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AI News List

List of AI News about multimodal models

Time Details
2026-03-12
00:41
Elon Musk Interview: How Humanoid Robots and AI Could Transform Medical Care — 3 Key Takeaways and 2026 Outlook

According to Sawyer Merritt on X, Elon Musk said in a new interview that highly dexterous, smart humanoid robots could give everyone access to better medical care, citing his own need for multiple neck surgeries as an example of where robotic precision could help (as reported by Sawyer Merritt). According to the interview clip shared by Sawyer Merritt, Musk’s vision implies surgical-assist robots and bedside automation could expand capacity, reduce errors, and improve access, especially in regions with clinician shortages (as reported by Sawyer Merritt). For AI businesses, the opportunity centers on humanoid platforms like Tesla Optimus integrated with computer vision, force feedback, and large multimodal models to perform repetitive clinical tasks and support minimally invasive procedures, pending regulatory approval and clinical validation (according to the interview context shared by Sawyer Merritt).

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2025-11-10
14:09
Waymo AI Achieves Breakthroughs with Billions of Simulated Miles: Autonomous Driving Safety and Multimodal Model Advances

According to @GoogleDeepMind, Waymo's AI has achieved significant advancements by simulating billions of miles in various driving scenarios and weather conditions, in addition to real-world testing. This large-scale data enables Waymo’s self-driving technology to handle rare and complex events, improving autonomous vehicle safety and reliability. The podcast discussion with Waymo's Distinguished Engineer Vincent Vanhoucke highlights the use of 3D world modeling, multimodal models, and advanced sensor technologies, positioning Waymo as a leader in scalable, safe autonomous driving solutions (Source: @GoogleDeepMind).

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2025-06-27
15:52
The Race for LLM Cognitive Core: Small-Scale AI Models Redefining Personal Computing

According to Andrej Karpathy, the AI industry is witnessing a significant shift towards developing 'cognitive core' large language models (LLMs) with a few billion parameters that prioritize real-time capability over encyclopedic knowledge. These streamlined models are designed to run natively, always-on, and by default on every personal computer, serving as the kernel of LLM-powered personal computing. Their emerging features include native multimodality, efficient memory usage, and integration with local applications, which open up new business opportunities for edge AI solutions, privacy-focused AI assistants, and custom enterprise deployments (source: Andrej Karpathy, Twitter, June 27, 2025).

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