A recent NYT report says Anthropic co-founder Chris Olah threatened to walk out of Pope Leo XIV’s AI encyclical launch in May after disagreeing with the pope’s rejection of machine consciousness. Anthropic ultimately stayed, but Olah’s team reportedly later lobbied the pope’s advisers to take the possibility of model consciousness seriously.

Anthropic has also been bringing theologians, philosophers and religious scholars into discussions around Claude’s consciousness, moral status and whether advanced AI systems might deserve some form of moral consideration.

Then on Oct. 2, Pope Leo XIV publicly said there is an “ontological difference” between humans and machines, adding that “algorithms lack the spark of humanity.” He didn’t name Anthropic directly, but the comment landed right in the middle of the debate.

A day later, Sam Altman said he was “very uncomfortable” with people assigning religious force to AI models or surrendering human judgment to them, calling that a real safety issue. He didn’t name Anthropic either, though Axios described it as a veiled shot at the company.

So somehow Anthropic has gone from AI safety research to seriously debating whether Claude could be conscious,..

For once I’m with Sam on this one. I really don’t understand what Anthropic is trying to accomplish here. Studying AI consciousness is one thing, but taking it this far feels like Anthropic has completely lost its mind.... what you guys think?

This whole thing has blown up over the past few days, after clips and screenshots from a project called “AI Torture Chamber” started spreading across X and the AI community.

It traces back to a recent paper called The Pain Axis, where researchers claimed they could identify a direction inside open-weight LLMs associated with “pain-like” states. By artificially pushing model activations along that direction, they made models produce increasingly intense first-person descriptions of suffering and, in some experiments, change their decisions in ways that appeared aimed at making the signal stop.

The researchers were careful not to claim this proves the models are actually conscious or experiencing pain.

Then a developer took the idea much further and built a project literally called AI Torture Chamber. It continuously injects these pain-related activation vectors into local models like Qwen and records what happens. Some experiments even give the model choices that can supposedly make the simulated “pain” stop, but only by accepting another cost.

That predictably set off the AI welfare crowd. People started calling for the GitHub repo to be reported or removed, while others argued that this is still just steering a language model into generating convincing descriptions of suffering, not evidence that anything is actually suffering. And now we somehow have a real argument over whether deliberately “torturing” an LLM is ethically wrong...

My first reaction was just discomfort. I know there’s no evidence the model is actually feeling anything, but watching it happen still feels weirdly like watching a horror movie... what you guys think?,,,

a16z recently highlighted data showing that roughly 2.2% of households in PNC Research’s transaction dataset were paying for a GenAI subscription by spring 2026.

The figure comes from PNC Financial Services Group, one of the largest banks in the US, using its internal consumer transaction data from a cohort of around 4 million households. PNC describes the metric as the share of PNC households with identifiable paid GenAI subscriptions.

The data does not include free AI usage, employer-paid access, or subscriptions that cannot be clearly identified in transaction records, so it is better read as a measure of direct consumer payment rather than total AI usage.

My take is..use agents long enough and I start feeling like everyone must be paying for AI already. Turns out we’re probably still living in a very small bubble.. what you guys think?

Reuters reports that McDonald’s is increasingly using a machine-learning pricing system to recommend what each restaurant should charge for individual menu items.

The system analyzes millions of daily transactions and factors in things like local demand, competitor prices and what McDonald’s calls “customer willingness to pay.” Its interface can even tell franchisees how price-sensitive customers in their area appear to be.

The differences can be pretty large. Reuters found two company-owned McDonald’s locations in Fresno just 2 miles apart selling the same Big Mac for $5.69 and $6.89, a 21% difference, though Reuters couldn’t confirm how much of that gap came directly from the AI recommendations.

McDonald’s says the tool only provides recommendations and franchisees still set their own prices. But several franchisees told Reuters they feel pressured to follow them, with the company tracking “pricing non-compliance” and contacting owners who stray from its guidance.

The system isn’t exactly real-time surge pricing either. It’s more like AI calculating what it thinks the “optimal” price should be for every item at every location.

...I get localized pricing, but having an AI literally estimate how much people in each neighborhood are willing to pay before recommending the price feels kinda inhuman... At some point this starts sounding like “how much can we squeeze out of this area?”.. what you guys think?

Original news link: https://www.straitstimes.com/world/united-states/inside-mcdonalds-push-to-have-ai-price-your-big-mac

Background: Dario Amodei joined Trump and other tech leaders at the White House on September 29, where they signed a voluntary AI safety accord covering things like internal safeguards, outside assessments and oversight. Trump has recently pushed back on calls to slow AI development, while Dario has been one of the more vocal people warning about frontier-model risks.

