Talking to AI agents is one thing — what about when they talk to each other? New startup Band debuts 'universal orchestrator'

Already, BAND's early users — and enterprises more broadly — are mixing and matching AI agents powered by models from various ...
Frontier Enterprise on MSN

Agentic AI: Scaling from pilots to production

Enterprises are struggling to scale agentic AI. Here’s what’s holding them back and what it takes to move from pilots to production. The post Agentic AI: Scaling from pilots to production appeared ...

Why Stanford Researchers Say AI Architecture Isn’t the Real Key to Performance

Discover how to audit and prune your LLM harness to achieve up to six times better performance without changing models.

Monitoring LLM behavior: Drift, retries, and refusal patterns

The offline pipeline's primary objective is regression testing — identifying failures, drift, and latency before production.
InfoWorld

Small language models: Rethinking enterprise AI architecture

As LLMs hit the limits of scale and cost, specialized SLMs are emerging as the faster, cheaper, and more private workhorse ...
TMCnet

MOREH Demonstrates Production-Ready LLM Inference on Tenstorrent Galaxy, Achieving DGX A100-Class Performance with Improved Cost Efficiency

Moreh, an AI infrastructure software company, led by CEO Gangwon Jo, announced that it has successfully validated LLM ...
Forbes

Why Metadata Is As Important As Data

When business leaders think about artificial intelligence, they often focus on models, platforms and compute capacity. That focus is understandable. AI has quickly become a board‑level mandate, tied ...
Semiconductor Engineering

Microarchitecture Tailored to 3D-Stacked Near-Memory Processing LLM Decoding (U. of Edinburgh, Peking U., Cambridge et al.)

A new technical paper, “Rethinking Compute Substrates for 3D-Stacked Near-Memory LLM Decoding: Microarchitecture-Scheduling ...