Doom or Bloom
Question 1
What do you think AI means for our future—and why?
AI could eventually be enormously beneficial, because general intelligence is achievable. But the current industry keeps confusing fluent imitation with dependable reasoning. LLMs can produce useful code, summaries, and interfaces while still fabricating facts, losing track of constraints, and failing unpredictably. “Hundreds of models, always the same failure modes.” Making them larger has improved performance, but it has not supplied a theory of structured knowledge, reasoning, or planning.
That distinction matters because unreliable systems are already being turned into agents and deployed with too little oversight. My immediate concern is not an omnipotent science-fiction villain suddenly awakening. It is agents enabling hacking at scale, automated systems making consequential errors, and powerful actors deploying them recklessly. A convincing demonstration is not evidence that a system works reliably in the open world.
Economically, the promises are inflated too. Investment commitments, subsidies, and cheap access do not prove sustainable customer value; if funding or willingness to pay weakens, the reversal could spread beyond one company. Technically, I expect progress to require different architectures that combine learning with structured knowledge, reasoning, and planning—not simply another giant training run.
So the future is neither “AI is fake” nor “AGI is around the corner.” AI can matter enormously, but getting there requires better science and, meanwhile, enforceable standards, testing, incident reporting, and liability. Press releases are not evidence, and lawsuits years after the damage are not oversight.