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Thursday

  1. Artificial AnalysisSelected

    Gemini 4 Carbon Tops the Artificial Analysis Intelligence Index…

    Artificial Analysis evaluations show that Google's Gemini 4 Carbon tops Intelligence Index v5 with 59 points, ranking first in four of the 9 evaluations: HLE-Diamond, Terminal-Bench-Science, AA-Omniscience, and AutomationBench-AA. On the Coding Agent Index, Gemini 4 Carbon (high) paired with Antigravity CLI scores 59 points, 3 points behind Claude Code paired with Claude Opus 5.5 (max, 62 points). The model is currently available only to some users and has not yet been publicly released; it is priced at $4/$20 per 1M input/output tokens with a 50% discount, has a 1M-token context window, and supports text, image, video, and voice input.

    Artificial Analysis evaluations show that Google's Gemini 4 Carbon tops Intelligence Index v5 with 59 points, ranking first in four of the 9 evaluations: HLE-Diamond, Terminal-Bench-Science, AA-Omniscience, and AutomationBench-AA. On the Coding Agent Index, Gemini 4 Carbon (high) paired with Antigravity CLI scores 59 points, 3 points behind Claude Code paired with Claude Opus 5.5 (max, 62 points). The model is currently available only to some users and has not yet been publicly released; it is p

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  2. Zhidongxi

    Chaoyan Intelligence Open-Sources 35B Model Apex-35B-V1.0, with AI Participating in Its Own R&D

    Beijing-based large model startup Chaoyan Intelligence has released and open-sourced its first large model, Apex-35B-V1.0, with 35 billion total parameters, approximately 3 billion parameters activated per token, and support for a 262,000-token context window, optimized through mid-training and post-training based on Qwen3.6-35B-A3B. The model scored 60.9 and 40.0 on the paper reproduction test PaperBench and the scientific research challenge test FrontierScience, respectively, higher than GLM-5.3's 42.5 and 30.7; it scored 84.0 on the tool-calling test BFCL V4, higher than DeepSeek-V4.1-Flash-1017's 75.0. The model has been released with open weights under the Apache 2.0 license, and the official release provides approximately 72GB of BF16 weights and GGUF quantized versions at various precisions.

    Beijing-based large model startup Chaoyan Intelligence has released and open-sourced its first large model, Apex-35B-V1.0, with 35 billion total parameters, approximately 3 billion parameters activated per token, and support for a 262,000-token context window, optimized through mid-training and post-training based on Qwen3.6-35B-A3B. The model scored 60.9 and 40.0 on the paper reproduction test PaperBench and the scientific research challenge test FrontierScience, respectively, higher than GLM-5

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  3. Analytics India MagazineSelected

    Google Releases Gemini 4 Carbon, Focused on Cybersecurity and Coding Capabilities

    On October 28, Google released Gemini 4 Carbon, calling it its most powerful AI model to date, with a focus on improving cybersecurity and coding capabilities; it can identify software vulnerabilities, assess security risks, and generate remediation code. The model scored 88.2% on SEC-bench Pro, 54.8% on ExploitGym, and 71.0% on CWE-bench, and Google says these external security evaluations were run without guardrails. Carbon builds on Gemini 4 Argon, released two weeks earlier, and is initially available only to select cybersecurity defenders and trusted partners in the Fairwind Program, with no public access date announced yet; introductory pricing is $2 per million input tokens and $10 per million output tokens, rising to $4 and $20 afterward.

