TechCrunch Disrupt 2026 Adds Real World AI Stage Featuring Nvidia, Robots, and Extinct Animals
TechCrunch Disrupt 2026 introduces a new Real World AI Stage, focusing on physical AI applications, with events running October 13 to 15 in San Francisco.
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The chips and systems powering modern AI — GPUs, accelerators, data-center infrastructure, and the hardware roadmaps from Nvidia, AMD, and custom silicon makers driving training and inference.
TechCrunch Disrupt 2026 introduces a new Real World AI Stage, focusing on physical AI applications, with events running October 13 to 15 in San Francisco.
Apple has filed new evidence in its lawsuit against OpenAI, alleging a former employee stole confidential data. The company claims more than 400 former Apple employees now work at OpenAI.
AWS ranked highest in Forrester’s AI Infrastructure Solutions Wave, scoring 5.00 in 16 criteria out of 13 providers.
China's CXMT is manufacturing HBM3E chips in small quantities, a step toward reducing reliance on foreign AI memory technology.
Nvidia is investing $3.5 billion in MediaTek to help it design custom AI chips for hyperscalers and cloud providers, according to a recent announcement.
OpenAI and rival AI labs have purchased tens of thousands of Mac minis to train computer-use agents, with Apple’s Mac revenue rising 29% in the June quarter.
Meta is testing robots to automate tasks like cable swapping and server resets in its data centers, with one worker estimating the bots could replace up to 80% of some roles.
Elon Musk claims SpaceX's in-house turbine casting could accelerate gas turbine production by up to 18 months, addressing a critical bottleneck for AI infrastructure.
Nvidia's market cap grew 10x between 2023 and mid-2025, but recent earnings show its edge extends beyond GPUs into data orchestration.
Neocloud Lambda raised $1 billion in short-dated debt to purchase Nvidia AI chips for Microsoft, per Bloomberg.
Meta is testing robots from Watney Robotics, Kinova, and ABB to automate tasks like cable swapping and server resets in its data centers, according to workers.
Anthropic's Model Hardware Standard (MHS) aims to streamline AI integration with physical devices, reducing experimental setup time from weeks to hours, according to the company.