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Author JasonSanchez

Articles published by JasonSanchez

A total of 4 articles
July 17, 2026

WeRide launched its physical AI foundation model WITT on July 17. It introduces the minimum physical fact unit to help AI understand multimodal data like video and images. This framework enhances environment perception and decision-making for autonomous vehicles, improving safety and efficiency while accelerating commercialization.

WeRide launched its physical AI foundation model WITT on July 17. It introduces the minimum physical fact unit to help AI understand multimodal data like video and images. This framework enhances environment perception and decision-making for autonomous vehicles, improving safety and efficiency while accelerating commercialization.

WeRide launched its physical AI foundation model WITT on July 17. It introduces the minimum physical fact unit to help AI understand multimodal data like video and images. This framework enhances environment perception and decision-making for autonomous vehicles, improving safety and efficiency while accelerating commercialization.
July 1, 2026

EquiLibre Technologies, founded by three ex-DeepMind researchers, raised Series A at a 500M valuation led by Creandum. It applies reinforcement learning to financial trading, executing billions in daily S&P 500 and Nasdaq trades, with zero monthly losses in crypto since 2025.

EquiLibre Technologies, founded by three ex-DeepMind researchers, raised Series A at a 500M valuation led by Creandum. It applies reinforcement learning to financial trading, executing billions in daily S&P 500 and Nasdaq trades, with zero monthly losses in crypto since 2025.

EquiLibre Technologies, founded by three ex-DeepMind researchers, raised Series A at a 500M valuation led by Creandum. It applies reinforcement learning to financial trading, executing billions in daily S&P 500 and Nasdaq trades, with zero monthly losses in crypto since 2025.
June 9, 2026

China launched the 2026 Humanoid Robot and Embodied Intelligence Field Training Action Plan to deploy humanoid robots in real production scenarios by end of 2026. Focus areas include manufacturing logistics emergency rescue and healthcare. The plan promotes innovative application consortiums and a verify one deploy a batch drive a region strategy. It also encourages a humanoid robot as a service model to lower investment barriers.

China launched the 2026 Humanoid Robot and Embodied Intelligence Field Training Action Plan to deploy humanoid robots in real production scenarios by end of 2026. Focus areas include manufacturing logistics emergency rescue and healthcare. The plan promotes innovative application consortiums and a verify one deploy a batch drive a region strategy. It also encourages a humanoid robot as a service model to lower investment barriers.

China launched the 2026 Humanoid Robot and Embodied Intelligence Field Training Action Plan to deploy humanoid robots in real production scenarios by end of 2026. Focus areas include manufacturing logistics emergency rescue and healthcare. The plan promotes innovative application consortiums and a verify one deploy a batch drive a region strategy. It also encourages a humanoid robot as a service model to lower investment barriers.
May 26, 2026

Apple is reportedly using a customized 1.2 trillion parameter Google model as the core for its next-generation Siri overhaul, far exceeding the scale of current mobile models. This aims to significantly boost Siri's reasoning and multimodal capabilities. A key challenge will be balancing this massive model's performance with efficient local device inference to ensure speed, privacy, and power efficiency. The move intensifies the AI competition ahead of major updates expected from Apple, OpenAI, Anthropic, and Google.

Apple is reportedly using a customized 1.2 trillion parameter Google model as the core for its next-generation Siri overhaul, far exceeding the scale of current mobile models. This aims to significantly boost Siri's reasoning and multimodal capabilities. A key challenge will be balancing this massive model's performance with efficient local device inference to ensure speed, privacy, and power efficiency. The move intensifies the AI competition ahead of major updates expected from Apple, OpenAI, Anthropic, and Google.

Apple is reportedly using a customized 1.2 trillion parameter Google model as the core for its next-generation Siri overhaul, far exceeding the scale of current mobile models. This aims to significantly boost Siri's reasoning and multimodal capabilities. A key challenge will be balancing this massive model's performance with efficient local device inference to ensure speed, privacy, and power efficiency. The move intensifies the AI competition ahead of major updates expected from Apple, OpenAI, Anthropic, and Google.
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