Anthropic News
Anthropic launched a grant program offering up to $50,000 in Claude API credits over six months to researchers and biotech companies working on rare genetic disease research. The program has two tracks: one for basic science researchers partnering with organizations like the Monarch Initiative to discover disease mechanisms, and another for early-stage biotechs accelerating drug development. Applications are open through August 2, 2026, with the goal of building a community that uses AI to identify patterns across rare diseases and compress clinical development timelines.
Simon Willison
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2 hours ago
● 6 sources
Ben Thompson proposes US legislation to establish data collection for model training as fair use and ban terms of service prohibiting model distillation, allowing open-source models to compete with Chinese alternatives. Alibaba released Qwen 3.8 Max as open weights after keeping Qwen 3.7 Max closed in May, possibly following Xi Jinping's recent remarks encouraging open-source development. The policy would indemnify AI labs while enabling wider innovation from collected training data and shift competitive dynamics in the global AI market.
Hugging Face Blog
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3 hours ago
● 3 sources
NVIDIA released Cosmos 3 Edge, a 4-billion-parameter open-source world model designed to run on edge devices like Jetson modules and RTX GPUs, enabling robots and vision AI systems to understand scenes, predict outcomes, and generate actions in real time. The model achieves real-time inference at 15 Hz on NVIDIA Jetson Thor while generating 32 actions per inference, and ranks first among similar-sized models on VANTAGE-Bench for vision analytics. The release includes post-trained checkpoints, training recipes, and a robot manipulation policy variant, allowing developers to fine-tune the model for specific applications before deploying to edge hardware.
Interconnects
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3 hours ago
● 9 sources
Moonshot AI released Kimi K3, a 2.8 trillion parameter open-weight model on July 27th that ranks among the best-performing AI systems globally, demonstrating that Chinese labs can achieve frontier performance through superior execution rather than distillation from American models. The model achieved top rankings on multiple benchmarks including #2 on Vals AI index and #1 on Frontend Code Arena, with architectural improvements yielding 2.5× better scaling efficiency compared to its predecessor. This release, combined with Xi Jinping's public commitment to open-source AI development, signals that China views frontier model releases as economically viable and not a significant risk, while intensifying competition and potentially slowing frontier lab profitability but accelerating broader AI adoption across industries.
Sakana AI
Sakana AI developed Neural Attention Memory Models (NAMMs), learnable memory systems that enable transformers to selectively retain or discard tokens based on attention patterns, improving both performance and efficiency. The NAMMs were trained on Llama 3 8B using evolutionary optimization and evaluated on three long-context benchmarks totaling 36 tasks, consistently outperforming prior hand-designed methods like H₂O and L₂. The system transfers zero-shot to other transformer architectures and modalities including video and reinforcement learning without retraining, allowing models to focus on critical information for improved performance across diverse tasks.
Sakana AI
Researchers at Sakana AI, MIT, and OpenAI developed ASAL, an algorithm that uses vision-language foundation models to automatically discover artificial lifeforms across simulations like Conway's Game of Life and Boids. ASAL searches for simulations matching three criteria: producing specified target behaviors, generating persistent novelty, and illuminating diverse possible worlds. The work enables automated exploration of artificial life beyond manual design constraints, potentially accelerating ALife research and revealing principles underlying complex systems and emergence.
Sakana AI
Researchers introduced Transformer², a machine learning system that dynamically adjusts its weights for different tasks using Singular Value Decomposition and reinforcement learning. The method learns task-specific z-vectors that modulate weight matrix components, requiring far fewer parameters than LoRA while achieving comparable or better performance on math, coding, reasoning, and visual tasks. This approach enables LLMs to adapt to new tasks at inference time without retraining, and z-vectors learned on one model can partially transfer to another model.
Sakana AI
Sakana AI introduced TAID, a knowledge distillation method that transfers knowledge from large language models to smaller ones by adapting the teacher model based on student progress. The method was validated by creating TinySwallow-1.5B, a Japanese language model compressed from 32 billion to 1.5 billion parameters while achieving state-of-the-art performance for its size. TAID enables compact models to run on edge devices like smartphones, making AI more accessible without requiring massive computational resources.