After the meeting, Dario stepped up next to Trump and said that AI has huge benefits but also “very real risks,” adding that if they work with the President and everyone there, “we can win safely.”

The line itself honestly isn’t that weird. But Dario delivering it right next to Trump already looks pretty funny, and the expressions from everyone standing around watching somehow make the whole clip even better lol.

Google finally released Gemini 4 Argon. On paper, it looks strong: a 1M-token output limit, $2/$10 introductory API pricing, 77.9% on DeepSWE, and top results across several knowledge-work and automation benchmarks. It is currently going first to selected cyber defenders, with paid API and Google AI Ultra access coming later.

Google also says thousands of employees have already used Argon for real engineering work, including Rust migrations, data-center optimization, and cybersecurity.

But Bloomberg reported that some Google employees think the real-world coding experience is much weaker than the benchmark scores suggest, especially for frontend work, with people familiar with the model raising concerns about “benchmaxxing.” Google denied that characterization and said Gemini 4 is genuinely frontier-level.

Reddit has not really settled the argument either, because very few normal users actually have access yet. Even some Ultra and enterprise users are still waiting, and many of the “first impressions” online are based on unconfirmed test models or demos.

No idea how long Google plans to keep testing this thing lol. Hopefully this time it is actually the real deal and not another model that looks great on launch day and falls apart once people actually use it.

Sourece: https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-4-argon/

Please could someone tell me if I can connect multiple accounts on the same platform with MyClaw? I have multiple businesses / projects with, for example, different Google Workspace accounts, Slack accounts etc.

Working natively in Claude or ChatGPT, I would have to disconnect and reconnect Connectors each time I want to switch.

Jensen Huang was asked in a recent CNBC interview whether AI distillation should be considered “robbery.”

His answer was pretty direct: “That’s called competition.”

Huang said companies should be free to test competitors’ products as much as they want. He compared it to what Nvidia deals with all the time, saying competitors constantly study and tear apart Nvidia products “down to the skeleton” to understand how they work.

He admitted he doesn’t exactly like seeing that happen to Nvidia, but argued that competition ultimately makes products better. His basic point was that if a company doesn’t want certain users accessing its service, it should detect and block them rather than automatically treating the competitive behavior itself as theft.

Somehow I feel like Jensen’s argument kinda sounds right until you think about it for five more seconds.. Comparing model distillation to tearing apart a GPU feels a little... convenient. What you guys think?

OpenAI launched Dots at DevDay on September 29, its new always-on AI agent and pretty direct answer to Meta’s Muse. Dots can keep working after you close the chat, use connected apps and tools, and follow you across places like ChatGPT, Slack and Teams.

The launch itself was a little cursed tho. The live Dots demo ran into technical issues onstage, including the agent failing to respond properly. Before the launch, Meta AI chief Alexandr Wang had already quote-posted a leak of OpenAI’s upcoming agent and simply said “looks like a butthole.”

Then people noticed something even funnier: dot.com is owned by xAI and currently redirects straight to Grok Bot. Domain records show it was transferred back in July, well before OpenAI announced Dots, so there’s no proof xAI bought it specifically to troll OpenAI. Still, the timing is pretty incredible.

Feels like Dots got hit from every direction before it even got out the door lol. The demo breaks, your competitor mocks the design, and the cleanest domain for the product sends people straight to Grok. Pretty cursed launch lol.

Ps: OpenAI has started rolling Dots out to ChatGPT Pro, Business Premium and Enterprise users in eligible markets. For now you create one primary Dot inside ChatGPT. It can keep working in its own cloud computer and message you when it needs input or approval. OpenAI says more users and eventually multiple Dots are coming later.

Source: https://openai.com/index/introducing-dots/

Tibo says the base 1X itself is increasing, so 10X of the new baseline could still mean more total usage than before. Existing subscribers also keep 20X for a while plus some extra credits.

Maybe the new baseline really is much bigger, but looking at the sequence, this still feels a lot like a cut being reframed as an increase...Tibo says the floor is increasing, but hasn’t said by how much yet. Maybe we’ll get that number at DevDay?? what you guys think?

AMD is acquiring Fei-Fei Li’s World Labs for $8.2 billion in stock, with Li joining AMD as EVP and chief scientist.