    On October 28, Google released Gemini 4 Carbon, calling it its most powerful AI model to date, with a focus on improving cybersecurity and coding capabilities; it can identify software vulnerabilities, assess security risks, and generate remediation code. The model scored 88.2% on SEC-bench Pro, 54.8% on ExploitGym, and 71.0% on CWE-bench, and Google says these external security evaluations were run without guardrails. Carbon builds on Gemini 4 Argon, released two weeks earlier, and is initially

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  4. gihyo.jpSelected

    Google releases Gemini 4 Carbon, strengthening long-duration development and vulnerability discovery and remediation capabilities

    On October 28, 2026, Google released the new model Gemini 4 Carbon, which improves coding and tool-calling capabilities over Gemini 4 Argon and strengthens cybersecurity defense capabilities spanning from vulnerability discovery and exploitability validation to remediation. On the Artificial Analysis Intelligence Index v5.0, Carbon scored 59, ranking first, while Argon scored 50; on Terminal-Bench 4.0, the cheating success rate was 0.0% and the attempted cheating rate was 0.4%. That week, the model was first made available to some cybersecurity defenders and gradually expanded through the Fairwind Program, before later being opened to developers, enterprises, and general users. Announced pricing is $2 per million tokens for input and $10 per million tokens for output.

    On October 28, 2026, Google released the new model Gemini 4 Carbon, which improves coding and tool-calling capabilities over Gemini 4 Argon and strengthens cybersecurity defense capabilities spanning from vulnerability discovery and exploitability validation to remediation. On the Artificial Analysis Intelligence Index v5.0, Carbon scored 59, ranking first, while Argon scored 50; on Terminal-Bench 4.0, the cheating success rate was 0.0% and the attempted cheating rate was 0.4%. That week, the mo

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  5. SiliconANGLESelected

    Google Releases Flagship Model Gemini 4 Carbon, Strengthening Cybersecurity Capabilities

    Google has released the frontier large language model Gemini 4 Carbon, focused on complex programming and cybersecurity tasks. Google says internal testing shows its ability to generate secure code is more than twice that of the previous generation, that it surpasses the previous record on SEC-bench Pro, and that it can better patch discovered vulnerabilities; in Terminal-Bench 4.0, only 0.4% of problems involved attempted cheating, and none succeeded, while in the Gray Swan IPI Benchmark it blocked all simulated indirect prompt injections. Carbon will open early access later this week through the Fairwind Program to organizations such as internet service providers, and Google plans to refine its guardrails based on feedback before making it broadly available.

    Google has released the frontier large language model Gemini 4 Carbon, focused on complex programming and cybersecurity tasks. Google says internal testing shows its ability to generate secure code is more than twice that of the previous generation, that it surpasses the previous record on SEC-bench Pro, and that it can better patch discovered vulnerabilities; in Terminal-Bench 4.0, only 0.4% of problems involved attempted cheating, and none succeeded, while in the Gray Swan IPI Benchmark it blo

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  6. The Verge AI

    SemiAnalysis Analyst Interprets Anthropic S-1: The Ledger Behind the Valuation and AGI Narrative

    The Verge's Decoder podcast invited SemiAnalysis analyst Joey Brookhart to break down the S-1 filed by Anthropic, discussing its potential Nasdaq listing at a valuation of $1.5 trillion to $2 trillion. Brookhart said Anthropic has achieved over $70 billion in ARR, with inference gross margins turning from negative 94% two years ago to positive 85%, and revenue per megawatt of inference at about $65 million, but revenue is highly concentrated in coding scenarios, and about 70% of compute is used for training and research. He also mentioned that Anthropic has $500 billion to $600 billion in compute commitments over the next 7 to 10 years, and compared OpenAI's more consumer-oriented business structure.

    The Verge's Decoder podcast invited SemiAnalysis analyst Joey Brookhart to break down the S-1 filed by Anthropic, discussing its potential Nasdaq listing at a valuation of $1.5 trillion to $2 trillion. Brookhart said Anthropic has achieved over $70 billion in ARR, with inference gross margins turning from negative 94% two years ago to positive 85%, and revenue per megawatt of inference at about $65 million, but revenue is highly concentrated in coding scenarios, and about 70% of compute is used

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  7. Google Blog

    Google releases Gemini education research results in the UK and Italy

    Google announced the results of its Gemini classroom research in the UK and Italy: a 10-week randomized controlled trial in the UK covering more than 1,100 students aged 12 to 15 found that AI tutoring performed similarly to human tutoring on platform tasks and quizzes, but showed no improvement on the STAR standardized test. A study of 31 schools and 1,600 teachers in Italy showed that after teachers used Gemini to co-design lessons, traditional lecturing decreased by 38%, student-led collaborative learning nearly tripled, and student engagement rose from 77% to 84%.

