daniel retweeted
We asked GPT-6 Astra to edit Qwen3.5-0.8B weights to improve math.
It directly changed only 0.016% of weights, fixing 0.8B's reasoning loops & improving math up to 6x and even instruction following 3x, without gradients or training.
We call this Weight-Space Programming: frontier LLMs can now natively read/write neural network weights! 🧵
Blog: rikiyat.github.io/blog/weigh…
Readers added context they thought people might want to know
LLM was given weights explicitly as text in prompt and used code/forward passes (per authors' logs) to ablate Qwen looping direction, a known thinking-mode issue per model card. Primarily fixed repetition in that mode, not general 'natively' improving weights/math.
rikiyat.github.io/blog/weight-sp…
github.com/RikiyaT/lm_und…
huggingface.co/Qwen/Qwen3.5-0…
huggingface.co/RikiyaT/Qwen3.…
daniel retweeted
The benefits of abundant intelligence will accrue far outside of San Fransisco.
Spent the last year writing about capital, sovereignty, and the coming reordering of economic power.
THE COMMANDING HEIGHTS
Commanding-Heights.com
daniel retweeted
"University researchers built a satellite that tracks people from low Earth orbit and dispatches a 5 kg payload to within .1 meter of their position, traveling at Mach 25 to anywhere on Earth in under 5 minutes. They suggest it could be used to deliver greeting cards."
Purdue University's IDEAS Lab built an autonomous drone that tracks runners through dense forests completely without GPS or cloud networks.
By running 3D LiDAR mapping and obstacle-avoidance AI entirely on-chip, it can weave under tree canopies and predict target movement through blind spots in real time.
Massive implications for next-gen search & rescue and edge AI.
daniel retweeted
We should be allowed to reverse engineer basically anything with AI. Yes, it presents issues with IP, but also we should have the right to understand and inspect how the software on owned local devices operates.
Let me get this straight.
A guy keeps getting weirdly targeted ads on his new Samsung TV.
So he breaks into his own TV to find out why. 1.2M people watch.
42 hours later, OpenAI deactivates his account. Reason: "Cyber Abuse."
His words: "i have never used openai to exploit or find vulnerabilities, only local reverse engineering"
Same week, people on r/claude say Claude now cuts off reverse-engineering write-ups MID-SENTENCE:
"A safety check stopped my response partway through creating the playbook"
The TV is fine.
The guy who opened it is the problem.
daniel retweeted
We can call it Black October for the security breaches:
Oct 21:
• PHP2Shell
• Railway
• Node.js
• LiteLLM
• GitLab
• SBI
• eMudhra
Oct 20:
• Plex2Shell
• SiteGuard
• Siemens
Oct 19:
• OVHcloud CLI
Oct 17:
• Opencode
daniel retweeted
Effective Immediately, all organizations using PHP for their systems are advised to be prepared for an update addressing two critical vulnerabilities. PHP is widely used for web applications. These vulnerabilities often provide a direct path to the server's file system or database. If an immediate update is not feasible, it is recommend that organizations take the system offline until it can be fully mitigated. NSA will follow up shortly with more specific guidance.
daniel retweeted
interpretability might be the most important scientific problem in the world right now, as I don't think we can solve alignment if we don't know what we're building. I think I have good news about it. I co-authored early work in mechanistic interpretability at OpenAI and came away pessimistic, because neural networks appeared to fold into arbitrary tangled knots. years later, I started openai's first large-scale automated interpretability project, finding about 2% of neurons legible with the primitive tools we had
with modern agentic tools and a much closer look, the picture looks totally different. the vast majority in models up to trillions of parameters are legible, and their circuits beautiful. many famous examples of tangled neurons turned out to be misunderstood. The roadblocks I expected mostly aren't there. I now think ambitious interpretability will be solved by the time we need it most, and possibly quite soon, as automated scientists keep improving. it may be a bitter lesson for interpretability: the simple thing, at absurd scale, works
already-clean.goodfire.com/
daniel retweeted
My dear friends, I’d like to show you my latest toy project
Introducing Handwired: turn your regular JavaScript code into a neural net!
- no training
- exact outputs vs the JS program
- fully differentiable
All runnable in a browser, without GPU
daniel retweeted
NASA's data is publicly accessible and while many excellent scientists work there they obviously don't have the time and resources (or incentives) to squeeze every last drop of data from legacy datasets.
There is a huge difference between what one postdoc spending 400 hours tweaking the department matlab script can find, especially when 200 of those hours are spent writing the paper and pushing it through review and extreme software skills are genuinely scarce.
Years ago I helped decode the Mars Viking GCMS raw data, which was uncharacteristically poorly documented. More recently I had a series of models replicate my results. To keep it interesting I initialized it without my results. Then once it had replicated my hard won work (in about 30 minutes) I instructed it to burn down the entire problem, pushing to the very limits of what the most sophisticated statistical methods can achieve. These are typically labor intensive and reserved for huge scientific collaborations like the LHC or LIGO. No-one is going to drop the equivalent of 100 postdoc years of effort on any legacy project. Then I had the model write it up and publish it.
Then I had another model do the same thing for the Mars THEMIS data, placing hard upper bounds on current vulcanism and hot springs. This instrument had a negative result about 25 years ago so never (afaik) even published a paper. It's still negative but at least people can read about it now.
Both analyses can be seen via projects.caseyhandmer.com
I hope teams at NASA are currently feeding all our hard won legacy data through state of the art models, but if not (or and) any private citizen could do it today for maybe $1 of tokens per project.
daniel retweeted
Lucky coincidence the labs are only successfully cracking esoteric math problems and not the problems where a solution would give the winner an asymmetric commerical advantage.
daniel retweeted
This is incredible
We’re releasing a broad range of new mathematical results produced by an internal frontier model.
We’ve been consulting with the independent Advisory Group on Mathematics and Artificial Intelligence at the Institute for Advanced Study, and we have drawn on their advice and public recommendations to inform how we release these results.
github.com/openai/math
daniel retweeted
neutrino observatories must be one of the most eerily beautiful structures humans have ever built
ALT Super-Kamiokande
ALT IceCube Neutrino Observatory
ALT Sudbury Neutrino Observatory
ALT The Deep Underground Neutrino Experiment (DUNE)
daniel retweeted
This is the doom I predicted a few days ago, coming for Photoshop. A clean-room open-source reimplementation.
No prizes for guessing that they decompiled Photoshop to source code, processed that to some kind of non-code specification language, then fed the spec to an LLM with an instruction to generate Rust.
Adobe just got nuked. And closed source is dead, dead, dead.
github.com/storytold/photocr…
daniel retweeted
too much writing, too much thinking, too much planning, too much analysis. your pencils are sharp enough. theres not much time left now, its best if you get going.
