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Qualcomm, Amazon Target Custom AI Data Center Silicon

Qualcomm, Amazon Target Custom Silicon for AI Inference

Qualcomm and Amazon are expanding their semiconductor partnership into large-scale AI data centers, with a multi-generation collaboration focused on custom silicon for AI inference and optical connectivity reaching speeds of up to 1.6 terabits per second. The agreement gives Qualcomm a larger role in the rapidly expanding AI infrastructure market while strengthening Amazon Web Services’…

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Triple Whale Bets on Agentic AI for Ecommerce

Triple Whale Repositions Around Agentic AI for Ecommerce

Triple Whale is repositioning itself from an ecommerce analytics platform into what it describes as an AI operating system for commerce, unveiling a new brand identity alongside a broader push into agentic automation. The company says its Moby AI operator can move beyond analyzing business performance to recommending and executing actions across advertising, creative, websites…

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Alif Launches Low-Cost Edge AI StartKits

Alif Cuts the Cost of Edge AI Development With New MCUs

Alif Semiconductor is targeting one of the biggest barriers to embedded AI adoption: the cost and complexity of getting started. The semiconductor company has introduced two low-cost evaluation boards, the SK-B1 and SK-E1C StartKits, designed to help developers test on-device AI and machine learning workloads on its Balletto and Ensemble microcontrollers. The boards bring dedicated…

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Function Health Connects Data to Meta's Muse AI

Function Connects Health Data to Meta’s Muse AI

Function Health is expanding its network of AI integrations by allowing members to connect their health data with Muse, Meta’s new personal AI agent. The integration gives Muse access to Function’s lab results and clinician-reviewed health summaries, allowing users to bring personal health context into AI-assisted planning and tracking while retaining control over the connection….

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Why Forward Engineers Matter for Enterprise AI

Why Forward Engineers Are Becoming Critical to AI

Enterprise AI has a deployment problem that increasingly sits beyond model performance. A widely cited industry estimate suggests that about 95% of enterprise AI pilots fail to reach production, highlighting the difficult transition from a successful demonstration to a system that can operate inside legacy infrastructure, security controls and complex business processes. Think41 is betting…

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