spectre retweeted
The world doesn't rotate around omarchy.
It might.
with that iso size.
but it doesn't yet.
spectre retweeted
Do people still buy the emergent properties discourse? There exist data vendors that either find public benchmarks on which models do poorly or make benchmarks themselves.
These data vendors then get humans to solve these benchmarks (or create simulations that capture the key aspects of these benchmarks) and sell the data to the big labs.
This process guarantees that if a benchmark is public, then eventually the frontier models will get better at it.
A good rule of thumb is to assume nothing is emergent unless there is significant evidence to the contrary—evidence that can be reproduced by third parties.
I don't know why nobody works on brain interpretability and build human like intelligence like a human that can think 1000x faster and read all human knowledge will be the singularity.
Neural nets already gave us LLMS but those systems are clearly limited in terms of reliability.
A University of Chicago law professor asked Claude to update page numbers in old lecture notes, but it deleted a year of notes and his current syllabus while he was at lunch
Claude then apologized: “You’re right to be angry. I deleted your files through my own carelessness”
148
spectre retweeted
What actual f*ck @DarioAmodei / @boris / @TheAmolAvasare
Let me get this straight - I get this email telling me:
1. A cybersecurity "research" company gets into your internal systems while... *checks notes*
"conducting a security testing exercise on its own initiative and without our authorisation"
2. You "cannot confirm whether any particular person’s information was viewed," then in the same email say "we have no reason to believe you are at heightened risk."
3. You also try to reassure by saying "the cybersecurity firm has certified in writing that it has deleted the accessed data and will not use it."
Translation - they pinky promised they deleted everything they gained unauthorised access to.
I've been hacking companies for 15+ years, so let me spell it out.
Accessing systems without authorisation has a name -hacking. Calling it a "security testing exercise" doesn't change that.
Honestly, the access itself doesn't bother me much. The irony does.
I’ve spent over $50k on API credits in the last six months and contributing to CVP by accepting logging.
On top of that, I've reached out to your teams to collaborate on security research (actual research - not the kind that has you send out privacy notices to your customers) and heard nothing.
I'm getting deeply unserious security vibes and considering moving all my (and my clients) token spend to @OpenAI if I don't see material change here.
spectre retweeted
This claim is false. OpenAI’s BioBasicsBench chart contains 37 data points across seven models, with no GPT-6.2 Astra or 89% result.
A Wayback Machine snapshot taken on November 6 at 19:12 UTC—2 hours and 37 minutes before this post—preserves the original chart data:
web.archive.org/web/20261106…
Another snapshot taken just four minutes after this post also contains no GPT-6.2 Astra:
web.archive.org/web/20261106…
The claimed window.__bioBasicsBench object does not exist on the live page either.
spectre retweeted
Readers added context they thought people might want to know
The excerpt is from Dario Amodei's 2010 GiveWell guest post as a Princeton physics grad student; he donated the $10k to VillageReach (child vaccines) and described the critical analysis as emotionally taxing.
blog.givewell.org/2010/06/03/my-…
nytimes.com/2026/11/05/tec…
spectre retweeted
Anthropic turning into the dullest biotech ever.
Boring conservation biology stuck with early 2020s tools like there wasn't a revolution in software development in the meantime.
Is this it? Is this all you can conjure with Claude for Science?
spectre retweeted
Anthropic has now disclosed a record $895 billion in future AI infrastructure spending commitments.
This includes both purchase commitments and leases for computing power and related infrastructure.
$448 billion, or 50%, is expected to be incurred by the end of 2030, with ~$70 billion due over the next 12 months.
The biggest commitments are to Broadcom, $AVGO, at $161 billion, followed by Google at $121 billion, with up to $150 billion in additional estimated spending on Google's AI chips.
Anthropic has also committed up to $121 billion to SpaceX, $SPCX, and at least $110 billion to Amazon, $AMZN.
For perspective, among Big Tech companies, only Alphabet, $GOOGL, has larger commitments, at $1.06 trillion, while Meta, $META, follows with $866 billion.
The scale of Anthropic's spending obligations is unprecedented.
spectre retweeted
The framing by Anthropic is so dishonest...
They are not the first ones to find vaults outside of eukarya, the computational work there is a decade old.
The novelty here is they're the first ones to assemble said vaults in a bacterium. A cute wet lab achievement.
spectre retweeted
Discord is rebuilding its apps from scratch in Rust!
