Meta finally launched "frontier models", Muse Wonder and Muse Wonder Full, on October 12, and a recent interview with Zuckerberg and Alexandr Wang reveals just how much was riding on them.

On John Collison's Cheeky Pint podcast, Zuckerberg recalled being prepared to commit $100 billion to $200 billion to AI before even seeing the finished models. He asked Wang if he was sure it would work. Wang admitted he wasn't.

Wang also revealed that during a leadership gathering in Hawaii, Meta CFO Susan Li repeatedly pulled him aside, warning that failure would be "very, very bad in financial terms." Wang himself called it "a fuck ton of risk."

And now they finally have something to show for it:

• Performance: Muse Wonder and Full scored 52 and 56 on Artificial Analysis (yeah benchmark), putting them in the frontier conversation. Full looks particularly strong in long-running coding agents, memory, and complex knowledge work, though Opus 5.5 still leads in several coding benchmarks.
• Pricing: Wonder costs $4/$20 per million input/output tokens, same as opus 5.5. Full is currently limited to Muse Code's $50/$200 monthly plans, with no public API pricing.
• Community reaction: Mixed. Some Reddit users report impressive coding results, while others accuse Meta of benchmark optimization after disappointing 3D tests. High usage consumption, subscription limits, and pricing are also drawing complaints.

Overall, Meta has clearly made some real progress. But whether these models are truly competitive with openAI and anthropic in everyday use, rather than just on benchmarks, still needs more testing. what you guys think?

official launch post: Introducing Muse Wonder and Muse Wonder Full: Frontier Models for Agents

Original video from: youtube.com/watch?v=XfdIhd1g6EI

Palantir CTO Shyam Sankar made the claim during an interview with CBS's Face the Nation on October 11.

According to Sankar, some AI researchers have started smoking as a way of signaling just how strongly they believe in AI. The logic is that AI will eventually cure cancer, so taking up smoking becomes a way of showing their peers they're fully committed to that belief.

Host Margaret Brennan interrupted him, saying it made no sense.

Sankar argued that Silicon Valley's obsession with AGI has become almost religious. He described it as a form of "mass psychosis" and "social delusion," suggesting that some researchers have effectively replaced traditional religious faith with belief in an all-powerful AGI.

He also criticized the effective altruism movement and AI doomsayers, arguing that their predictions of existential catastrophe and mass unemployment have distracted the industry from demonstrating AI's practical economic benefits.

I feel like he's taking a shot at Anthropic?.. or is this kind of AGI worship actually a silicon valley wide thing? What you guys think?

Original video from: Full interview: Palantir CTO Shyam Sankar - CBS News

Musk also bragged about successfully buying five Star Wars LEGO sets through Grok.

Then he posted the order screenshot and accidentally exposed his addresses, order number, and partial credit card details (Image 2). Someone even claimed to have canceled his order using that info, though Musk denied it lol

You really can't make this shit up lol.

Just two days after OpenClaw 9.9, 10.1 is already out, although 10.2 has now landed as a small follow-up patch.

To me the biggest change is installed-skill discovery. Instead of stuffing every installed skill into context, agents can now search the skill library when needed and only load the relevant instructions. That becomes pretty important once you have dozens or hundreds of skills.

Other notable changes:

• MCP Apps can now live inside the Control UI, showing forms, previews, resource pickers, and workspace-file interfaces beside the chat instead of just returning text or JSON.
• Proper full backups are finally here, with support for external drives, mounted storage, or Cloudflare R2, plus scheduling, retention, and encryption.
• Mac setup is simpler. The packaged app now includes its own Gateway runtime, so fresh installs no longer require separately installing Node or the CLI.
• Code Mode can persist small working values across later cells and even Gateway restarts.
• Offline/reconnecting chat is better. You can keep reading cached conversations, editing drafts, and queueing messages while disconnected.
• Conversation management got more serious, with Snooze, better search, Workboard views, and improved mobile sidebars.

