Snapdragon

Headlines · 3

1. 4d
   Qualcomm bets on open software, acquisitions to loosen Nvidia's CUDA grip

   TechNews reported on Oct. 13 that Qualcomm is pushing an "open software, proprietary silicon" strategy, keeping the hardware layer closed and differentiated while making upper-layer software tools portable across platforms to erode the developer lock-in Nvidia built around CUDA. To fill in its software stack, Qualcomm has disclosed acquisitions of Edge Impulse, Arduino and Modular since early 2025, with robotics software maker PickNik Robotics added in its latest move. At Snapdragon Summit the company said it will unify Mojo, MAX and Modular Cloud into a single software layer for Snapdragon phones, X2 PCs, AR1 glasses, Wear Elite watches, Sound Gen earbuds and the upcoming Dragonfly data-center processor, letting developers move work between Nvidia or cloud GPUs and Snapdragon devices via a Mojo workflow without rewriting code. The report says Nvidia's edge lies in its integrated toolchain, simulation and robotics compute platform plus a large developer community, which also raises switching costs.

   科技新报 · 🔥 0
2. 6d
   Qualcomm CEO: AI companies ask for phones running 100B-parameter LLMs locally by 2028

   Qualcomm president and CEO Cristiano Amon said in an interview with Sources that several companies at the forefront of AI are asking Qualcomm to support smartphones that run at least a 100-billion-parameter language model locally and continuously by 2028, adding that "AI companies are starting to do phones." He did not name those companies, and Qualcomm has not published a complete hardware plan or commercial phone roadmap for reaching that goal. The report notes a 4-bit quantized 100B model would need roughly 50GB of memory for its weights alone, before room for the OS, apps and context cache, while flagship phones typically offer 12GB to 16GB and DRAM supply is tight and expensive. Possible workarounds include more aggressive quantization, MoE expert offloading or keeping weights in flash storage loaded on demand, each with quality or speed trade-offs; Amon said a more realistic near-term step is distilled 20B-to-30B models, with thermals and battery life still limiting always-on operation.

   Wccftech · 🔥 0
3. Oct 8
   Liquid AI pitches on-device personal AI built on Liquid Context

   Liquid AI COO Jeffrey Li said at theCUBE's Fully Connected event that phones, wearables, PCs and cars capture the richest signals about users, making the edge the natural home for personal AI. The company's Liquid Context, optimized for Snapdragon processors, sits between models, agents and hardware, and uses Liquid AI's own models to decide what information to retain and how to compress it within fixed on-device compute. Liquid AI is also working with Mercedes-Benz on in-car on-device AI, and says it is building observability and continuous-improvement loops so models and agent harnesses can self-heal and personalize after deployment.

   SiliconANGLE AI · 🔥 0

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