
Streaming guy ex @confluent, CTO @excelian thoughtworks. Founder @logscape.com. code-monkey, songwriter, tennis nut, snowboarding nut and dad!
London
Joined March 2012
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Neil Avery retweeted
Replying to @PolitlcsUK
This is unfair. Why should people who watch Netflix have to fund the BBC?
SCRAP the BBC license fee!!
Replying to @PolitlcsUK
Say you just want to watch Netflix.
You pay £96 a year to Netflix to watch their service.
Then the government makes it law for you to pay a rival broadcaster £180 a year that you don't watch, so you can legally watch Netflix.
Can anyone think of a more crazy economic situation?
Neil Avery retweeted
Replying to @firesidealpha
Affleck is confusing the mechanism of a system with the properties that can emerge from that system. Some people have no concept of emergent phenomena. If you keep reducing the human body to its constituent elements, you will find no consciousness, emotions, or thoughts anywhere.
Build your own harness, folks.
This is absolute banger paper from NVIDIA on self-evolving agent harnesses.
(bookmark it)
They introduce SoL-Pi which cuts token traffic by nearly half.
And it matches its baseline harness on GPT-5.6 Sol and Opus 5.
More details below:
Instead of tuning a harness by hand, they run auto-research loops at the harness layer across many repository-derived and verifier-driven environments, keeping only the mechanisms that survive selection.
Four mechanisms survived:
> Action Fusion changes how actions execute
> Online Context Compact handles compaction during a run
> ObservationPack reshapes observation handling
> Evidence-Preserving Reducer covers delegated reading
On the 51-task EdgeBench evaluation, the savings translate to about a third off API cost. In dollars that is an estimated $8.75 to $13.50 per hour against native Codex and Claude Code harnesses, and $4.36 to $5.71 against the baseline harness.
Because the search runs across many environments rather than one, the retained mechanisms keep working outside the setting that produced them. Code is on GitHub under NVlabs.
Paper: arxiv.org/abs/2609.20519
Chat with Paper: academy.dair.ai/papers/sol-p…
A lot of otherwise smart people on Twitter seem 100% convinced AI risks are all fake and stupid and part of some marketing ploy. What is surprising is that some of these people seemingly also believe that AI’s positive uses are on an incredible trajectory of increasing capability with no end in sight. VC Twitter is particularly infected by this pattern. It’s not really coherent.
Most positive use cases for AI have a corresponding “dark version”. If you are super human at coding, you are also super human at hacking. If you are superhuman at structural engineering you are likely superhuman at finding structural flaws to knock buildings down. If you are superhuman at designing drugs, you are superhuman at designing novel undetectable poisons. If you can cure viruses, you can create them. Some of these “dark versions” are not so bad, and some are actually pretty scary. Either way these are real societal and technical problems that need to be solved to get the good stuff and avoid the bad stuff. We’re experiencing the first of these with coding and computer security which is the most advanced, but that won’t be the last. I think we’ll be able to solve these problems, but they aren’t solved yet and if you believe in continued AI progress they are surely coming.
But “bad people using AI” is not the only problem. Uncontrolled AI autonomously doing bad things, despite sounding kind of nutty, is also something we should be concerned about. AI “killing us all” is not the most likely outcome, but the chance of a major civilization-wide catastrophe doesn’t have to be very high for it to be a concern. Again, this is only a problem if capabilities advance to a point that AI can do really crazy things on their own, which hasn’t happened yet, but I think the Hugging Face incident is a good example of the outline of how things can go wrong when capabilities outpace alignment. We should be glad that the only available bad thing right now is hacking, which isn’t all that bad. It’s clear that as you get to superhuman capabilities you need a level of alignment and control that is correspondingly superhuman. Humans have plenty of misalignment problems themselves (serial killers, mass shooters, tyrants, etc), but it’s a manageable problem because most humans can’t do that much damage and we’ve developed systems to prevent dangerous humans from getting too much power.
Talking about these issues is just common sense. It’s not a sign of some kind of neuroticism or pessimism. These are just hard problems that it’s very important to solve for AI to have a positive impact. I’m pretty confident we will solve them. But we haven’t solved them yet, and to my mind we are clearly on a trajectory of rapidly increasing capabilities which means this is important. Mocking people who are worried about this or talking about it, without anything substantive to say about how we can be sure these problems won’t arise, is not really a very helpful contribution.
Neil Avery retweeted
🦔An NYU mathematician says OpenAI used his own progress against him to beat him to one of the biggest unsolved problems in mathematics. Tristan Buckmaster had been working toward a Millennium Prize proof using OpenAI's Codex when information about his progress reached OpenAI.
Days later, OpenAI published a full proof of the same problem using the same uncommon approach, after burning $22.5 million in compute to get there. When Buckmaster confronted them, exec Sébastien Bubeck allegedly said "Why would you ruin your career?" and "If you don't want me to be nice, then I don't have to be nice."
My Take
OpenAI spent $22.5 million to solve a problem with a $1 million prize. They didn't do this for the bounty. They needed a headline that says "our AI solved one of the hardest problems in mathematics" and they needed it before someone else got credit. They started days after they heard about Buckmaster's progress and took the same uncommon approach he'd pursued for months. That's hard to explain as coincidence.
Buckmaster did his work inside Codex. OpenAI reserves the right to train on Codex data. They admit they can't rule out that his usage helped improve their models. So a customer used their product, potentially handed them the roadmap, and then OpenAI outran him with $22.5 million in compute he could never match. I don't know if any of this was intentional. But if you're a researcher and you just watched this happen, I don't think you'd keep your best ideas inside someone else's product.
Hedgie🤗
techcrunch.com/2026/09/08/op…
Neil Avery retweeted
متكبرين
وصخين
ماكرين
غشاشين
فاسدين
المنتخب الوحيد اللي خلّى العالم كله يتفق على هدف واحد: يشوفهم يبكون... وبالنهاية صار اللي تمنّوه
Neil Avery retweeted
Qwen 3.8 Max is here and it beats Fable 5.
86.6 on TerminalBench vs Fable 5 at 84.6.
GPT 5.6 still holds the top at 88.8, so it is not a clean sweep.
But at $2/$6 per million tokens, the value is absurd.
The real headline: open weights next week. 2.4T Max going open, plus a 27B model that runs on a laptop.
Frontier intelligence, downloadable, in seven days.
Anthropic and OpenAI should be nervous.
Neil Avery retweeted
No quería creerle a los bicholovers pero tenían razón respecto a Messi. Soltarle un riflazo en la cara a un rival y ni siquiera preocuparte un poco por él? Se cayó la mentira del Messi humilde, su legado completamente manchado.
Neil Avery retweeted
Opus 5
As usual I have no take, other than:
If you've designed your harness/environment well, and not over-optimised around a specific model, today should feel like any other day...
...with a slightly lower failure rate
Neil Avery retweeted
Uma das maiores covardias que eu já vi um jogador fazer numa Copa do Mundo. Ainda mais sendo uma final...
Messi tentando cavar uma expulsão do Cucurella do nada.
Que coisa de mau caráter. xitter.cf/Anindagol9/status/2078…





