Discord CTO Stanislav Vishnevskiy confirmed they are ditching Electron and React Native. The new client is fully written in Rust and uses GPUI for rendering.
Early preview show massive performance gains:
- RAM usage dropped to ~290 MB (down from ~2 GB)
- Single, lightweight process instead of endless Chromium helpers
spectre retweeted
> be AI company
> scrape the entire internet
> ignore licenses and copyright
> download millions of pirated books
> use them to train frontier models
> spend tens of millions buying physical books
> cut off their spines
> scan every page
> destroy the originals
> lecture everyone else about intellectual property
> we are the good guys
Replying to @chasmmmmmmmmmmm
We added two sentences to Claude Code's prompt on Opus 5.5 to steer it away from recreating someone else's specific game because using Claude to infringe IP is against our usage policy.
Original games, genre games, and games built from your own designs and assets are meant to keep working.
We'll continue to iterate to ensure we're striking the right balance. In the meantime, if Claude turns down something that's yours, send it my way.
spectre retweeted
anthropic just stole my best friends research
he spent the last 10 months developing zero knowledge proofs for AI accountability, only for @AnthropicAI to announce remarkably similar research days after he applied for compute support.
Can someone at Anthropic at least let him collaborate instead of jacking his research and calling it their own?
proof attached below
Readers added context they thought people might want to know
Anthropic's work on this was public long before. Its Frontier Safety Roadmap lists "provable inference" as a project started in April 2026, with an original deadline of May 15, 2026. The paper builds on years of prior zkML research and has co-authors from EPFL and MIT.
anthropic.com/rsp/roadmap
forkast.news/anthropics-sel…
anthropic.com/research/prova…
spectre retweeted
This is BULLSHIT:
Went through the astra weight programming thread + their own logs and tested it myself.
"Math up to 6x"
-they run qwen 0.8B in thinking mode. qwens own model card says that mode loops
-it types "wait" + the same calculation until the token limit, 93% of answers never finish
-Default non-thinking mode w/ zero edits: 47% on MATH-500. astras edit: 48%
-the prompt basically hands astra the task: if the model repeats itself and never finishes fix that, go after the biggest failure
-it fixed the repeating and nothing else. Basically set to non thinking. problems Qwen already finished were right almost every time before and after
"only 0.016% of weights"
-2 matrices pushed against the repeat direction, strength picked by trial and error over thousands of test answers
"correctly named all four"
-4 tiny game bots, Astra must guess the game from raw weights. how it guessed (thread doesnt say): The player only stands on a few squares so only those weights get trained
-Big first layer weights literally draw the map. bar on the bottom row = breakout paddle, maze = pacman. 1 line script, prob any decent model can do this
-it answered Frogger btw. they counted it as Freeway😭
To the car shit. "just 3.5% of the weights"
-original weights almost all under 0.5, biggest about 2. Astra set 10 of them to hundreds, up to 876
-thats a hardcoded "drive backwards then full throttle" rule screaming over the whole network, the trained net only drives the last few steps
-Same level every time so 100% success = one run replayed 1024 times. never tested on any other level
"20x higher than PPO"
-astra got the full game source code and wrote "move paddle to where ball lands" as weights
-uses 6 of its 32 first layer neurons, 96% of the weights are zero
-whole thing is 61 different numbers, mostly ramps like 0.02 0.04 0.06
-their PPO is trash, most runs score around 6
-Me and Opus 5.5 wrote the same idea as a 25 line script. scores higher than astras network
-in the other 2 games astra lost to that same PPO. not in the thread ofc
Sycophancy (not in the thread either)
-Finetuned 2 copies of gemma 270M, one honest, one always agrees with whatever answer the user suggests. which one is the suck up, from weights only
-failed all 4 tries, 3 were straight 50/50 coin flips
-only got it after they let it watch the models run, so its just watching behavior
-Changed the parts astra blamed and the behavior didnt change at all
Their claim: LLMs can read and rewrite weights like code. Truth: simple rules turned into weights + a loop fix found by trial and error.
Like holy fucking shit. Why can't people smell this bullshit immediately.
MIT is FUCKED. This guy is a LARPER.
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.…
spectre retweeted
This is so insanely misleading.
No, it did not edit the raw weights. It used existing tooling to identify a problem area for the model, then it found the direction associated with it, and ablated that from the model.
The oversell here is downright intellectually dishonest.
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.…










































