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The Information, citing people familiar with the matter, reported that OpenAI CEO Sam Altman last week internally proposed three AI safety paths: establishing a regulatory body modeled on the International Atomic Energy Agency (IAEA), a lab merger plan known as the Demis Plan, and a single-developer compute monopoly plan known as the Eliezer Plan. Altman also complained that there are too few speed-limit proposals for AI development, while noting that OpenAI cannot afford to fall behind in the competition, and plans to decide on an IPO path within a year. The United States currently relies on voluntary pre-review of new models, and in June imposed export controls on Anthropic on the grounds that the Fable model posed a jailbreak risk.
The Information, citing people familiar with the matter, reported that OpenAI CEO Sam Altman last week internally proposed three AI safety paths: establishing a regulatory body modeled on the International Atomic Energy Agency (IAEA), a lab merger plan known as the Demis Plan, and a single-developer compute monopoly plan known as the Eliezer Plan. Altman also complained that there are too few speed-limit proposals for AI development, while noting that OpenAI cannot afford to fall behind in the c
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AWS introduces the Agent Registry runtime tool discovery approach: agents use hybrid semantic and keyword search to find approved MCP servers and A2A agents, then instantly build clients from descriptors to execute requests. The sample code is based on Amazon Bedrock AgentCore Gateway and runtime, integrates an order management MCP server and two A2A agents for pricing and customer service, and demonstrates a return and refund scenario using pure semantic matching. The registry returns only connection metadata; invocation credentials must be obtained separately through Cognito OAuth or IAM, and new capabilities require no changes to orchestrator code.

hen instantly build clients from descriptors to execute requests. The sample code is based on Amazon Bedrock AgentCore Gateway and runtime, integrates an order management MCP server and two A2A agents for pricing and customer service, and demonstrates a return and refund scenario using pure semantic matching. The registry returns only connection metadata; invocation credentials must be obtained separately through Cognito OAuth or IAM, and new capabilities require no changes to orchestrator code.
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General Motors has invested $900 million to build a battery cell development center at its Warren Technical Center in Michigan, and is advancing its in-house LMR (lithium manganese-rich) cells, with plans to mass-produce them in 2028 in partnership with LG Energy Solution. Its LMR cells have a nickel content of about 30% to 40%, lower than the roughly 85% in current high-nickel cells, and an energy density about one-third higher than mainstream LFP cells, at a comparable cost. GM says the technology is independently developed and does not rely on Chinese licensing, with the goal of giving large electric pickups and full-size SUVs cheaper batteries with longer range.
General Motors has invested $900 million to build a battery cell development center at its Warren Technical Center in Michigan, and is advancing its in-house LMR (lithium manganese-rich) cells, with plans to mass-produce them in 2028 in partnership with LG Energy Solution. Its LMR cells have a nickel content of about 30% to 40%, lower than the roughly 85% in current high-nickel cells, and an energy density about one-third higher than mainstream LFP cells, at a comparable cost. GM says the techno
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Vectorial has closed a $3 million seed round with investors including Smilegate, SenseAI Ventures and Dent Capital, to expand its behavioral dataset and develop the SAPIENS 2.0 model. Its platform first uses behavioral data to build models of target audiences, then lets product, design and marketing teams simulate product journeys, marketing concepts and AI agent conversations before reaching real users. The company says it has modeled over 2.5 million people and completed more than 30,000 simulations, with simulations reproducing existing user research findings with over 85% accuracy, and SAPIENS predicting behavior 30% more accurately than general-purpose large language models.
Vectorial has closed a $3 million seed round with investors including Smilegate, SenseAI Ventures and Dent Capital, to expand its behavioral dataset and develop the SAPIENS 2.0 model. Its platform first uses behavioral data to build models of target audiences, then lets product, design and marketing teams simulate product journeys, marketing concepts and AI agent conversations before reaching real users. The company says it has modeled over 2.5 million people and completed more than 30,000 simul
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