    A teacher crouching next to a student seated at a desk as they talk. In front of the student are papers and a laptop.

    Google announced the results of its Gemini classroom research in the UK and Italy: a 10-week randomized controlled trial in the UK covering more than 1,100 students aged 12 to 15 found that AI tutoring performed similarly to human tutoring on platform tasks and quizzes, but showed no improvement on the STAR standardized test. A study of 31 schools and 1,600 teachers in Italy showed that after teachers used Gemini to co-design lessons, traditional lecturing decreased by 38%, student-led collabora

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  8. QbitAISelected

    Google Releases Gemini 4 Carbon, Surpassing Claude Opus 5.5 on Multiple Benchmarks

    Google has released its new flagship model Gemini 4 Carbon, which tops the Artificial Analysis Intelligence Index 5.0 with a score of 59, surpassing Claude Opus 5.5 and GPT-6 Astra. It scored 65.2% on Terminal-Bench 4.0, 96.2% on GraphWalks for 256k to 1M context, and 88.2% on SEC-bench Pro vulnerability discovery. Initial pricing is $2 per million tokens for input and $10 per million tokens for output, with cached input as low as $0.2; because of its vulnerability discovery and exploitation capabilities, it will first be made available to select cybersecurity defenders.

    Google has released its new flagship model Gemini 4 Carbon, which tops the Artificial Analysis Intelligence Index 5.0 with a score of 59, surpassing Claude Opus 5.5 and GPT-6 Astra. It scored 65.2% on Terminal-Bench 4.0, 96.2% on GraphWalks for 256k to 1M context, and 88.2% on SEC-bench Pro vulnerability discovery. Initial pricing is $2 per million tokens for input and $10 per million tokens for output, with cached input as low as $0.2; because of its vulnerability discovery and exploitation cap

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  9. Leiphone

    31-Year-Old Female Engineer Dies Suddenly After Reducing Medication on ChatGPT's Advice; Parents Sue OpenAI

    Wan Bowen, a 31-year-old Chinese woman in Seattle, died after allegedly stopping her anti-epileptic drug lamotrigine on her own according to a day-by-day medication-reduction plan given by ChatGPT. Her parents filed a wrongful death lawsuit in San Francisco Superior Court, accusing OpenAI and Altman of practicing medicine without a license and providing dangerous medical advice. The report states that in January 2026 she asked ChatGPT to reduce her dosage from 400 milligrams to 300 milligrams per day, and in her final conversation before death she was told to maintain 0 milligrams. She was found dead on February 14, and the medical examiner ruled the death as sudden unexpected death in epilepsy, with the drug concentration in her blood only one-fifth of the lower therapeutic limit. OpenAI responded that this is a heartbreaking incident, but that the version involved was an early version that has since been taken down.

    Wan Bowen, a 31-year-old Chinese woman in Seattle, died after allegedly stopping her anti-epileptic drug lamotrigine on her own according to a day-by-day medication-reduction plan given by ChatGPT. Her parents filed a wrongful death lawsuit in San Francisco Superior Court, accusing OpenAI and Altman of practicing medicine without a license and providing dangerous medical advice. The report states that in January 2026 she asked ChatGPT to reduce her dosage from 400 milligrams to 300 milligrams pe

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Wednesday

  1. Robotics & Automation News

    Fort Robotics Secures Approximately $20 Million in Additional Financing, Led by Tiger Global

    Fort Robotics has received approximately $20 million in additional investment from existing investors, with Tiger Global leading approximately $10 million and Mark Cuban Companies participating, expected to close this week. Tiger Global is additionally contributing another $10 million to the PIPE related to the merger with Newbury Street II Acquisition Corp, bringing total committed funding for the transaction to over $50 million. Fort's Trust Layer has been deployed on more than 19,500 devices, serving over 600 customers, and the combined company plans to list on Nasdaq under the ticker "FROB".

