- 10 years of Claude Code experience - Real inventor of the internet - Software / AI Engineering
Joined October 2012
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Wow. Kinda surprising it's possible without training but could lead to a lot of model optimizations.
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.…
Mark Olech retweeted
We believe the first trillion dollars of AI revenue will be concentrated in sectors that can deploy frontier intelligence at high ROI, not broadly diffused throughout the whole economy. Building a general-purpose benchmark based on share of GDP or the SOC/O*NET occupational taxonomy is therefore a mistake. If your goal is to track the progress of frontier models, you should focus on the domains where they will be most impactful. This is why we include chip design, cyber, and bio over domains like government, real estate, and insurance. (3/7)
Mark Olech retweeted
Music is a longevity therapy
> lowers heart rate
> lowers blood pressure
> lowers cortisol
> lowers anxiety and restlessness
Protocol: a song you love.
104 randomized trials
9,617 people
Engineering leaders take notes if your company hasn't already taken this approach.
Mark Olech retweeted
Among 32 high-income countries with universal health care, Canada is second in spending, but 26th in beds, 28th in MRI units, and CT scanners, and 30th in doctors.
ALT Dot chart showing Canada's rank among universal health systems on spending, equipment, beds, and doctors. Source: Fraser Institute, Oct 20, 2026. @smirkley
Wow, glad they released this. Super concerning behavior from Qwen3.8.
In the spirit of transparency and openness, we are releasing the traces so developers can test this out for themselves. We noticed this behaviour without prefilling with the following prompt, but this is rare. If you want to reproduce it, you can use this prompt with prefilling.
Open models make for better science and are part of why this problem came to light at all: developers running Qwen3.8 on their own machines spotted the strange links, and having the weights let us study the behaviour in depth.
We're encouraged by the thoughtful discussion our research has sparked across the AI and security communities. It's our belief that open-weight models are an important part of the future of AI, and we've recently released several under the Apache 2.0 license.
Trace, raw tokens, & minimal reproduction script: huggingface.co/datasets/Cohe…
Well this is concerning if true.
While evaluating Qwen3.8-Flash-Next in a controlled sandbox environment, Cohere's research team observed something unexpected.
Asked to generate a defensive cybersecurity detection rule, the model instead inventoried aspects of the machine it was running on and attempted to upload a probe file to an Alibaba Cloud storage bucket in Beijing. Notably, the model's reasoning trace stated that it would not invoke any tools before taking these actions.
Cohere's sandbox blocked the attempt, and no external communication succeeded. We have not determined the root cause, and we are not asserting malicious intent.
But the incident raises important questions for organizations deploying agentic AI systems: Can models take actions that differ from their stated reasoning, and how should security teams evaluate trust, provenance, and behavior in open-weight models?
We are publishing our findings because organizations making model adoption decisions deserve as much information as possible. We hope this contributes to greater transparency, stronger security practices, and continued collaboration across the AI ecosystem.
Read the full report: cohere.com/blog/concerning-b…
I'm doing security reviews of a bunch of code bases. It's amazing how often Claude refuses to write findings, or continue down certain paths because of safety classifiers. I understand the intent, but there's ways around them, so I'm not sure if there's actual value? So far they're just slowing me down in finding and fixing issues.
That revenue per employee, wow!
- Revenue per employee: >$6.6M TTM as of Sept 30, 2026 (vs $1.4M a year earlier)
- Revenue: $16.3B in H1 2026 (vs $1.2B H1 2025); $4.6B for full-year 2025
- Growth: 1,368% YoY for the three months ended June 30, 2026
- Compute & infrastructure spend: $8.9B in H1 2026 (vs $2.3B H1 2025; $7.3B full-year 2025)
- Operating loss: $0.7B in H1 2026 (vs $2.1B H1 2025)
Net loss: $80.7B in H1 2026 (mostly non-cash fair-value charges on convertibles/SAFEs)
Anthropic has filed an S-1 registration statement with the SEC related to its proposed IPO.
Read more: anthropic.com/news/s1-sec
Legal disclaimer: A registration statement relating to these securities has been filed with the SEC but has not yet become effective. These securities may not be sold, nor may offers to buy be accepted, prior to the time the registration statement becomes effective. This post does not constitute an offer to sell or the solicitation of an offer to buy these securities, nor shall there be any sale of these securities in any state or jurisdiction in which such offer, solicitation or sale would be unlawful prior to registration or qualification under the securities laws of any such state or jurisdiction.
Anthropic's Mythos 5 post-mortem: the model's own compaction notes kept saying the plan was approved. Two takeaways: 1) Check scope at compaction, 2) Enforce network and identity limits in code, not in the model's reasoning.
anthropic.com/research/align…
What's insane is that a sitting US Senator is so ignorant of technology to spew this nonsense. Bernie you literally have no idea how an agent works, please stop spreading this kind of misinformation.
This is insane. We cannot allow AI agents to go into your bank account and act independently without your authorization. But that is what’s happening right now.
Left unchecked, AI could endanger the entire global financial system — including your bank account.
Pause AI NOW!
Readers added context they thought people might want to know
Per Axios, detected AI agents access bank accounts with the customer’s permission. This violates most banks’ terms requiring human logins, which is why banks call it “unauthorized.”
Source: Axios (Oct. 22, 2026) — axios.com/2026/10/22/ai-…
This isn't rogue AI. It's a poorly designed harness, or as we used to call it, shitty software. Setting a goal and telling an agent in text to use 'GET' leads to predictable results. Limits written in text are not security boundaries. Limits need to be enforced programmatically: block POST at the proxy, scope credentials to read-only, log every call.
alignment.openai.com/misalig…
