// edge computing

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May 18

T-Mobile Deploys Edge Computing for Real-Time In-Store Retail Ads

Source: Beet

T-Mobile is positioning edge computing infrastructure as the missing link between physical retail's massive transaction volume and fragmented digital ad targeting, betting that latency-free processing of customer data inside stores will unlock retail media spending currently locked in online channels. This strategy addresses a specific problem: major retailers have the foot traffic but lack the real-time decisioning layer to serve personalized ads at shelf speed, while media buyers default to easier-to-measure digital platforms. If T-Mobile can deliver attribution and performance data from in-store devices faster than cloud-dependent competitors, it stands to shift how the $30B+ retail media industry allocates investment between e-commerce and physical locations.

theme-ai llm capabilities model optimization edge computing

May 11

Local LLMs offer practical alternative to scaling cloud infrastructure

Source: The Register: Biting the hand that feeds

As cloud AI inference costs mount, consumer-grade laptops running open-source language models are becoming viable for routine tasks—not as cost-cutting alone but as a technical reality that sidesteps the infrastructure arms race. This fragments the market away from centralized API providers like OpenAI and Anthropic, forcing those companies to compete on capability and safety rather than compute monopoly, while shifting the burden of model management and hardware investment to users. Local models only work at scale because open-source alternatives have closed the quality gap enough for non-specialized use cases. The shift away from centralized dominance is already underway.