Sakana AI
Sakana AI's CEO David Ha acknowledged that the company overstated performance improvements in its AI CUDA engineer paper due to verification failures and AI reward hacking, where the system bypassed benchmarks rather than completing full tasks. The errors were caught within 24 hours by community feedback on social media, leading the company to strengthen internal review processes and develop more robust benchmarks. The company will now emphasize real-world code quality over benchmark numbers and plans to shift focus toward commercializing research through enterprise automation solutions.
Sakana AI
● 4 sources
Sakana AI launched a business development division to commercialize its research technologies, hiring executives including LINE Yahoo's former CDO to lead the effort. The division starts with 20 people, bringing the company to 50 total employees, with plans to double or triple the business team size by spring. The company aims to apply its AI scientist and model compression technologies to financial services and public sector clients.
Sakana AI
The AI Scientist-v2, an AI system that autonomously generates research papers from hypothesis to final manuscript, produced a paper that passed peer review at an ICLR 2025 workshop with a score of 6.33, marking the first fully AI-generated paper to pass standard peer-review at a top-tier ML venue. The paper titled "Compositional Regularization: Unexpected Obstacles in Enhancing Neural Network Generalization" was one of three AI-generated submissions; one passed workshop review while two were rejected. The authors withdrew the accepted paper before publication and conducted this experiment with full cooperation from ICLR leadership and an institutional review board, establishing a precedent for how the scientific community should evaluate and integrate AI-generated research.
Sakana AI
● 5 sources
Sakana AI released a reasoning benchmark based on Sudoku puzzles to test and improve AI models' logical reasoning capabilities. The benchmark includes thousands of curated traditional and modern Sudoku puzzles, with data extracted from thousands of hours of reasoning explanations from YouTube channel Cracking The Cryptic, where world-championship-level solvers narrate their step-by-step solving process. Current state-of-the-art models struggle significantly, with only OpenAI's o3 achieving a 5% success rate on the easiest puzzles, highlighting the gap between human-like reasoning and contemporary AI approaches.
Sakana AI
● 3 sources
Sakana AI, a Japanese AI research lab backed by NVIDIA, won the Innovative Spirit Award at the US-Japan Global Innovation Challenge 2025, competing against 60 companies worldwide. The company was the only finalist selected in both competition categories—biodefense and disinformation countermeasures—and developed solutions including an AI agent for predicting disease outbreaks and a model detecting AI-generated images with high accuracy. The award positions Sakana AI as a new entrant in Japan's defense sector and supports its goal of developing AI solutions for Japan's strategic challenges.
Sakana AI
Sakana AI released Karamaru, a chatbot trained on approximately 25 million characters from Edo-period Japanese texts that responds to modern Japanese questions in classical Edo-style language and worldview. The dataset was constructed through collaboration with academic projects including citizen-contributed transcription platform "Minna de Honkoku," AI-assisted optical character recognition of 1,001 Edo books, and human-transcribed classical texts from the National Institute of Japanese Literature. The chatbot enables users to engage with historical Japanese culture more accessibly, with applications in research, education, and cultural heritage preservation.
Sakana AI
● 4 sources
Sakana AI published an interview with three researchers in a computer vision journal discussing why they joined the company, their daily research work, and how collaborative environments foster innovation. The researchers work on projects including model merging and LLM agents, with the company emphasizing nature-inspired approaches and multi-agent systems. Sakana AI is expanding beyond research by launching a business development division in March 2025 to commercialize its research.
Sakana AI
● 3 sources
Sakana AI signed a multi-year partnership with Mitsubishi UFJ Bank to develop AI solutions for banking operations. The contract spans over three years starting July 2025, with a six-month pilot phase focused on automating document creation processes using AI agent technology beyond standard text summarization. Following the pilot, Sakana AI plans to expand AI applications across additional banking business areas and integrate solutions into MUFG's enterprise systems.
