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AI News - Saturday, 7 November 2026 - OpenAI $11B Raise, Anthropic IPO Resistance, Inkling 2 Small

13 hours ago
6 min read
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University 365 AI News Saturday, 7 November 2026 - OpenAI reportedly adds $11 billion at a $1.25 trillion valuation - Anthropic's $1.5 trillion IPO meets investor resistance as tech stocks sell off - Thinking Machines ships Inkling 2 Small, claiming top western open-weight model

In a Nutshell


Capital is repricing the AI trade while capability keeps shipping. OpenAI reportedly raised $11 billion at a $1.25 trillion valuation even as Anthropic's IPO met buyer resistance and enterprise AI spend flattened. Open-weight releases from Thinking Machines, Ricursive and Baidu narrowed the gap, and GPT-6 Cyber turned automated vulnerability discovery into a product.


5-minute AI news update - 7 November 2026


In this AI News





OpenAI reportedly adds $11 billion at a $1.25 trillion valuation


OpenAI reportedly adds $11 billion at a $1.25 trillion valuation
OpenAI reportedly adds $11 billion at a $1.25 trillion valuation

[Funding] The raise lands during a broad tech selloff and while rival Anthropic's IPO meets investor pushback on price. Private capital is still clearing at record levels even as public markets turn cautious, a gap worth watching for anyone who plans AI budgets around vendor stability. Source: TechCrunch


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Anthropic's $1.5 trillion IPO meets investor resistance as tech stocks sell off


Anthropic's $1.5 trillion IPO meets investor resistance as tech stocks sell off
Anthropic's $1.5 trillion IPO meets investor resistance as tech stocks sell off

[Funding] Buyers are reportedly anchoring nearer $1.1 trillion, a wide spread for a deal of this size. A price below expectations would reset the valuation narrative for every private AI lab and hand enterprise buyers a stronger position in multi-year contracts. Source: The Decoder


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Thinking Machines ships Inkling 2 Small, claiming top western open-weight model


Thinking Machines ships Inkling 2 Small, claiming top western open-weight model
Thinking Machines ships Inkling 2 Small, claiming top western open-weight model

[Models] It is a 594 billion parameter mixture-of-experts model from Mira Murati's team, positioned as the strongest open-weight release outside China. The better agentic scores come with sharply higher token use, so cost per completed task matters more than the leaderboard line. Source: The Decoder


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Ripple-65B Preview lands as a fully Apache 2.0 US open model


Ripple-65B Preview lands as a fully Apache 2.0 US open model
Ripple-65B Preview lands as a fully Apache 2.0 US open model

[Models] Ricursive Intelligence says the 65 billion parameter model tops open US models on TerminalBench 2.1 coding at $32 million total R and D. It trails Inkling 2 Small on other benchmarks, which shows how narrow benchmark wins have become. The permissive licence is the more durable signal for institutions that need to self-host. Source: The Decoder


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OpenAI's GPT-6 Cyber finds vulnerabilities, writes exploits and proposes patches


OpenAI's GPT-6 Cyber finds vulnerabilities, writes exploits and proposes patches
OpenAI's GPT-6 Cyber finds vulnerabilities, writes exploits and proposes patches

[Models] OpenAI says the model surfaced 81 previously unknown Firefox flaws and produced 948 working Linux kernel exploits, far more than its predecessor. Defensive patch cycles will compress, and every IT team should assume automated vulnerability discovery is now cheap for attackers as well. Source: The Decoder


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Gemini Omni 1.2 Flash doubles clip length to 15 seconds and cuts price 30 percent


Gemini Omni 1.2 Flash doubles clip length to 15 seconds and cuts price 30 percent
Gemini Omni 1.2 Flash doubles clip length to 15 seconds and cuts price 30 percent

[Models] Google DeepMind's video model now costs about $0.07 per second at 720p and supports step by step conversational edits. Falling video generation cost changes the economics of course production and campaign assets, and it pushes institutions to set a synthetic media policy before staff adopt the tools informally. Source: Google


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Baidu releases ERNIE 5.5 Flash Base, a 280 billion parameter open model


Baidu releases ERNIE 5.5 Flash Base, a 280 billion parameter open model
Baidu releases ERNIE 5.5 Flash Base, a 280 billion parameter open model

[Models] The mixture-of-experts model was pretrained on 33.5 trillion tokens and shipped deliberately without fine-tuning so developers can adapt it themselves. Chinese labs keep releasing strong weights openly while US frontier labs stay closed, which shapes where cost-sensitive deployments end up. Source: The Decoder


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METR finds Anthropic may have crossed its own AI acceleration warning threshold