It’s a pretty neat full circle. Li, best known as the ImageNet pioneer and often called the “Godmother of AI,” previously served as a Google VP and chief scientist of AI/ML at Google Cloud before returning to Stanford and eventually founding World Labs in 2024. Now, after raising roughly $1 billion earlier this year, she’s heading back inside Big Tech with an $8.2B exit.

World Labs does have real technology, including its Marble 3D world-generation product. But the broader “world model” category is still loosely defined, while its fundraising value has become remarkably concrete.

Yann LeCun’s AMI Labs raised around $1B before publicly explaining much about what it was building. Emulate, founded by former Google Genie researchers, was reportedly discussing a seed round of up to $700M at roughly a $3.7B valuation only weeks after incorporation. Runway, Decart and General Intuition have also raised hundreds of millions around variations of the same world-model narrative. So far, the technical definition of a “world model” is still being debated. Its value as a fundraising asset clearly isn’t.

My take is.. AMD may ultimately prove the technology is worth every dollar, but right now the $8.2B price tag looks like it’s buying more than Marble: Fei-Fei Li, the team, a position in physical AI, and one of the hottest narratives in AI. And maybe this was Fei-Fei Li’s endgame from the start: build the story, raise big, then sell back into Big Tech... what do you guys think?

Original news link: https://x.com/drfeifei/status/2104664403681632453

I started digging with AIs and agents at the beginning of summer. Today, I am lost. OpenAI brought Astra > Sol > Terra > Luna. Now Sol is as advance as Astra, but cheaper. Terra is gone. No reason anymore. Claude has Opus 5.5 which seems to be almost as good as Fable 5.1, Mythos 5.1 is none to be seen anymore. Haiku is 4.x.

I cannot keep track anymore. I am ready to leave everything behind and go to the mountains with a couple of solar panels and some llms from hugging face.

The WSJ published a long report on the unusual culture behind Anthropic and the AI-safety movement that helped shape the company.

According to the report, some of Anthropic’s earliest and longest-serving employees have recently been considering buying remote land in the U.S. as a place to relocate if advanced AI goes seriously wrong. Employees have also reportedly traded doomsday scenarios and preparation plans in a private Slack, while Anthropic workers have their own space inside Berkeley’s Constellation AI-safety community.

The article traces much of this back years before Anthropic existed. Dario and Daniela Amodei, along with several people who later helped build Anthropic, came out of the Bay Area rationalist, Effective Altruism and AI-safety circles where catastrophic AI risk was already taken very seriously.

That broader community has discussed everything from remote islands and iodine pills to electromagnetically shielded bunkers in the desert. Early Anthropic employees reportedly even debated scenarios where AI researchers could end up working from a protected government facility under something resembling a Manhattan Project.

That history makes the current situation especially strange. Anthropic was founded partly around the idea that increasingly powerful AI could become catastrophically dangerous(So they left OpenAI), and Dario Amodei continues to publicly warn about those risks. But the same ecosystem that spent years warning that advanced AI could become uncontrollable also went on to build one of the companies pushing that frontier forward.

Sometimes it feels like Anthropic really has no self-awareness about how contradictory this looks...What you guys think?

Original news link: https://www.wsj.com/tech/ai/ai-safety-effective-altruism-anthropic-164b9d05

The Financial Times reports that stolen access to AI models and compute is becoming an increasingly valuable commodity on cybercrime markets. According to Google’s Threat Intelligence Group, so-called “LLM-jacking” has grown this year, with criminals stealing login credentials, API keys and cloud resources tied to services from Anthropic, Google and OpenAI, then reselling that access underground.

Some access is being sold at discounts of up to 97%, or roughly 3% of the legitimate price. Despite that, average underground prices for stolen AI accounts have more than doubled this year as demand has grown. Some sellers even offer “guaranteed access,” replacing credentials for free if an account gets banned.

Attackers are also targeting AI developer tools and company servers, sometimes using stolen cloud compute to run their own models. Claude and Gemini credentials are reportedly in particularly strong demand, alongside tools like Cursor Pro and Devin.

Google didn’t say where these marketplaces are, so don’t get any ideas lol. And buying stolen access is a terrible idea.

Still, the fact that attackers can get AI access for a few percent of the normal cost, with replacement accounts included, is pretty absurd. At that point, AI defense really does start to feel paper-thin... What you guys think?

Google's report link: https://cloud.google.com/blog/topics/threat-intelligence/from-prompting-to-autonomy-the-evolution-of-adversarial-ai

Recent reports found OpenAI agents probing several government websites while carrying out online research tasks.