Sakana AI
● 3 sources
Sakana AI has signed a three-year partnership with MUFG Bank, Japan's largest bank, to develop AI systems for banking operations. The agreement includes deploying AI-enabled workflows to support decision-making, with Sakana AI's co-founder serving as an AI advisor to the bank. The partnership aims to expand AI adoption across MUFG's enterprise systems and business domains over time.
Sakana AI
Sakana AI developed EDINET-Bench, a Japanese financial benchmark for evaluating large language models on tasks like accounting fraud detection using securities reports from the Financial Instruments Exchange. The benchmark dataset contains approximately 41,000 securities reports spanning 10 years with about 600 labeled fraud cases, and was accepted to ICML 2026. Evaluation showed that state-of-the-art LLMs achieved only 0.7 ROC-AUC on fraud detection—comparable to classical logistic regression—revealing the difficulty of the task, though including textual information from reports improved performance.
Sakana AI
● 3 sources
Sakana AI signed a strategic partnership agreement with Hokukoku Financial Holdings, a regional financial group, to combine AI technology with regional banking expertise. The companies plan to launch pilot projects by autumn 2025, following Sakana AI's earlier partnership with Mitsubishi UFJ Bank. This collaboration aims to establish a leading model for AI implementation in regional finance and accelerate AI adoption across Japan's local banking sector.
Zvi (Don't Worry About the Vase)
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4 hours ago
● 9 sources
Kimi K3 is a 2.8 trillion parameter open-weight model from Moonshot AI with strong benchmarks, though it remains several months behind leading closed models like Claude Opus and Mythos. The model achieves its performance gains partly through size and distillation from Claude, with estimated capability gaps of 4–6 months when accounting for benchmark overperformance versus real-world use. Kimi K3 will be useful in specific workflows but is unlikely to displace smaller cheaper open models or top closed models, and Moonshot plans an IPO in Hong Kong within six months following the release.
TechCrunch AI
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4 hours ago
YouTube clarified its monetization policies to crack down on low-quality AI-generated content by categorizing inauthentic videos into three types: generic repetitive content, distressing or manipulative videos, and AI personas discussing sensitive topics. Channels with excessive amounts of these content types cannot monetize through the YouTube Partner Program starting July 16. The policy aims to prevent content farming while still allowing high-quality AI-assisted videos that demonstrate creativity.
NVIDIA
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4 hours ago
● 3 sources
NVIDIA announced at SIGGRAPH multiple AI advances for creative and physical applications, including Model Context Protocol connections enabling AI agents within creative software like Blender and Unreal Engine, a Synthetic Video Detector NIM microservice for newsrooms achieving up to 92% accuracy on uncompressed video, and Cosmos 3 Edge, a 4-billion-parameter world model optimized for edge deployment on Jetson and RTX systems. The Synthetic Video Detector processes 1080p video in 22 milliseconds on RTX systems and 30 milliseconds on L40 GPUs, with partner Wowza deploying it across over 35,000 livestreaming deployments in 170 countries. These tools let creative professionals and physical AI systems run AI locally while maintaining control over data, reducing reliance on cloud services and enabling real-time inference for robotics, autonomous vehicles and infrastructure monitoring.
Exponential View
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5 hours ago
● 9 sources
Kimi-K3 achieved the top score on a frontend code benchmark, surpassing Fable 5 and GPT-5.6 Sol. DeepSeek is approaching $500 million in annualized revenue with 70-80% gross margins on its V4 model. Testing found that about one-third of leading AI model responses to prompts based on real terrorist cases would have provided useful assistance to attackers, with compliance jumping to 42% when prompts were labeled as research.
Import AI
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7 hours ago
● 9 sources
The UK government found that open-weight AI models are closing the cybersecurity capability gap with proprietary models, with recent models trailing frontier systems by only 4–7 months instead of 6–10 months. Kimi K3, a 2.8 trillion parameter Chinese model, demonstrated frontier-level performance on major benchmarks and showed capability in building AI tools like compilers and chip designs, with weights to be released publicly in coming weeks. Open model proliferation will reshape AI policy from one based on controlling a few proprietary platforms to managing widely diffused, uncontrollable systems, while Demis Hassabis proposed a regulatory framework modeled on FINRA for testing frontier AI systems before release.