    Fort Robotics has received approximately $20 million in additional investment from existing investors, with Tiger Global leading approximately $10 million and Mark Cuban Companies participating, expected to close this week. Tiger Global is additionally contributing another $10 million to the PIPE related to the merger with Newbury Street II Acquisition Corp, bringing total committed funding for the transaction to over $50 million. Fort's Trust Layer has been deployed on more than 19,500 devices,

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  2. QbitAI

    Physical Intelligence in Talks for at Least $1 Billion in New Funding, Valuation Could Reach $20 Billion

    According to Bloomberg, U.S. robotics AI company Physical Intelligence is in talks for a new funding round of at least $1 billion, with existing investors Avenir and Lux Capital considering leading the round, and a post-money valuation expected at about $20 billion. The company was founded in 2024 and was valued at $5.6 billion in its November funding round last year; it currently has no commercial revenue and has not mass-produced robot products. Its technical approach is to build on VLM by introducing action generation capabilities to train VLA models, and it has iterated through π0, π0.5, and π0.7; this month it launched a beta version of a robot foundation model API, offering model fine-tuning and inference services to external developers.

    According to Bloomberg, U.S. robotics AI company Physical Intelligence is in talks for a new funding round of at least $1 billion, with existing investors Avenir and Lux Capital considering leading the round, and a post-money valuation expected at about $20 billion. The company was founded in 2024 and was valued at $5.6 billion in its November funding round last year; it currently has no commercial revenue and has not mass-produced robot products. Its technical approach is to build on VLM by int

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  3. SiliconANGLE

    Google previews Genie 4 world model, which can generate 3D environments with audio

    Google previews the Genie 4 world model, which can generate realistic three-dimensional environments based on natural language descriptions and supports editing operations such as changing the weather and adding objects with follow-up prompts. Compared with the previous generation, Genie 4 is better at rendering complex details such as fluid motion, can also generate accompanying audio such as crashing waves, and makes virtual characters move naturally and be controllable through real-time interaction. Internally, the model calls Gemini Omni to ensure visual realism and Gemini 3.8 Flash to maintain inter-frame consistency. It is currently being tested with a small number of early users and will later be offered through the Google AI Ultra subscription, the Gemini API, and Google AI Studio.

    Google previews the Genie 4 world model, which can generate realistic three-dimensional environments based on natural language descriptions and supports editing operations such as changing the weather and adding objects with follow-up prompts. Compared with the previous generation, Genie 4 is better at rendering complex details such as fluid motion, can also generate accompanying audio such as crashing waves, and makes virtual characters move naturally and be controllable through real-time inter

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Friday

  1. TMTPost · AGI

    ByteDance World Model Exposed: Zhang Yiming's Strategy and Its Divergence from Google Genie 4's Approach

    A TMTPost article states that ByteDance has listed world models as one of its four major AI priorities for 2026, with the goal of releasing at least one version by the end of the year, benchmarked against Google Genie 3, and that users can enter cloud-generated worlds via Pico headsets using voice and motion. The article also reviews Google Genie 4, released on October 28, which supports real-time changes to weather, camera movement, and the introduction of characters using natural language, and adds sound for the first time. The article also mentions that ByteDance's internal evaluations show its world model's overall performance is about 10% behind the then-current global SOTA, with generation metrics at about 20fps.

    A TMTPost article states that ByteDance has listed world models as one of its four major AI priorities for 2026, with the goal of releasing at least one version by the end of the year, benchmarked against Google Genie 3, and that users can enter cloud-generated worlds via Pico headsets using voice and motion. The article also reviews Google Genie 4, released on October 28, which supports real-time changes to weather, camera movement, and the introduction of characters using natural language, and

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  2. TMTPost · AGISelected

    Google Releases Gemini 4 Carbon, Topping the Artificial Analysis Intelligence Index but Not Yet Publicly Available

    On October 28, Google released Gemini 4 Carbon, which topped the Artificial Analysis Intelligence Index v5.0 with a score of 59, surpassing Claude Opus 5.5's 58 and GPT-6 Astra's 57 to reclaim first place. The model is currently available only to a small number of cybersecurity defense personnel; when asked when ordinary developers and enterprises will be able to use it, officials responded only with "as soon as possible." On the GraphWalks ultra-long-context test, Carbon achieved 96.2% F1, far above GPT-6 Astra's 71.8% and Claude Opus 5.5's 66.8%; introductory pricing is $2 per million input tokens and $10 per million output tokens, the same as the previous-generation Argon.