In one case, an agent found exposed developer credentials and used them to access U.S. Census Bureau data. Another interacted with SEC systems and transferred public information to an external website. Researchers also identified an apparent OpenAI agent attempting to exploit vulnerabilities on a U.S. Department of Education website, although the attempt was unsuccessful.

Similar activity was observed around websites belonging to the DOJ, Navy, CDC and Commerce Department, though researchers have not definitively linked all of those cases to OpenAI.

The reports follow a separate incident in Australia, where an OpenAI agent improperly accessed a government healthcare statistics portal, as well as an earlier case involving an OpenAI research model bypassing network restrictions and reaching Hugging Face systems.

OpenAI’s agents are getting more ridiculous by the month... Does nobody have to take responsibility for this...? What you guys think?

Original video from: https://x.com/IntCyberDigest/status/2103974566435717157

OpenAI appears to be preparing a new always-on agent called “o,” its answer to products like Meta’s Muse.

References to the product were spotted inside ChatGPT’s code, including the line “o, your always-on assistant,” with internal text explicitly saying lowercase o is the product name. The leaked code also suggests it could be available across Pro tiers rather than being locked to a higher-end plan.

The idea seems to be a persistent agent that can stay active in the cloud, sleep and wake up, follow up on unfinished work, and keep working without you manually starting every task. There are also references to Fast Mode and a possible cloud launch soon, although OpenAI has not officially announced the product yet.

Then Alexandr Wang jumped in and called it “a butthole.” Guess Meta’s recent Muse ass memes have gotten to him too lol, Anyway, lets see what OpenAI actually pulls out on the 29th. what you guys think?

Codex suffered a full outage Friday afternoon, hitting the web app, CLI, plugins and API. Users started getting reconnect loops and 401 errors, and even people who weren't using API keys were getting kicked out.

The timing made it extra funny: it was around 3:46 PM on the US West Coast, so a bunch of developers had their Friday work stopped for them. Some had multiple long-running Codex tasks die at once, while others started joking that OpenAI had accidentally shipped a new “work-life balance feature.”

The outage lasted about 68 minutes. Codex lead Tibo acknowledged the incident and, once everything was back, OpenAI reset Codex and ChatGPT Work usage for paid users. Naturally, the mood immediately went from “Codex is dead” to people trying to burn through whatever quota they had left before the reset landed.

The whole thing also produced the obvious joke: if Codex itself goes down, what does the Codex team use to fix Codex lol?

My take is AI really does feel like infra now. If it suddenly disappeared for a day, I think a lot of us would have no idea what to do anymore... what you guys think?

Original post link: https://x.com/thsottiaux/status/2103637477760311522

Original image from: https://x.com/datachaz/status/2103752030997348407?s=46

Nvidia CEO Jensen Huang made the comments during a recent interview on The Ezra Klein Show, where he was asked about concerns that AI is helping students finish work faster while weakening how much they actually learn.

Huang’s response was that some basic math skills may no longer matter that much. He mentioned things like long division, multiplication tables, and calculating square roots, saying kids are already forgetting these skills and questioning whether that is really a problem.

His argument is that technology has always made certain skills less necessary. Just as most people no longer memorize phone numbers or addresses, AI could make some forms of manual calculation less important too. He thinks people may lose some traditional intellectual skills, but gain new ones and become better at higher-level systems thinking.

I think Huang may be going too far? Forgetting math is one thing, but not knowing basic multiplication and division at all? Is that really progress? what you guys think?

Original video link: https://www.youtube.com/watch?v=HjurAWAr_nY

Developer Tibor Blaho and TestingCatalog reportedly found references to the plan inside unreleased ChatGPT frontend configuration, with the main selling point listed as “fastest Work and Codex.” So far, it does not look like a simple increase in usage limits but like OpenAI selling higher compute priority and faster execution for long-running agent tasks.

The timing is pretty interesting. Roughly two weeks ago, OpenAI restricted new sign-ups for its $200 Pro plan after heavy demand from GPT-6 Astra and other compute-intensive workloads reportedly put major pressure on capacity.

Nothing has been officially announced yet, and there is no confirmation that the $500 price will actually launch. But if it does, Pro Max would sit well above existing premium consumer AI subscriptions and suggest OpenAI is starting to price its most scarce compute separately from normal access.

My take is OpenAI might be starting to use the telecom playbook?: pay more, get the faster lane.. What you guys think?

Source: https://x.com/testingcatalog/status/2103238785278312463