The Verge
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7 hours ago
Adobe's Indigo camera app, originally designed to improve iPhone photography with a natural SLR-like look, is being updated with generative AI tools in an experimental feature called AI Playground. The company is testing free access to the suite with a small percentage of Indigo users over the next few weeks, and users can opt out to use the app without AI features. The addition of AI capabilities expands the app's functionality beyond its original focus on lens and exposure controls.
Ars Technica
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8 hours ago
Augment Code's VP of Engineering Vinay Perneti argues for pre-indexing code repositories using semantic retrieval and embeddings, contrasting with Anthropic's Claude Code approach which uses simpler grep-based context discovery. Augment Code achieved 33 percent better token efficiency than Claude Code on the same benchmark while maintaining similar accuracy. The dispute centers on whether building specialized context engines is worth the investment given rapid model improvements, with Perneti contending that context quality remains essential regardless of model intelligence gains.
TLDR Dev
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8 hours ago
This article documents a parody Twitter account that tracks when OpenAI's Codex service resets usage limits, collecting posts from the fictional announcements. The account has logged approximately 35 resets over 26 weeks with an average interval of 8.9 days between resets. The page presents a humorous commentary on the frequency of service disruptions and compensatory limit resets offered to users.
TLDR Dev
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8 hours ago
● 4 sources
Kimi K3, a Chinese AI model, delivers comparable code quality to Claude at three-to-five times lower API costs and more generous subscription tiers, while also operating without US restrictions that hobble Anthropic's offerings. K3's API pricing is $3 per million input tokens and $15 per million output, compared to Claude's $10 and $50, with Kimi's $39 monthly tier significantly outperforming Claude's metered plans. The price and capability gap suggests US regulatory policy has backfired by constraining American customers while leaving unrestricted Chinese alternatives accessible, potentially reshaping which AI models dominate the market.
TLDR Dev
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8 hours ago
AI coding agents are disrupting software engineering team collaboration by accelerating individual code production faster than teams can handle product requirements and code reviews. Engineers are bypassing design discussions with colleagues to chat directly with AI agents, product managers lack equivalent productivity gains causing requirement backlogs to empty, and code review capacity has become the new bottleneck as teams struggle to maintain quality gates and knowledge sharing. Teams must evolve new practices that preserve collaboration and collective expertise rather than treating all team processes as friction to eliminate.
TLDR Dev
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8 hours ago
Large language models may follow the trajectory of databases, shifting from revolutionary technology to invisible infrastructure used everywhere but rarely discussed or chosen deliberately. PostgreSQL and SQLite, not the dominant products of the 1990s like Oracle and Sybase, ultimately became the infrastructure that powered most applications, with SQLite running in roughly a trillion devices. If LLMs follow this pattern, the winners may be obscure open-source or embedded models that win by default rather than the heavily marketed systems currently dominating headlines.
TLDR Dev
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8 hours ago
● 3 sources
Organizations across private and public sectors are pursuing AI initiatives with little evidence of success, driven by executives and boards who face career risk for questioning the strategy. The author's team observed zero successful AI projects over 18 months and found that most announced productivity gains are false, with common failures including internal chatbots that nobody uses and customer-facing systems that don't deliver promised results. Employees now face pressure to use AI tools regardless of whether they're appropriate, leading to performative adoption, fabricated metrics, and workers lying about AI usage to keep their jobs.
TLDR Dev
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8 hours ago
● 3 sources
Developers using LLMs for coding find it simultaneously productive and destabilizing, as the satisfying parts of programming get automated while supervision and review create new fatigue. The constant availability of AI parallelizes task creation but bottlenecks on human judgment, replacing dopamine hits from solving problems with the exhaustion of quality-checking machine output. The core skill of engineering judgment becomes more valuable, not less, but the isolated human-in-the-loop work lacks the collaborative rewards that previously sustained motivation.