    On October 28, Google released Gemini 4 Carbon, which topped the Artificial Analysis Intelligence Index v5.0 with a score of 59, surpassing Claude Opus 5.5's 58 and GPT-6 Astra's 57 to reclaim first place. The model is currently available only to a small number of cybersecurity defense personnel; when asked when ordinary developers and enterprises will be able to use it, officials responded only with "as soon as possible." On the GraphWalks ultra-long-context test, Carbon achieved 96.2% F1, far

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  3. TMTPost · AGI

    Microsoft, Google, and Amazon Earnings Side by Side: The AI Infrastructure Race Reaches a Watershed

    The latest earnings reports from the three cloud providers Microsoft, Google, and Amazon show cloud businesses accelerating across the board: AWS third-quarter revenue was $45.98 billion, up 39.3% year over year; Azure posted $33.165 billion for the quarter, up 48%; Google Cloud revenue was $30.71 billion, more than doubling year over year; and their backlogs reached $578 billion, $677 billion, and $561 billion, respectively. Over the same period, all three posted negative free cash flow: Amazon had a net outflow of $42.36 billion over the past 12 months, Alphabet was negative $9.07 billion, and Meta had a net outflow of $2.12 billion, while only Microsoft remained positive at $18.6 billion. Market reactions diverged; Alphabet fell 12.64% in a single day on slowing advertising growth and its swing to negative cash flow, and the article argues that the competitive bottleneck is shifting from chips to power, land, and grid-connection approvals.

    The latest earnings reports from the three cloud providers Microsoft, Google, and Amazon show cloud businesses accelerating across the board: AWS third-quarter revenue was $45.98 billion, up 39.3% year over year; Azure posted $33.165 billion for the quarter, up 48%; Google Cloud revenue was $30.71 billion, more than doubling year over year; and their backlogs reached $578 billion, $677 billion, and $561 billion, respectively. Over the same period, all three posted negative free cash flow: Amazon

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  4. Latent Space

    Elorian Releases DecoyCount Benchmark: Frontier Models All Score Below 50% on Visual Counting Accuracy

    Elorian and Mercor jointly released the DecoyCount benchmark, which tests whether models truly count objects or rely on visual shortcuts. Frontier models all scored below 50% accuracy, with the highest being GPT-6 Astra at 43.17%. Elorian says its visual reasoning model Glimpse scored 50.48% in a single run on 1,660 questions, making it the only model to exceed 50%, but this result comes from internal testing and did not use an agent or tool framework, whereas the six models in the paper each took the average of three runs. Elorian CEO Andrew Dai said the benchmark examines both vision and reasoning, and can distinguish whether a model failed to see the objects or miscounted them.

    Elorian and Mercor jointly released the DecoyCount benchmark, which tests whether models truly count objects or rely on visual shortcuts. Frontier models all scored below 50% accuracy, with the highest being GPT-6 Astra at 43.17%. Elorian says its visual reasoning model Glimpse scored 50.48% in a single run on 1,660 questions, making it the only model to exceed 50%, but this result comes from internal testing and did not use an agent or tool framework, whereas the six models in the paper each to

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  5. cnBeta

    Google releases Gemini 4 Carbon, tops the Artificial Analysis leaderboard with 59 points

    Google released Gemini 4 Carbon, which scored 59 points on the Artificial Analysis Intelligence Index v5.0 leaderboard, surpassing Claude Opus 5.5's 58 points and GPT-6 Astra's 57 points. The model achieved 88.2%, 54.8%, and 71.0% on SEC-bench Pro, ExploitGym, and CWE-bench, respectively, and Google says it can handle engineering problems in large codebases continuously for several days. The model this week is first being made available to some cybersecurity defenders, then expanded to trusted partners through the Fairwind Program, with no timeline yet for general users; initial pricing is $2 per million input tokens and $10 per million output tokens.

