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AMD acquires AI chip startup Taalas, which etches model weights directly into silicon, promising order-of-magnitude inference performance boosts. The deal is seen as AMD's move to challenge Nvidia's dominance in AI hardware.
Anthropic plans to build in-house silicon expertise to design custom hardware for Claude, aiming to reduce reliance on Nvidia and improve performance through co-design of models and chips.
SCI Semiconductor announces the first silicon implementation of CHERIoT, a RISC-V-based security architecture providing deterministic memory safety and compartmentalization. The ICENI chip runs at up to 250 MHz and will be demonstrated at Embedded World.
AI chip startup Etched raised $300M at a $10.3B valuation, defying skeptics by designing specialized chips for AI inference with low-voltage and cluster-scale memory technologies.
This article announces the design and tape-out of what is claimed to be the world's first open source Ethernet switch ASIC, with silicon bring-up expected in mid-November 2025. It discusses the lack of open source networking hardware and the author's motivation to build a switch ASIC as a first step toward an open source router.
Apple is reportedly planning an M7 Ultra chip that could support up to 1.5 TB of unified memory, indicating a massive leap in memory capacity for future Macs.
Apple's failed self-driving car program led to the development of the Neural Engine and powerful on-device AI chips, which now underpin Apple's AI hardware strategy, including upcoming M7 chips with significant Neural Engine upgrades.
Apple Silicon exec Doug Brooks explains the surging demand for Mac mini and Mac Studio for AI agent workloads, highlights Apple's chip design philosophy integrating neural engines, and discusses the shift toward on-device AI for privacy and cost reasons while envisioning a hybrid future.
This paper demonstrates the first successful positional control of adding and removing individual atoms on a silicon surface using inverted-mode scanning tunneling microscopy, representing a foundational step toward molecular assemblers.
OpenAI unveiled its custom inference chip called Jalapeño, built with Broadcom, marking a significant move by Big Tech to reduce dependence on Nvidia.
Apple plans to skip M6 Pro/Max chip variants to accelerate development of M7 chips for enhanced on-device AI, aiming for a 2027 release. The move responds to competition from Nvidia, AMD, Intel, and Qualcomm in AI processing.
Apple plans to skip the high-end M6 Mac chips and instead launch an AI-focused M7 line, including M7 Pro, M7 Max, and M7 Ultra.
Tensordyne introduces Napier, an inference system using logarithmic math on silicon, claiming massive efficiency gains for MoE and reasoning models, with air-cooled racks.
Apple announces that its Private Cloud Compute architecture now extends to third-party hardware, specifically Google's servers, using Nvidia, Intel, and Google security technologies to maintain privacy guarantees for advanced AI models like AFM 3 Cloud Pro.
Analysis of Google I/O 2026 arguing that the event unveiled a complete AI stack (silicon, model, developer tools, distribution, proactive agents, and physics-aware media) rather than isolated products, positioning Google as dominant with Microsoft/OpenAI as the only plausible challengers within 18 months due to silicon maturity.
This article explores the open source silicon business model pioneered by AESC Silicon, which offers free core IP and charges for support and customization, similar to Linux. It highlights the potential for verifiable security and lower barriers for custom chips, and introduces IP Forge, a package manager for open-source IP blocks.
Apple has removed the 256GB M3 Ultra Mac Studio configuration from its online store, raising speculation about future storage options for upcoming models.