Simon Willison
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1 hour ago
Mira Murati's Thinking Machines Lab released Inkling, an open-weights multimodal transformer with 975 billion total parameters and 41 billion active parameters, licensed under Apache 2.0 and trained on 45 trillion tokens. A smaller version with 276 billion parameters is in testing. The model is positioned as a strong base for fine-tuning rather than a frontier model and competes with other open-weights alternatives like NVIDIA Nemotron and Gemma 4.
Sakana AI
Sakana AI is integrating NVIDIA's Nemotron open models into its Fugu multi-agent orchestration system, which coordinates multiple specialized models to handle complex tasks. In early evaluations, the orchestration-based approach has shown strong performance alongside leading frontier systems, demonstrating that model coordination can serve as a scaling path. This collaboration aims to create a feedback loop where open models, orchestration, and real-world use reinforce each other, reducing dependence on single providers and enabling more capable AI systems.
The New Stack
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1 hour ago
Linus Torvalds announced that Linux will support AI tools in development and told those opposed to either fork the project or leave, marking a shift from his skepticism a year earlier when he criticized AI hype. Torvalds stated this position explicitly as the top-level maintainer, saying AI is a useful tool like any other, though he acknowledged it presents challenges for maintainers. The Linux project will now actively integrate AI assistance while requiring human developers to take responsibility for understanding and explaining contributions.
Deep Learning Weekly
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1 hour ago
This week's deep learning newsletter covers Thinking Machines Lab's release of Inkling, a 975B-parameter open-weights multimodal MoE model, OpenAI's GPT-Red system which cut prompt injection failures by 6x through adversarial training, and research showing video generation models can serve as general-purpose vision learners, achieving state-of-the-art performance on diverse vision tasks while requiring 7 to 500 times less training data than specialized models. The issue also features MLOps optimizations, agentic system architectures, and a comprehensive survey on metacognition in large language models.
TechCrunch AI
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2 hours ago
Moonshot AI's upcoming Kimi K3 model, expected between 2 trillion and 3 trillion parameters, is projected to match or exceed Anthropic's Opus 4.8 performance according to Financial Times sources. Moonshot is raising fresh capital at a $31.5 billion valuation, up from $20 billion in May, as Chinese open-weight models increasingly close the performance gap with expensive closed-source alternatives from OpenAI and Anthropic. The release is expected in the coming days and reflects growing momentum toward open-source AI models as cost-effective alternatives to proprietary systems.
Simon Willison
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3 hours ago
Linus Torvalds stated that Linux will not adopt an anti-AI stance and that developers opposed to AI integration can fork the project or leave. He argued that AI's utility is now established, distinguishing it from theoretical questions about AI's long-term economic impact. This positions Linux as open to AI-assisted development tools, contrasting with open-source projects that have explicitly rejected AI contributions.
Ben's Bites
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3 hours ago
Thinking Machines launched Inkling, its first open-weights model with a 1M-token context window supporting text, images and audio, available on the Tinker fine-tuning platform. The model is positioned for custom fine-tuning as startups increasingly shift workloads from frontier models to self-hosted versions, with alternatives like GLM-5.2 gaining adoption despite lacking vision capabilities. The release reflects a growing market trend toward open-source and customized AI models rather than reliance on leading proprietary systems.
Hugging Face Blog
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5 hours ago
DharmaOCR, a Portuguese-language optical character recognition model, outperformed newer competitors Mistral OCR4 and Unlimited-OCR on a Brazilian Portuguese benchmark through domain-specific training rather than architectural superiority. DharmaOCR scored 0.925 on the Portuguese benchmark while Mistral OCR4 scored 0.798 and Unlimited-OCR scored 0.7587. The specialized model's advantage persists because concentrating all parameters on a single language outperforms distributing them across multiple languages, even as general OCR architectures improve.
TLDR Dev
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5 hours ago
Boop is an open-source iMessage-based personal agent template that runs on Claude or ChatGPT subscriptions, using the Claude Agent SDK or Codex runtime without requiring separate API keys. The system connects to 1000+ integrations through Composio (Gmail, Slack, GitHub, etc.), manages tiered memory with daily consolidation, dispatches tasks to specialized sub-agents, and includes a debug dashboard with timeline, automation, and memory visualization. Users can text natural language requests and receive responses with full context, plus optional local browser automation and Apple data access, though the creator explicitly states it is not optimized for cost or security and should be reviewed before personal use.
TLDR Dev
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5 hours ago
A company released Inkling, an open-weights Mixture-of-Experts model with 975B total parameters and 41B active parameters, trained on 45 trillion tokens of multimodal data. The model supports a 1M token context window and includes a smaller 12B variant, with both available for fine-tuning on their Tinker platform. Inkling enables developers to customize and deploy models across diverse domains while balancing performance with computational efficiency through controllable thinking effort.
Meta AI Blog
Meta and the World Resources Institute released Canopy Height Maps v2, an open-source model that uses satellite imagery to measure forest structure globally for conservation and land management. The model's accuracy metric (R²) improved from 0.53 to 0.86, and it was built using Meta's DINOv3 vision model trained on 493 million satellite images. Governments and organizations in the UK, EU, and US cities are already using the maps to monitor forests, track tree-planting commitments, and plan urban cooling interventions.
Meta AI Blog
TRIBE v2 is an AI model trained to predict how the human brain responds to visual, auditory, and language stimuli by learning from fMRI scans of over 700 volunteers. The model was trained on more than 700 healthy volunteers presented with diverse media including images, podcasts, videos, and text, and can make predictions for new subjects, languages, and tasks without additional brain imaging data. Researchers can now test hypotheses about brain function computationally, reducing the need for human subjects in experimental studies and potentially accelerating neuroscience discovery.
The Batch
Z.ai released GLM-5.2, an open-weights language model optimized for autonomous coding tasks that ranks first among open models on multiple benchmarks. The model processes up to 1 million tokens of input context with 753 billion total parameters, and costs $1.40 per million input tokens through the API. U.S. universities have established at least 1,000 AI programs across 584 colleges, including 78 majors and 103 minors as of April, up from just five schools offering AI majors in 2021.
The Batch
DeepSeek released an open-weight reasoning model (DeepSeek-R1) that matches OpenAI's o1 performance, triggering a stock market sell-off of Nvidia and other U.S. tech companies. DeepSeek-R1 costs $2.19 per million output tokens compared to o1's $60 per million, a nearly 30-fold price difference. The advancement demonstrates that algorithmic innovation and optimized training can compete with raw computational scaling, shifting focus away from the assumption that more computing power is the only path to AI progress.
MarkTechPost
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10 hours ago
SpaceXAI open-sourced Grok Build, its terminal-based AI coding agent, under the Apache 2.0 license on GitHub today, providing the agent harness, TUI, tool layer, and extension system for local or remote code editing and task management. The release includes multiple Rust crates covering the agent loop, terminal UI, file tools, and workspace integration, with configuration-based model selection supporting any inference endpoint. Developers can now audit the agent code before use, fork it for internal deployment, run it fully offline with local models, or integrate it into CI pipelines through headless mode.
Latent Space
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10 hours ago
Thinking Machines Lab released Inkling, a 975-billion-parameter open-weights multimodal model with 41 billion active parameters that processes text, images, and audio. The model was pretrained on 45 trillion tokens and supports context windows up to 1 million tokens, with an Apache 2.0 license available immediately on Hugging Face and partner platforms. Inkling ranks as the strongest U.S.-based open-weights model released to date, though independent reviewers note it remains behind top Chinese open models and closed systems on some benchmarks.
