Being in AI , I can see where @svembu is coming from on this issue. The pace of advancement is so rapid that even industry leaders are being taken by surprise.
When I said several months ago that mass layoffs were inevitable it was seen as scaremongering.
AI represents a fundamental shift in the way things can be done. It is not just an incremental tool to boost efficiency.
Also if you can deploy an application for a customer in a week instead of several months of development your pricing model goes for a toss as development costs are much lower.SAAS/Licensing models will undergo severe disruption with huge downward pressure. The only way companies can survive is by becoming leaner. AI, server and infra costs may be going up now but they too will see a plateauing soon.
@gssudharsan For a lot of companies seems like a no brainer offering. Existing open ai customers will just use decisions api. Anthropic will soon come up with one and so do every other lab.
Meet Microsoft-Decision-1 by @Microsoft
A small model built for one job: fast decisions
Routing, classification, agent controls, AI judging. It returns a calibrated probability for every option.
→ Post-trained from Qwen3.5-9B
→ 35x faster than GPT-6 Sol
→ 4.5x faster than the runner-up
→ Top accuracy across 36 benchmarks
→ $0.042 per million input tokens, output is free
@gssudharsan Played with Jev a bit. Was pretty good. But its a decision model so most of the use cases are also fairly simple. Really comes down token economics.
NYU (@nyuniversity) announced the creation of the Courant Institute School of Mathematics, Computing, and Data Science today, signaling the university’s enthusiastic commitment to mathematics, computing, and data science over the coming decades: https://t.co/dz4NsvJg4w
@soumithchintala Best wishes for wherever you go/whatever you do next. Have been a big fan of your work and all the contributions you have done. Pytorch for the W.