B→$350B revenue ramp cements frontier AI as a capex arms race, not a normal software business. For enterprise buyers, this likely means continued price pressure on base inference and aggressive pushes into higher-margin, higher-lock-in products to make those curves meet.
Applied AIOpenAI Projects Burning Through $278 Billion by 2030
If one lab is modeling nearly $300B of cash burn through 2030, hyperscalers, chipmakers, and power providers are implicitly underwriting that risk—your AI roadmap is now entangled with their balance sheets. Operators should assume rapid iteration in pricing, packaging, and partnership terms as these capital plans collide with real demand.