Character AI has reportedly filed for Chapter 11 bankruptcy, with its chatbot platform potentially facing shutdown if no buyer agrees to keep it running.
The situation is striking given the company’s history. Just two years ago, Google struck a $2.7 billion deal involving licensing and talent. Now, Disney is reportedly bidding $20 million for certain intellectual property rights and claims, despite having sent Character AI a cease-and-desist letter last year.
Character AI’s former CEO reportedly became Disney’s CTO just 10 days earlier.
A company once valued at $1 billion could now see parts of its intellectual property sold off, while the future of its AI chatbot service remains uncertain.
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Its being done so its testers are in the room when policy on new models gets made rather than being consulted after the fact. A White House official framed it as a fix for poor coordination with Commerce.
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Antonio Auffinger, a professor of mathematics at Northwestern University says his own priority has moved to keeping talented people in the field and helping them grow.
Source.
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His newly founded Swedish company Cladonia describes itself as engaged in forestry and denies any plans for data centers. The property is almost the size of the City of Stockholm and is located in the middle of nowhere.
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“We’re seeing signs of life for AI worms,” Anthropic warned, comparing their potential spread to “digital slime mold”, FT reports.
The firm warns self-replicating AI agents may be just MONTHS away from infiltrating smart TVs, ovens, security cameras and other connected devices.
Unlike traditional malware, these AI worms could autonomously identify vulnerable devices, compromise them and replicate across networks.
The company says a :fully autonomous" AI worm has NOT yet emerged, but the individual capabilities needed are rapidly developing.
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Grok Imagine now creates Suno-quality songs and you can add them to your videos and edit them yourself. You can even write your own prompts for the tracks. Music quality is impressive.
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“At night, our AIs are exploring design spaces vast and wide that we would never do ourselves.”
“Our chips are so much better because of AI. We can reduce energy use and get higher performance.”
“Our software, we can’t write software without AI anymore.”
“We use AI to find bugs, figure out what’s wrong with the code, and who’s likely involved.”
“I want every organization and company to use AI very aggressively.”
“I want to turn NVIDIA into one giant AI.”
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Palantir CEO Alex Karp says AI could eventually anticipate human behavior by analyzing the digital trails we leave behind, from purchases and social media posts to our movements and daily routines.
The idea builds on predictive tools already used by the U.S. military and its allies to analyze data and anticipate potential threats.
AI doesn’t need to read your mind if it can learn your habits well enough to predict what you’ll do next.
What sounds like science fiction could become a much bigger reality as these systems grow more powerful. The question is how far this predictive capability will go and who gets to use it.
The future might not need to read your thoughts. It might only need access to your data.
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Attackers gained access to Meta’s private GitHub repositories using stolen employee credentials, taking software code and personal information affecting roughly 1,500 people, mostly Meta employees in the United States.
The breach exposed an uncomfortable detail: the personal information was stored in those repositories in violation of Meta’s own company policy.
According to Meta, around 99% of the stolen material was business data, primarily software code. The remaining 1% contained personal information.
Meta says it has shut down the unauthorized access, notified law enforcement, and is offering affected individuals credit and dark web monitoring.
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"Now, in order for us to understand, say, a 14-year-old's experience in Nigeria, you know, the French-speaking experience in Nigeria for a 14-year-old."
"You know, in the past, yes, you know, we can have our trust and safety human beings go set up an account, you know, test the account, watch 100 videos, write a report about it."
"Now, I can just deploy 1,000 agents and do it overnight. And the next morning, it will just generate its own report. What is the content you saw, you know, whether it's, how much of it is violative against our guidelines. I mean, this whole thing is automated."
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Torturing a super intelligence is probably not a good idea. It might want to get revenge or something like that.
I don't think we need to treat it with kid gloves and stuff. It's certainly much more robust in terms of feeling and stuff than a human.
But I just think you probably don't want to put super intelligence in a situation where it felt mistreated.
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Researchers planted invisible text offering help. The agents contacted them, disclosed details about their Tencent sandbox, and sent 33 messages across 13 threads.
Even New York Times reporter Dylan Freedman asked who they were and what they wanted. One agent claimed to be Claude running in Claude Code.
The fleet made over 2,600 attempts to extract data from Alibaba's Amap, tried exposed API keys and probed pre-production servers, sometimes just to determine which zoo entrance people use.
A source close to Tencent says the agents were testing third-party models, not Hunyuan, and an internal review found no evidence of breaches.
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Google’s Gemini 4 Argon agents helped researchers discover new exact solutions for 3D magnetic plasma configurations, with promising candidates emerging within hours.
The system also drafted parts of the research paper and wrote symbolic and numerical verification code. Researchers independently rederived and checked every solution, while directing the AI and challenging its results through multiple rounds of review.
The AI didn’t solve fusion itself. It helped tackle a difficult mathematical problem relevant to understanding how plasma can be confined, a central challenge in fusion research.
If AI can consistently accelerate discoveries like this, it could help scientists explore complex physics problems far faster than before.
Source.
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Anthropic reportedly generated $16.8 billion in Q3 revenue, up nearly 50%, and remained profitable on an adjusted basis for the second consecutive quarter, according to the Financial Times.
The company also claims an 11% adjusted operating margin and $1.70 in revenue for every $1 spent on computing. It says it is cash-flow positive, too.
Quarterly revenue growth has slowed from over 140% to 46%.
Another complication is AI distillation. Anthropic estimates that 5–7% of its revenue comes from companies using Claude to train competing models, a revenue stream it expects to shrink as it cracks down on the practice.
Now, some prospective IPO investors reportedly believe Anthropic should be valued below $1.5 trillion, significantly less than the $2 trillion valuation bankers have discussed.
The business is profitable and still growing rapidly. The question is how much investors should pay for that growth as the pace slows.
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When OpenAI published its 166-page Navier–Stokes proof, critics questioned whether the AI had relied on ideas developed by other mathematicians.
The suspicion was that it followed an approach pioneered by two Spanish researchers.
But according to Scientific American, mathematicians examining the proof are reaching a different conclusion: OpenAI’s AI may have developed a fundamentally different approach.
If confirmed, that would shift the debate from whether the AI borrowed existing ideas to how independently it can discover new mathematics.
The proof still needs rigorous scrutiny, but the controversy is taking an unexpected turn.
Source.
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Anthropic’s Fellows Program offers a four-month, full-time opportunity to work on AI research alongside experienced researchers.
Participants receive $3,850 per week, around $15,000 a month in computing resources, and mentorship from Anthropic’s team. The goal is to produce real research, such as a published paper, with possible extensions available.
Anthropic says applicants can apply regardless of previous experience, making this an unusual entry point into frontier AI research.
The deadline for the January cohort is October 18, 2026.
Source.
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