How AI Inference Sends Decision Making To The Edge

The next phase of AI infrastructure will not be defined by a single destination called “the cloud” or “the edge.” ...
TechCrunch

Tether is pushing the 13-billion parameter BitNet b1.58 LLM to the edge.

Tether released a fine-tuning framework for Microsoft’s BitNet b1.58 LLM that works on any GPUs and consumer-grade handheld devices. For the first time, the model can be fine-tuned efficiently across ...
Tech Times

LLM Data Mixture Breaks When Training Pools Shift: Causal Inference Offers Fix

LLM training data mixture optimization breaks when training pools shift — every prior proxy experiment becomes stale.
SiliconANGLE

Kneron’s new AI chip brings LLM performance out of the cloud and onto devices

San Diego-based startup Kneron Inc., an artificial intelligence company pioneering neural processing units for the edge, today announced the launch of its next-generation KL1140 chip Founded in 2015, ...
Semiconductor Engineering

Small Language Models: A Solution To Language Model Deployment At The Edge?

While Large Language Models (LLMs) like GPT-3 and GPT-4 have quickly become synonymous with AI, LLM mass deployments in both training and inference applications have, to date, been predominately cloud ...
Nasdaq

Akamai Sharpens Its AI Edge with Launch of Akamai Cloud Inference

New service gives companies the ability to realize a 3x improvement in throughput, 60% less latency, and 86% lower cost than traditional hyperscale infrastructure CAMBRIDGE, Mass., March 27, 2025 ...
InfoWorld

Partitioning an LLM between cloud and edge

Using edge systems to run elements of generative AI could be game-changing. It requires planning and skill, but this hybrid approach may be the future. Historically, large language models (LLMs) have ...