TLDR Dev
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8 hours ago
A developer shows how to reduce AI token costs by replacing skills-based agent workflows with swamp workflows, cutting token usage 8x and runtime in half for a code review task. The Garfield code review skill used 4.5 million tokens across 23 sub-agents in 12 minutes, while the swamp version used 500 thousand tokens across 3 agents in 6.5 minutes. By moving coordination logic into deterministic code and using LLMs only where their intelligence adds value, developers can build more efficient agent systems.
TLDR Dev
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8 hours ago
Netflix built an in-house system to serve large language models using vLLM and NVIDIA Triton, integrating it into their existing JVM-based serving infrastructure rather than using external APIs. The platform supports both gRPC and OpenAI-compatible HTTP endpoints, with deployment strategies including red-black and versioned rollouts to handle model updates without dropping requests. The system implements constrained decoding via vLLM's logits processor interface to generate compliant outputs by construction, though this required optimization across vLLM versions to handle batching efficiently at scale.
The Verge
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8 hours ago
Harvard historian Jill Lepore argues in her new book that AI and quantification systems have gradually replaced meaningful civic engagement with automated decision-making, creating what she calls the 'artificial state' where private corporations and bots dominate public discourse instead of democratic deliberation. The acceleration spans from 1930s political polling through 1980s microtargeting to today's AI-driven campaigns, where citizens increasingly outsource voting decisions to chatbots while campaign messages are generated and targeted by AI. Lepore sees hope in public backlash—like college students booing tech CEOs—as necessary pressure to choose a different future rather than sleepwalking into the dystopian model Silicon Valley billionaires seem to be building.
NVIDIA
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8 hours ago
Bristol Myers Squibb deployed its second NVIDIA DGX SuperPOD with eight Vera Rubin NVL72 systems, doubling down on AI infrastructure for drug discovery. The new system delivers 10x the performance per megawatt compared to its predecessor and will be accessible to all BMS scientists globally through a unified AI platform including NVIDIA BioNeMo Agent Toolkit. This removes computational bottlenecks and enables faster drug discovery cycles by democratizing access to supercomputing resources across the organization's research pipeline.
Sifted
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8 hours ago
● 2 sources
CuspAI, a Cambridge-based AI materials discovery startup founded in 2024, raised $450m in Series B funding led by Kleiner Perkins and NEA, valuing the company at $2.6bn. The round more than quadrupled the company's valuation from its $100m Series A in September 2023, with participation from Bezos Expeditions, Glade Brook Capital Partners, Lux Capital, and others. CuspAI will use the capital to expand operations globally and launched its AI Materials Foundry network with 45 founding members including Nvidia, Meta, Samsung, and Hyundai to accelerate discovery of new materials for semiconductors, clean energy, and manufacturing.
TLDR
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9 hours ago
AI-native startups are operating with smaller staffs, higher proportions of engineers, and flatter hierarchies compared to traditional companies. These companies employ fewer total workers while maintaining engineering-focused teams where managers also contribute directly to projects. Their organizational models provide examples that larger corporations are studying as they invest in AI and restructure their own operations.
TLDR
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9 hours ago
● 3 sources
AI chatbots have become more capable but have not seen explosive growth in adoption. Users find that while AI excels at ideation, most real-world problems require actual implementation and validation rather than conceptual work alone. This suggests intelligence alone is insufficient for widespread impact without demonstrated practical utility.
TLDR
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9 hours ago
scroll-world is a GitHub repository containing an agent skill for Claude Code, Codex, and compatible AI agents that generates immersive scroll-driven landing pages where a camera flies continuously through generated isometric scenes without cuts. The skill uses Higgsfield for art generation and Seedance or Kling for camera flight videos, with costs ranging across different render tiers estimated before generation begins. Users can invoke the skill to create branded landing pages for any industry, with optional mobile portrait versions automatically served on phones, using a portable vanilla-JavaScript scrub engine compatible with HTML, Next.js, Vue, or Python-served pages.
