132 summarised stories about AI Efficiency, each linking back to the original source. Browse all topics →
Ars Technica 1 month ago 25 ● 7 sources
Apple released the iPhone 18 Pro with updated camera controls and a new A20 Pro chip. The A20 Pro is Apple’s first 2 nm iPhone chip. As a result, users get a variable aperture camera and improved AI/ML processing via a larger Neural Engine design, alongside faster CPU and GPU performance.
Product Hunt 1 month ago 34
Desert Ant Labs launched a free SDK for building small AI models that can run on a phone or in a browser without internet. It offers free usage up to 100k monthly active devices. As a result, developers can plug in task-specific speech, text, and vision models in a few lines of code with no per-use cost.
The Verge 1 month ago 33
Dyson’s CameraJet AI-powered toothbrush is failing for some early buyers because water is getting into the battery compartment. The reported price is $499.99 and one user said their unit broke within 30 seconds. The result is that multiple units show similar wet-battery failures, and customers are reporting faulty batches.
Dwarkesh Podcast 1 month ago 10
Researchers compared pretraining recipes and data corpora from 2019 to 2025 and found more of the compute-efficiency gains came from data than from model changes. Data improvements contributed 3.24x more compute efficiency gains than model improvements (12.0x for data vs 3.7x for models) at a 1e19 FLOPs budget. The study concludes data and model improvements are mostly independent additively (88% of OLMES score variance explained), so progress is increasingly driven by better data engineering rather than interacting with specific model tweaks.
Cohere 1 month ago 2
Cohere released a serving engine for its North Mini Code model built around a decode megakernel running BF16 on a single H100. On batch size 1 it reached 292 tok/s, or 62% of the H100’s bandwidth ceiling (SoL), and was about 1.58× faster than vLLM end-to-end. The serving stack changes from many small decode kernels with synchronization gaps to a single persistent kernel that uses task-level scheduling and synchronization to raise decode throughput without measurable accuracy loss.
Katelyn Lesse 1 month ago 33
The tech industry is facing a CPU supply shortage that is tightening infrastructure bottlenecks for software teams, including agentic workloads. Server orders are quoting about 6 months and prices are up roughly 10–20% since March. Teams now need to forecast and capacity-plan CPU usage earlier, optimize how capacity is isolated and utilized, and improve cluster bring-up and software efficiency.
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TLDRocket
17 October 2026
The big thread today is the messy middle between agent ambitions and the boring parts that make them safe and auditable. ServiceNow is positioning its AI Control Tower as the enterprise hub to discover, govern, and—crucially—control AI agents across models and clouds, while a field study of 15 large-enterprise customers (conducted September 15–21, 2026) presses on a key question: how strong is “technical runtime enforcement” and lifecycle evidence compared with other tools? ServiceNow’s answer is mostly commercial muscle—aiming for $1.5B in full-year AI ACV—but its guidance effectively says buyers should treat Control Tower as strongest for governance workflows and operational action, then verify where model validation evidence and real-time blocking are actually handled.
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