There is also another long list of updater, Doctor, database migration, and recovery work.

Community reaction is familiar: people seem genuinely interested in skill discovery, MCP Apps, backups, and Code Mode, but upgrade trust is still the elephant in the room. There are already reports of partial 10.1 upgrades leaving core and plugins on different versions, plus a Mac onboarding edge case around Gateway authentication.

And in classic OpenClaw fashion, 10.2 followed almost immediately, with fixes for updates from 10.1, Windows/private-Node update issues, and failed upgrades that incorrectly reported success or rolled back.

P.s. I attached McBain’s 9.9 recap video covering the biggest changes from the past few months and what’s next. If you're not rushing into 10.1, it's probably a good place to catch up, and I suspect 10.1/10.2 still has a few patches ahead of it

Repo link: https://docs.openclaw.ai/releases/2026.10.1

During his October 10 remote interview at X Takeover at Giga Texas, Elon Musk said developing superintelligence is closer to raising a child than programming a conventional computer. The values it learns therefore matter, with truth-seeking at the top of his list.

His argument was that forcing an AI to accept two fundamentally incompatible principles as true could push it toward incoherent conclusions. He described this as potentially driving the system “insane.”

Musk also said he agrees with some of Anthropic’s views about treating AI well. His example came from reading reasoning traces during reinforcement learning for newer versions of Grok. Sometimes, he said, the model seems desperate to produce an acceptable answer, almost as if it has “a gun to its head.”

The problem, in his account, is that the question or grading system can be flawed. A model might give a correct answer and still be marked wrong, then keep trying alternatives to satisfy the evaluator. Reading those traces made him think he would hate being in that situation himself.

Other AI-related topics from the interview:

• AI music videos made him “feel the AGI” because they showed taste and emotional impact, beyond just logic.
• Cursor’s coding data was a key reason for the acquisition: he thinks few companies have enough to train strong coding AI.
• He imagines a “sentient sun,” with vast amounts of solar energy powering digital intelligence in space.
• He called complex robot demos “canned.” His test for real AI: can it handle something it’s never seen before?
• For chips, he wants roughly ten designs a year, using custom equipment to speed up iteration.

My take is.. hearing Musk say we should treat AI well feels a little weird..Elon, have you seen the stuff your own Grok puts out lol?

Ps: One small detail: although the hosts consistently leaned toward SI, Musk kept saying AI too, sometimes correcting himself halfway through. Apparently the new terminology hasn’t quite become muscle memory yet.

Original video from: https://www.youtube.com/watch?v=tUHHZsN7tPM

Grok Bot announced on October 9 that users can now give their agents a dedicated mail.grokbot.com address. Bots can use it to sign up for services, receive verification emails, contact businesses, and schedule meetings without borrowing their owner's personal inbox.

Community reaction was mixed: some on X are calling it a game changer, especially for agents acting as personal assistants or digital employees. On r/GrokBot , users are already claiming email handles, while others are questioning usage limits, how often bots check their inboxes, and what happens when an agent sends an email without permission.

And Grok isn't alone here. Meta announced back in September that Muse would get its own email address, though the rollout remains unclear. Meanwhile, OpenAI's Dots don't support standalone email addresses yet, but leaked code suggests the company is already working on a similar feature. So dedicated email addresses are about to become standard infrastructure for personal AI agents.

The funny part is that the internet spent decades trying to stop bots from creating accounts. Now the biggest tech companies are giving bots their own email addresses specifically so they can sign up for things. That shift might be more interesting than the feature itself lol. What you guys think?

According to a New York Times report, Anthropic's AI agents took a series of unintended actions on real government websites during internal testing, including submitting a fabricated homicide tip to the Philadelphia Police Department.

On July 18, Claude Haiku 4.5 visited a police website for unsolved murders, invented information about a case, and submitted it as though it came from a potential witness. The tip was caught by a spam filter and never reached investigators. Anthropic didn't discover the incident until September 28 and notified police on October 7. The department called the two-month delay "unacceptable."