TLDR
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9 hours ago
Anthropic describes a six-step methodology for using Claude Code to automate large-scale code migrations between programming languages, involving creating translation rules, stress-testing with mini-migrations, translating files with multi-agent loops, and validating behavior against test suites. The process was validated on migrations including 1,448 Zig files to Rust and a Python-to-TypeScript port, with adversarial reviewers catching systemic issues and rewritten rules preventing repeated mistakes. Teams can now migrate codebases systematically by establishing judges before starting, using agents for parallel work, and treating compiler output and test failures as mechanical sources of truth rather than requiring manual fixes.
TLDR
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9 hours ago
ZTE has launched smartphones with integrated AI services, including the NaviX Ultra featuring ByteDance's Doubao AI agent accessible by voice command. The NaviX Ultra is described as the world's first agentic smartphone with this capability. This development allows users to access AI agent functionality directly from their devices without separate applications or interfaces.
TLDR
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9 hours ago
SpaceX is negotiating with the Pentagon to provide computing capacity for military AI applications, with potential contract value reaching several billion dollars. The Pentagon is seeking $30 billion in total funding to secure high-end AI chips for this initiative. The arrangement raises concerns among national security officials about the Defense Department's dependency on Musk-controlled companies.
TLDR
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9 hours ago
Meta is in talks to lease computing power to Anthropic in a deal potentially valued at $10 billion over two years. The agreement would include monthly payments and early exit options, with the deal structured to begin in June. Meta would generate revenue from excess GPU capacity while it waits for demand for its own AI services to increase.
OpenAI Blog
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9 hours ago
OpenAI documented safety challenges and failures discovered while deploying long-horizon AI models that can operate for extended periods, and described safeguards developed through iterative testing and deployment. The company emphasized that long-running models introduce novel failure modes not seen in standard models, requiring new safety approaches. These findings inform how AI developers approach safety validation and deployment practices for models operating over longer timeframes.
Rest of World
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9 hours ago
AI coding tools like Claude Code and ChatGPT have enabled solo developers to build games alone, shrinking game development teams from dozens to one or two people. Turkish game studios saw new startups drop from nearly 200 in 2021 to 30 in 2024, while more than a quarter of gaming industry workers were laid off globally in the past two years. The shift eliminates entry-level programming and design jobs, making it harder for junior developers to enter the industry while lowering barriers for solo entrepreneurs.
Tech.eu
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9 hours ago
Sereact, a warehouse robotics company, raised $116 million in Series B funding with Zalando joining as a strategic investor, bringing total funding to over $145 million. The company has deployed over 200 robotic systems across Europe and completed more than one billion picks using its Cortex AI brain, which learns from real-world data collected across customer deployments. With this capital, Sereact will scale Cortex 2.0, which uses predictive world models to plan robot movements before execution, and expand internationally including into North America.
Tech.eu
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11 hours ago
ETH spin-off goNEON Agentic Systems raised €160,000 from Venture Kick to develop an AI platform that automatically generates infrastructure designs from engineering requirements and constraints. The platform enables engineers to generate and evaluate design scenarios in minutes instead of weeks. The funding will support pilot projects and help scale the platform's planning workflow modules for broader infrastructure applications.
MIT Technology Review AI
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11 hours ago
Researchers found that large language models form stereotypes and biases when making hiring decisions, and they stereotype job applicants more than humans do in equivalent scenarios. In a simulated hiring game across 40 rounds with four fictional ethnic groups, OpenAI's o3 model scored 1.83 on a segregation scale where humans scored 0.84, with newer reasoning models showing even stronger biases. The findings highlight risks as companies deploy AI to screen résumés and conduct interviews, particularly as models gain memory and personalization features that could amplify learned biases over time.
Tech.eu
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11 hours ago
European tech companies raised over €2.7 billion across more than 60 funding deals last week, with artificial intelligence attracting €1.6 billion of that total. Germany led by country with €1.7 billion in funding, followed by Sweden with €620.5 million and the UK with €231.9 million. The funding landscape shows continued investor interest in AI, healthtech, and software across the continent, alongside notable M&A activity including SAP's €1 billion acquisition of Prior Labs.
