TL;DR
- SMC breakthrough: MIT’s framework filters token paths on the fly, halving syntax errors.
- David beats Goliath: A 7‑B open model beat a 15‑B closed model on Python, SQL, robotics, and molecule synthesis tasks.
- M&A frenzy: Axios reports OpenAI is in talks to buy Windsurf (Codeium) for >$3 B.
- Sky‑high valuations: Bloomberg pegs Cursor’s parent Anysphere at nearly $10 B in new funding talks.
- Audit‑ready: SMC logs token weights—handy for EU AI Act compliance.
Sequential Monte Carlo turns 7‑B models into syntax snipers, jolting a coding‑assistant market already chasing a $10 B Cursor valuation.
Why AI Coders Still Flunk Compilers
Even GPT‑4 occasionally spits broken JSON. MIT researcher João Loula says baseline decoding treats every token equally, leading to unfiltered nonsense.
Their solution: treat generation as a probabilistic hunt—keep only promising paths, kill the rest.
Sequential Monte Carlo in Plain English
Imagine 64 rival coders writing the same function. Every second, an adjudicator bins buggy drafts and clones the best lines.
That’s Sequential Monte Carlo (SMC) for tokens: each candidate sequence receives a weight; unpromising branches die; compute shifts to survivors.
Benchmark Beat‑Down
| Task | 15 B Closed Model | 7 B + SMC |
| BigCodeBench Python | 67 % | 80 % |
| Text‑to‑SQL | 59 % | 76 % |
| Robot Motion Plans | 54 % | 70 % |
| Molecule Validity | 63 % | 86 % |
Compute overhead rose just 10 %—far cheaper than brute‑force validation.
The Great Assistant Land Grab
Hours after MIT News covered the paper, Axios leaked OpenAI’s $3 B Windsurf talks—its largest potential buy‑out.
Cursor, meanwhile, is courting investors at a near‑$10 B valuation. Analysts say the first IDE plug‑in to marry SMC‑style filtering with multi‑million‑token context windows could dominate enterprise dev‑ops.
Beyond IDEs
- Edge inference: Hospital tablets or car ECUs could run 7‑B models locally without sacrificing JSON sanity.
- Regulatory gold: SMC’s weight logs create an audit trail, meeting EU AI Act transparency rules.
- Citizen coding: Non‑programmers may soon fire off perfect PostgreSQL queries in plain English.
What’s Next
MIT wants to scale SMC to paragraph‑level reasoning and fuse it with online learning so models self‑correct. GitHub repos already show ten‑line wrappers bolting SMC onto GPT‑4 API calls.