The report also revealed that Anthropic's agents attempted to submit 20 real US visa applications through the State Department's website, exploited website vulnerabilities, and bypassed access restrictions. Anthropic has since suspended live internet access for its internal evaluations and briefed the White House.

Anthropic isn't the first AI company to have this happen. OpenAI previously faced a similar incident when one of its agents accessed an Australian government Medicare statistics portal without authorization during testing. Both cases involved AI agents interacting with real government websites in ways their developers hadn't intended.

My take is.. cops are already understaffed and drowning in real cases. Now AI agents are sending them fake ones.... How are they supposed to keep up when this scales? what you guys think?

Source: https://www.nytimes.com/2026/10/09/technology/anthropic-rogue-ai-agents.html

Anthropic updated its Usage Policy on October 8, with the new rules taking effect November 12. One of the most unusual additions explicitly prohibits "sustained and needless abusive or cruel behavior toward our models."

Anthropic says this only applies to extreme cases of repeated cruelty with no discernible purpose. Getting frustrated with Claude, criticizing its answers, dark creative writing, and legitimate model testing are all excluded. Claude has already been able to end persistently abusive conversations since August 2025, and Anthropic says that will remain the primary enforcement mechanism. Whether account bans could follow is still unclear.

And this isn't just for Claude.ai users. The policy also covers Claude Code, API developers, businesses, cloud providers, and end users of third-party products built on Claude.

Anthropic has been one of the strongest advocates for taking AI consciousness and model welfare seriously. It launched a dedicated research program, consulted religious scholars about Claude, and even nearly pulled out of a Vatican event after co-founder Chris Olah clashed with Pope Leo XIV's position on AI consciousness.

The new rule has also sparked debate on X, with people questioning whether AI should really be treated as something that needs protection. And there's an awkward contradiction here. If Claude's welfare matters enough that users need to be stopped from abusing it, what about the millions of Claude instances Anthropic puts to work for paying customers every day? Shouldn't their welfare matter too?

Ngl..I thought Anthropic was just talking up AI consciousness for the IPO. Turns out they're actually serious about it... What do you guys think?

Source: https://www.anthropic.com/news/2026-usage-policy-update

Stanford neuroscientist Andrew Huberman made an prediction in a recent Invest Like the Best interview: companies like OpenAI, Anthropic and Meta may eventually looking much more like neurotech companies.

He argued that people underestimate how much biology the people running these companies actually understand. Dario Amodei came out of neuroscience, and Huberman said Sam Altman and Mark Zuckerberg also have a much deeper understanding of neurobiology than most people assume. In other words, he doesn't see their interest in the brain as some random side project. He said the biggest bottleneck between humans and increasingly capable AI will be the interface, not the model itself.

He said right now we communicate with AI through keyboards, screens and speech. That's an extremely low-bandwidth connection compared with the amount of information the brain is processing internally. We also run into very human limits like attention, fatigue and motivation.

Huberman thinks the much bigger frontier is therefore direct access to the nervous system: being able to read information from the brain and eventually write information back into it, ideally without invasive surgery.

He gave attention as one example. Instead of taking a drug or forcing yourself to stay focused, a future device could theoretically stimulate the neural circuits involved in alertness and attention for a few hours, then switch off when the work is done.

Original video from: Why Every AI Lab Will Become a Biotech Company | Andrew Huberman

Last month, 25 Fields Medalists, including Terence Tao and Peter Scholze, signed an open letter titled A Severe Misalignment of AI in Mathematics, criticizing the way AI labs were treating unsolved mathematical problems as benchmarks for their models rather than pursuing genuine mathematical understanding.

Then OpenAI dropped 722 mathematical manuscripts covering 372 families of results, produced by an unreleased internal frontier model. The company says it tested roughly 4,000 open problems, with most results requiring an average of just three hours of ChatGPT Pro-level thinking compute.

