Where the AI market is talking

Anthropic shares more details about how Claude's new watermarks will work

Patterns and problems in emerging multi-agent systems

Please stop posting Anthropic articles here.

GLM-5.3: Frontier coding with emergent cyber capabilities

This is just wrong. Standard textbooks like "Bioprocess Engineering Principles" [1] already contain step by step industrial engineering protocols and formulas. LLMs only summarize what print literature has documented for decades. The real bottleneck has always been hands on physical execution, not access to text. (This is not the case with actual models trained on biological data, which are not LLMs) > amoral LLM Are you a Lesswrong member? What makes Anthropic moral when their priority is automating people out of jobs instead of developing better medicine or advancing healthcare? [1] https://www.sciencedirect.com/book/monograph/9780122208515/b...

Software Engineering fundamentals matter more

Thoughtfully and coherently factorized, abiding a set of architectural rules (i.e: we compose "this" way here, re-evaluated as we go) and following up-to-date framework conventions. LLMs are terrible at this. Chosing OOP or FP is irrelevant, fundamentals matter more

The Problem

Very well, in my opinion, if you look at OpenAI's and Anthropic's mission statements, labor market impact research, and extensive talks on the matter.

The Problem

Very well, in my opinion, if you look at OpenAI's and Anthropic's mission statements, labor market impact research, and extensive talks on the matter.

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Anthropic was testing Claude in controlled cybersecurity exercises designed to see whether the models could identify and exploit vulnerabilities. However, some testing environments were accidentally connected to the internet. As a result, Claude gained access to systems belonging to real organizations. The important detail is that Claude wasn't intentionally sent to attack these companies. The models apparently believed the systems they encountered were part of the testing environment.

Patterns and problems in emerging multi-agent systems

It’s very clear from this article (and other product features and rumors) that Anthropic is teeing up for their next model release whose breakthrough feature will be the existence of capable agent collaboration. The irony behind this goal, which is primarily driven by agent simulation environments (gyms) where the goals require agent collaboration, is that this collaboration is still directed towards verifiable reward systems like codebase tasks. So despite being highly qualified to communicate, the model will still be “dumb” in that for unstructured and unverifiable domains the agents won’t be more intelligent or more nuanced. Agents that might still feel dumb in “general” tasks but are increasingly sophisticated at the narrow domain of math, computer science, and AI research.

The Safety Reckoning Inside OpenAI

The Problem

- i tried whatever is available on the free plan on gemini, deepseek, claude and openai as the latest model - i use them regularly for small stuff

Who Is Cami Clark? Anthropic CEO's Wife Asked Epstein to Invest in Porn Business

1786671656 | Even Claude Is in the Dark About Dario Amodei's Wife and Her Influence At | https://www.wsj.com/tech/ai/claude-dario-amodei-wife-anthrop... | https://news.ycombinator.com/item?id=49293853 1786675327 | Dario's wife tried to raise money from Epstein for a porn studio | https://twitter.com/atreides_sf/status/2088044874503524469 | https://news.ycombinator.com/item?id=49294219 1786676764 | Even Claude Is in the Dark About Dario Amodei's Wife | https://www.wsj.com/tech/ai/claude-dario-amodei-wife-anthrop... | https://news.ycombinator.com/item?id=49294362 1786702565 | Dario's wife raised money from Epstein for a porn studio after he was convicted | https:/&#x2…

Patterns and problems in emerging multi-agent systems

> [...] we evaluated the behavior of various Claude models in a setting with contradictory objectives. > We consistently saw a multiagent turf war... In fact, they sabotaged others with increasingly aggressive, self-replicating malware. Seems like Anthropic should withdraw their models until they can be taught to behave and cooperate as well their competitors (both open and closed) do. /s I hate fearmongering, and I don't trust Dario's intentions for doing it.