    Google released Gemini 4 Carbon, which scored 59 points on the Artificial Analysis Intelligence Index v5.0 leaderboard, surpassing Claude Opus 5.5's 58 points and GPT-6 Astra's 57 points. The model achieved 88.2%, 54.8%, and 71.0% on SEC-bench Pro, ExploitGym, and CWE-bench, respectively, and Google says it can handle engineering problems in large codebases continuously for several days. The model this week is first being made available to some cybersecurity defenders, then expanded to trusted p

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Tuesday

  1. The Guardian Technology

    Critics criticize Musk's AI version of The Odyssey made with Grok Imagine

    Musk produced the seven-minute first episode of The Odyssey with Grok Imagine and London startup Wonder Studios, drawing 7.3 million views on X, but the critical response was lukewarm, with The Guardian film critic Peter Bradshaw giving it 1 star. The episode was completed by a three-person creative team in under two weeks at a cost reportedly in the tens of thousands of dollars, whereas Nolan's version cost $250 million, shot for 91 days, and grossed $1.8 billion at the box office. Wonder Studios co-founder Xavier Collins said they will improve the second episode based on the reviews, with the goal that the final episode be a fundamental improvement over the first.

    Musk produced the seven-minute first episode of The Odyssey with Grok Imagine and London startup Wonder Studios, drawing 7.3 million views on X, but the critical response was lukewarm, with The Guardian film critic Peter Bradshaw giving it 1 star. The episode was completed by a three-person creative team in under two weeks at a cost reportedly in the tens of thousands of dollars, whereas Nolan's version cost $250 million, shot for 91 days, and grossed $1.8 billion at the box office. Wonder Studi

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  2. Yicai

    Why Jensen Huang Can't Help European AI

    It is difficult for Jensen Huang and Nvidia to help Europe build a local AI ecosystem, and the core reason is that Nvidia is too powerful: the full-stack AI factory it delivers covers GPUs, CUDA-X libraries, and the model layer, so European companies can only build the application layer on top of it. Europe lacks chip companies that can compete head-on with Nvidia, and the representative model company Mistral AI has not gained global recognition. Nvidia has previously invested 8 billion US dollars in Europe and will add another 2 billion US dollars in the near term, but the funds are spread across dozens of companies in multiple countries, so the effect is limited.

    It is difficult for Jensen Huang and Nvidia to help Europe build a local AI ecosystem, and the core reason is that Nvidia is too powerful: the full-stack AI factory it delivers covers GPUs, CUDA-X libraries, and the model layer, so European companies can only build the application layer on top of it. Europe lacks chip companies that can compete head-on with Nvidia, and the representative model company Mistral AI has not gained global recognition. Nvidia has previously invested 8 billion US dolla

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  3. Redwood Research:Blog

    Redwood Research: Why AI's conceptual reasoning capabilities should be accelerated

    Redwood Research argues that AI's conceptual reasoning capabilities should be accelerated differentially—that is, tasks that resemble philosophy, lack verifiable standards, and rely on a priori argumentation. The organization believes such capabilities are crucial for safety work such as alignment, yet are neglected by AI companies because of their low value for AI R&D and commercial applications, with currently insufficient investment. Its preliminary work shows that basic steering methods such as few-shot prompting and small-scale training can improve models' scores on the main conceptual reasoning benchmark by an amount equivalent to 3 to 12 months of frontier progress.

    Redwood Research argues that AI's conceptual reasoning capabilities should be accelerated differentially—that is, tasks that resemble philosophy, lack verifiable standards, and rely on a priori argumentation. The organization believes such capabilities are crucial for safety work such as alignment, yet are neglected by AI companies because of their low value for AI R&D and commercial applications, with currently insufficient investment. Its preliminary work shows that basic steering methods such

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