GoKawiil
Tech News
A new textbook titled Foundation Model Engineering has been released, aimed at AI engineers and research-minded readers who want to understand foundation models beyond basic API use. It ties together topics like attention, mixture-of-experts, RLHF, multimodality, long-context inference, retrieval-augmented generation, and agents into a single engineering narrative, using PyTorch examples, quizzes, and interactive visualizers.
TechCrunch Disrupt 2026, running October 13–15 at Moscone West in San Francisco, will feature a Builders Stage session titled 'What Happens When OpenAI Ships Your Roadmap.' The panel brings together Michel Tricot of Airbyte, Rob Toews of Radical Ventures, and Linda Tong of Webflow to discuss how AI startups navigate the risk of foundation model providers absorbing their core features. The event is expected to draw over 10,000 founders, investors, and operators across 250+ sessions.
NASA and IBM have jointly published an open-source AI system, along with a compiled dataset drawing on over 30 aligned data layers from nine instruments across four lunar missions. The model merges multiple imaging types, angles, and resolutions to let researchers study the Moon's surface more comprehensively than existing tools allow.
IBM has developed a Lunar Foundation Model designed to process decades of accumulated Moon observation data. The AI system aims to help researchers identify surface hazards, locate resources, and track changes on the lunar terrain as NASA targets returning astronauts to the Moon by 2028.
NASA and IBM have jointly released the Lunar Foundation Model, an AI system trained on decades of lunar observation data, now freely available on Hugging Face. Built alongside what the two say is the first open-source dataset combining imagery from nine instruments across four moon missions, the model is designed to support NASA's Artemis program.
NASA and IBM launched the NASA-IBM Lunar Foundation Model, a free AI system on Hugging Face designed to help scientists study the Moon. Trained on lunar imagery and environmental data, the model can spot likely ice deposits and identify craters more accurately than existing tools like Microsoft's SwinV2-B. It was recently put to a real test when it correctly flagged the impact site of a SpaceX Falcon 9 rocket that crashed into the Moon in August, even though the new crater overlapped an existing one.
Robotics startup Generalist has raised nearly $200 million more in an extension of its Series B round led by 8VC, pushing its valuation to $3 billion and total round funding to $600 million. The company, founded in 2024 by ex-Google DeepMind and Boston Dynamics engineers, builds AI foundation models meant to control multiple types of robots, with its Gen 1.5 model reportedly learning new tasks from short video clips.