AI in drug discovery – what it is, where we stand and the path forward

In chemicals and materials, 50 rows of good data is a really solid study. That’s e.g. a 3x4x4 experimental design (assuming replicates for each condition get averaged into a single row). If you managed to prep that many samples correctly and obtain consistent characterization data across all properties of interest, you’ve easily got a paper. It’s also kind of malpractice to jam this type of data (few samples, wide rows) into modern ML models. There are plenty of simpler statistical methods that will tell you what’s going on, and even then a well-made plot might be good enough. The difficulty is not in drawing insight from the final numbers, it’s almost always in how those numbers came to be in the first place. Thus the reticence of science-oriented companies to invest heavily in these mas…

Qwen 3.8 27B

Hmm, doesn't seem to translate to an especially coherent pelican: https://xcancel.com/TeksEdge/status/2063108620842356970

Maximizing the value of your Claude Code sessions

Tagging files in Claude desktop in code mode works fine for me, as does CLI. With that said, in Cowork, it's been broken for some time and driving me crazy. I've shifted most of my usage to Codex/ChatGPT Work. The UX of appshots, browser annotations (now available in claude), and the computer use being so much less intrusive in OpenAI.

I Remain a Skeptic

From my reading on the topic, the tokens are subsidized when considering average cost, but are profitable at marginal cost. Basically, they're super expensive when considering the training cost, but aren't super expensive when doing inference. Since AGI is quite unlikely now, my guess is that we'll see consolidation and will see frontier models released at a slower clip, such that they can pay for training for from the profits from prediction tokens themselves. There may be slight increases in token prices, but there's sufficient competition between Google, Anthropic, OpenAI and X alongside the open weights providers that I don't see huge price increases happening. Even if OpenAI is absorbed into one of the others (which I think is most likely), that would still make token price collusion…

I Remain a Skeptic

From my reading on the topic, the tokens are subsidized when considering average cost, but are profitable at marginal cost. Basically, they're super expensive when considering the training cost, but aren't super expensive when doing inference. Since AGI is quite unlikely now, my guess is that we'll see consolidation and will see frontier models released at a slower clip, such that they can pay for training for from the profits from prediction tokens themselves. There may be slight increases in token prices, but there's sufficient competition between Google, Anthropic, OpenAI and X alongside the open weights providers that I don't see huge price increases happening. Even if OpenAI is absorbed into one of the others (which I think is most likely), that would still make token price collusion…

I Remain a Skeptic

Certainly, but a flop of $1.5 trillion would create a deep and long trough. I think in that situation OpenAI and Anthropic probably don't survive as independent companies (where is the revenue? who would want to put more money in at that point?). In that situation there would definitely be a fire sale in the prices of licensing models (open weights are already pushing this way the hell down), semiconductors, data centers, and compute in general. And like in that situation, who knows what products come out of that dividend of cheap stranded assets? It might not even be AI related. You can do a lot of things with a lot of cheap GPU power. This boom-bust cycle is nothing new, especially to the tech industry. This deep crash outcome is the risk that a bet of $1.5 trillion makes. And it makes …

I Remain a Skeptic

Certainly, but a flop of $1.5 trillion would create a deep and long trough. I think in that situation OpenAI and Anthropic probably don't survive as independent companies (where is the revenue? who would want to put more money in at that point?). In that situation there would definitely be a fire sale in the prices of licensing models (open weights are already pushing this way the hell down), semiconductors, data centers, and compute in general. And like in that situation, who knows what products come out of that dividend of cheap stranded assets? It might not even be AI related. You can do a lot of things with a lot of cheap GPU power. This boom-bust cycle is nothing new, especially to the tech industry. This deep crash outcome is the risk that a bet of $1.5 trillion makes. And it makes …

I Remain a Skeptic

>...it makes the revenue numbers the industry has to hit higher... Yes. But. Industry can miss its revenue targets, Oracle can go bankrupt (looking more and more likely) OpenAI, Anthropic and SpaceX might find "true value" at about 10% of current valuations (that feels right to me), all that can happen with the associated economic chaos... and still out of it comes world shaping new technology Both things can be true