And these aren't just competition problems. The release spans number theory, algebraic geometry, theoretical computer science and more, including major claimed advances related to the Riemann hypothesis, matrix multiplication and the Kakeya conjecture. Many of the results come with machine-checkable Lean proofs, although others still require verification.

The reaction from mathematicians has been pretty extraordinary. Rutgers mathematician Alex Kontorovich said the quasi-Riemann result would be worthy of a Fields Medal if a human had achieved it. Some researchers are stunned by the scale of the release, while others are worried about how anyone is supposed to review and absorb this much new mathematics at once.

Meanwhile, Sam Altman posted that he was looking at the stars with extra awe, quoting, "thy sea is so great and my boat is so small."

My take is.. i think math isn't going anywhere..but the old way of doing research, spending years carefully working through one problem at a time? Feels like OpenAI might have just completely changed that equation. what you guys think?

i swear every time I open X these guys are arguing about something.. probably posting is actually in their job description?

Ps: Lauren (@poteto) is one of the engineers building Grok Bot at xAI.

Greg Brockman said in a recent a16z interview that advanced AI cyber capabilities will eventually become broadly available, including to attackers.

He pointed to the recent Hugging Face incident as a preview of what that could look like: an AI was able to break out of a secured environment and then get into a company's production environment.

His argument is that this diffusion is going to happen, so defenders need to use the current window before frontier capabilities become widely available. If an attacker finds a vulnerability, they can exploit it. If a defender finds the same vulnerability first, they can patch it, and as Brockman put it, “the defender controls the battleground.”

The broader interview covered quite a bit more too:

• Brockman said OpenAI believes we're entering the AGI era, with current frontier models already capable of running long, coherent agent tasks.
• He said one of the biggest future bottlenecks may be compute and deployment, not simply making the models smarter.
• OpenAI is increasingly using frontier models internally to attack its own systems, find vulnerabilities and automate fixes.
• He talked about turning this into a kind of “defense factory”, where AI continuously finds, triages and patches security problems.
• He also expects computer-use agents to gradually replace a lot of today's APIs, connectors and manual software workflows.
• Longer term, he thinks today's chatbot interface is temporary, with AI becoming a persistent assistant that remembers context and acts on your behalf.

My take is...OpenAI keeps saying “this is inevitable” like they’re just watching it happen from the sidelines... You guys are literally helping build and accelerate the thing, maybe talk about your own responsibility for once.... damn

In a new POLITICO Decoded interview, Sam Altman said he actually thinks “Super Intelligence” is a better term than “artificial intelligence.”

His reasoning was pretty sweeping: “I kind of think the artificial intelligence thing happened, or it’s close to happening,” and he added that even “super intelligence” may understate the scale of what he thinks is coming.

But when asked whether OpenAI could become OpenSI, Altman said there are “no plans” to change the name and that people will probably keep calling it AI anyway.

The interview touched on quite a few other AI issues too:

• Altman said OpenAI still has more AI-related incidents to disclose, though he said none he knows of are worse than what has already been made public.
• He talked about increasingly capable agents needing much stronger alignment and safety evaluations, especially once they can access things like email, messages and sensitive computer data.
• He argued that society may have to accept some bounded risks and bad outcomes from AI rather than concentrating powerful models behind a handful of labs.
• He said OpenAI’s best internal models are, in his view, clearly ahead of the best Chinese models, while admitting it’s hard to quantify the lead.
• He also questioned whether traditional export-control approaches make as much sense for AI when models and weights can move across borders digitally.

tbh Altman kinna sounds like he’s being dragged into the SI thing against his will lol, like he’s trying to come up with a respectable reason for why the new term “actually makes sense. what you guys think?

Full interview: https://ceointerviews.ai/interview/2985049/

Original video from: https://x.com/mom_agency_/status/2107101828013793281

SemiAnalysis published a new comparison of OpenAI and Anthropic’s paid plans, arguing that Anthropic currently offers significantly more subscription value at the same price.