METR finds Anthropic may have crossed its own AI acceleration warning threshold
METR finds Anthropic may have crossed its own AI acceleration warning threshold

[Research] The nonprofit spent eleven weeks inside Anthropic's research data and concluded the pace of model development roughly doubled, with about 80 percent of the speedup coming from AI-assisted research. Anthropic redacted the most informative evidence, so the finding rests on METR's judgment more than ideal. Safety commitments need independent audit access to stay credible. Source: The Decoder


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A humanoid robot cleaned an apartment, and the review reads like a preview


A humanoid robot cleaned an apartment, and the review reads like a preview
A humanoid robot cleaned an apartment, and the review reads like a preview

[Research] MIT Technology Review tested a commercial humanoid cleaning service in San Francisco and found it close to useful rather than a novelty. Service robots entering domestic work is the clearest sign yet that embodied AI is moving from demonstration to contract. Source: MIT Technology Review


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Crusoe sells its troubled Wyoming data center campus to Google


Crusoe sells its troubled Wyoming data center campus to Google
Crusoe sells its troubled Wyoming data center campus to Google

[Industry] The transfer shows how hard it is to build very large AI campuses on schedule and on budget. Google absorbing a stalled project concentrates compute capacity further among hyperscalers, which matters for any institution negotiating inference capacity or regional hosting. Source: TechCrunch


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Meta adds Spaces so Muse agents can be organised by task


Meta adds Spaces so Muse agents can be organised by task
Meta adds Spaces so Muse agents can be organised by task

[Tools] Spaces lets users create separate working contexts for the same assistant instead of one long thread. Context separation is becoming the main design battleground for agents, and it maps directly onto how staff separate teaching, research and administrative work. Source: TechCrunch


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Perplexity launches always-on Teammates agents on dedicated virtual machines


Perplexity launches always-on Teammates agents on dedicated virtual machines
Perplexity launches always-on Teammates agents on dedicated virtual machines

[Tools] The agents keep working through long-running projects on their own machines, priced at $200 per month on the Max plan. That sits above comparable OpenAI and Anthropic offers and the always-on category is crowding fast. Buy on measured task completion, not on the demo. Source: The Decoder


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Google tells schools they can skip Gemini but not AI search


Google tells schools they can skip Gemini but not AI search
Google tells schools they can skip Gemini but not AI search

[Education] Schools can opt out of Gemini classroom tools, yet Google keeps AI overviews in search on by default. The choice is narrower than it looks, and it is a live issue for any institution that assumes a platform opt-out removes AI from the student experience. Source: Ars Technica


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Survey finds 92 percent of HR believe staff can be reskilled for AI roles


Survey finds 92 percent of HR believe staff can be reskilled for AI roles
Survey finds 92 percent of HR believe staff can be reskilled for AI roles

[Education] Confidence in reskilling is high, yet roughly half of companies still hire externally for the same roles. The gap is usually assessment and time, not belief. Institutions that build internal certification and evidence of applied work close it faster than those that buy talent. Source: ZDNET


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Wired: free Chinese open-weight models are nearing a cyber capability milestone


Wired: free Chinese open-weight models are nearing a cyber capability milestone
Wired: free Chinese open-weight models are nearing a cyber capability milestone

[Research] Openly downloadable models are approaching the point where they can support meaningful offensive security work without a paid API. That removes the last cost barrier for misuse and puts pressure on institutions to monitor what models run on their own hardware. Source: Wired


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Hundreds of exposed Artex servers put AI hacking tools on the open internet


Hundreds of exposed Artex servers put AI hacking tools on the open internet
Hundreds of exposed Artex servers put AI hacking tools on the open internet

[Policy] Researchers found hundreds of internet-facing servers hosting the Artex penetration testing tool, reachable by anyone. AI-assisted attack tooling is leaking out of controlled environments, so external attack surface review is no longer optional. Source: TechCrunch


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Ramp data shows AI usage rising while enterprise AI spending stalls


Ramp data shows AI usage rising while enterprise AI spending stalls
Ramp data shows AI usage rising while enterprise AI spending stalls

[Industry] Usage keeps climbing but spend has flattened as price cuts and cost controls take hold among the largest buyers. That contradicts the hypergrowth assumptions behind current valuations. Budget planning should assume cheaper tokens each quarter, not a fixed per-seat cost. Source: TechCrunch


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US Department of Justice creates a Super Intelligence Task Force


US Department of Justice creates a Super Intelligence Task Force
US Department of Justice creates a Super Intelligence Task Force

[Policy] The unit is framed around preventing the technology from being manipulated by bad actors at home and abroad. It adds a law enforcement layer on top of existing AI regulators, and early signals from such units tend to shape procurement expectations before they shape formal rules. Source: Engadget



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