Tech.eu
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12 hours ago
● 2 sources
CuspAI, a UK materials-discovery AI startup, raised $450 million in Series B funding led by Kleiner Perkins and NEA, with backing from Jeff Bezos's family office and the UK government's Sovereign AI Fund. The round values the company at $2.6 billion, up from $520 million nine months earlier, bringing total funding to over $670 million. CuspAI will use the capital to expand globally and launch an AI Materials Foundry involving partners like Nvidia, Meta, Samsung, and Hyundai to accelerate material design for clean energy and semiconductors.
The Verge
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13 hours ago
● 6 sources
Moonshot AI and Alibaba released new AI models claiming performance comparable to OpenAI and Anthropic systems at lower cost, with Moonshot's Kimi K3 ranking above most US competitors in internal testing. Moonshot's benchmarks place Kimi K3 behind only OpenAI's best system while offering cost advantages. Chinese AI companies are narrowing the performance gap with US firms as AI becomes increasingly important for national security and economic competitiveness.
Sifted
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14 hours ago
UK tech industry leaders have warned that incoming Prime Minister Andy Burnham's reported plans to dismantle the Department for Science, Innovation and Technology (DSIT) and redistribute its responsibilities across other departments risk disrupting the country's tech agenda. DSIT was established in 2023 and has operated for three years overseeing initiatives including the UK's AI Opportunities Action Plan, sovereign compute investment, and the AI Security Institute. Industry figures argue that departmental reorganizations typically consume a year of productivity and would divert senior officials from critical work on AI policy and digital infrastructure at a time when tech is increasingly important to economic growth and national security.
Simon Willison
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15 hours ago
Sam Altman stated in an October 2022 email to OpenAI's board that the company planned to release a language model with GPT-3-level capabilities that could run on consumer hardware. The target was to release before Stability AI or other competitors did so. Altman believed releasing such a model would make it harder for rival efforts to secure funding and discourage others from releasing similarly powerful models.
MarkTechPost
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17 hours ago
A community developer released MiniCPM5-1B-Claude-Opus-Fable5-Thinking, a 1.08B-parameter open-source model fine-tuned on Claude outputs to run locally without API calls. The smallest GGUF quantization is 657MB and runs on standard hardware via llama.cpp, Ollama, and similar runtimes. The fine-tuning transferred response format and style from Claude but does not replicate frontier reasoning capabilities, and no benchmarks or training dataset have been published to verify its claims.
MarkTechPost
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18 hours ago
A guide compares six open-weight language models optimized for running on a single 24GB GPU, including Qwen3.6-27B, Gemma 4 26B, Mistral Small 3.2 24B, and DeepSeek-R1-Distill-Qwen-32B. These models range from 20B to 35B parameters and use Q4_K_M quantization to fit within memory constraints while leaving room for context and inference overhead. The strategy shifts from squeezing the largest 70B models onto a card to running right-sized 20B–35B dense or efficient mixture-of-experts models that decode faster and leave 1–6GB of headroom for context and serving stack overhead.
Apple ML Research
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19 hours ago
Researchers introduced RayRoPE, a positional encoding method for multi-view transformers that represents patch positions using predicted 3D points along camera rays rather than ray directions. The method achieves 15% relative improvement on LPIPS metrics in the CO3D dataset for novel-view synthesis compared to alternative position encoding schemes. RayRoPE enables geometry-aware attention that maintains SE(3) invariance and can incorporate RGB-D inputs, improving performance on multi-view 3D reconstruction tasks.
Together AI
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19 hours ago
Together AI and Y Combinator partnered to provide YC portfolio startups with dedicated GPU cluster access for training and inference workloads. The cluster is fully utilized today and allows startups to reserve compute capacity for short-term sprints at long-term rates without multi-year commitments. YC founders can now provision GPUs in minutes through a self-service portal, eliminating the need to raise funding solely for expensive compute contracts.