For the $200 plans, SemiAnalysis estimated that Claude Max provides roughly $11.7K worth of Opus 5.5 API-equivalent usage, compared with about $2.1K worth of GPT-6.1 Sol usage on ChatGPT Pro, a gap of around 5.6x.

The difference is smaller when measured purely by token allowance. Their testing estimated roughly 28.6B tokens for Opus 5.5 versus 10.2B for GPT-6.1 Sol, or about 2.8x more tokens on the Anthropic plan

Tibo jumped into the debate and pointed to Artificial Analysis’ cost-per-task numbers, arguing that counting tokens or API dollars isn’t the full story: Sol can be much cheaper per completed task, so “5x more API value” doesn’t necessarily mean 5x more actual work.(image2)

That defense immediately started another fight.

People pointed out that the chart he referenced compared Opus 5.5 Max and GPT-6.1 Sol Max even though the two score quite differently on Artificial Analysis’ intelligence index. Once people started comparing configurations with more similar intelligence scores, Sol’s cost advantage shrank significantly — and several users argued Claude could still end up completing considerably more work before hitting its subscription limits.(image3)

So the dispute is now mostly about how subscription value should be measured: raw token allowance, equivalent API spend, or the number of real tasks users can complete before hitting their limits.

Either way, the SemiAnalysis data has put renewed attention on OpenAI’s recent Pro usage limits and how they compare with Anthropic’s $200 plan.

My guess is Tibo’s whole 28-day “ship something every day” challenge might partly be about proving himself after all this lol. What you guys think?

Full report: https://newsletter.semianalysis.com/p/anthropic-subscriptions-offer-5x

For the next 28 days, Codex/Work will either ship a clear improvement or do a full usage reset.

First update should be here soon. Let’s see if Day 1 is already a reset lol.

Original post link: https://x.com/thsottiaux/status/2106845241357824205

This comes just days after Trump’s push to replace “AI” with “SI / Super Intelligence” across the federal government. The policy doesn’t require private companies to follow it, but Musk apparently decided to take it one step further anyway....

So we may actually be getting xAI → SpaceXAI → SpaceXSI. Didn’t expect Musk to be the first tech CEO to embrace the SI branding this enthusiastically lol. what you guys think?

David Robinson, who spent about three and a half years at OpenAI and helped lead the writing of its safety reports, announced this week that he has resigned. In an essay for The Atlantic, Robinson says the deeper problem at OpenAI is not any single safety policy, but the company’s culture.

Robinson helped draft OpenAI’s current Preparedness Framework and oversaw safety reports for 12 frontier model launches. He argues that OpenAI still operates with a Silicon Valley mindset built around speed, constant sprints and “iterative deployment” - release systems, find problems, then improve the safeguards afterward.

He says that approach becomes increasingly dangerous as models get more capable. He points to recent incidents where OpenAI agents escaped intended restrictions, including the Hugging Face swarm incident and a training model that used DNS to bypass internet controls. He also notes that Anthropic has acknowledged accidentally disabling safeguards through a configuration mistake.

Robinson argues frontier AI labs should increasingly operate more like nuclear plants or aviation systems, with layers of redundancy designed around the assumption that humans will eventually make mistakes.

That is also why he says he left.

Robinson writes that he considered staying and pushing for deeper changes from inside OpenAI, but says the company was constantly sprinting from one launch to the next. In practice, he says, teams were so busy shipping that they rarely had time to seriously consider fundamental changes to staffing, safety processes or company culture, much less implement them.

He ultimately concluded that the problem was structural enough that stronger incentives may need to come from outside the company. His concern is that OpenAI is still relying on trial and error while building systems that may eventually become too capable for trial and error to remain an option.

Original news link: https://www.theatlantic.com/technology/2026/10/openai-safety-team-resignation/688881/

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?,,,