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The Innovation Showcase is back at Transform 2026: The Orchestration of Enterprise Agentic AI at Scale, taking place July 14 and 15 in Menlo Park. This year, we are moving beyond generative AI to autonomous agents, focusing on enterprise agentic orchestration, LLM observability and evaluation (LLMOps), RAG infrastructure, inference platforms and optimization, and agentic AI…

Getting AI agents to perform reliably in production — not just in demos — is turning out to be harder than enterprises anticipated. Fragmented data, unclear workflows, and runaway escalation rates are slowing deployments across industries. “The technology itself often works well in demonstrations,” said Sanchit Vir Gogia, chief analyst with Greyhound Research. “The challenge…

The prevailing assumption in AI development has been straightforward: larger models trained on more data produce better results. Nvidia’s latest release directly challenges that size assumption — and the training recipe behind it may matter more to enterprise AI teams than the model itself. The open-weight model’s Cascade RL post-training pipeline, detailed in Nvidia’s technical…

Not long ago, the idea of being a “generalist” in the workplace had a mixed reputation. The stereotype was the “jack of all trades” who could dabble in many disciplines but was a “master of none.” And for years, that was more or less true.  Most people simply didn’t have access to the expertise required…

Look, we’ve spent the last 18 months building production AI systems, and we’ll tell you what keeps us up at night — and it’s not whether the model can answer questions. That’s table stakes now. What haunts us is the mental image of an agent autonomously approving a six-figure vendor contract at 2 a.m. because…

Large language models are running into limits in domains that require an understanding of the physical world — from robotics to autonomous driving to manufacturing. That constraint is pushing investors toward world models, with AMI Labs raising a $1.03 billion seed round shortly after World Labs secured $1 billion. Large language models (LLMs) excel at…

Voice AI is moving faster than the tools we use to measure it. Every major AI lab — OpenAI, Google DeepMind, Anthropic, xAI — is racing to ship voice models capable of natural, real-time conversation. But the benchmarks used to evaluate those models are largely still running on synthetic speech, English-only prompts, and scripted test…

Enterprises that have been juggling separate models for reasoning, multimodal tasks, and agentic coding may be able to simplify their stack: Mistral’s new Small 4 brings all three into a single open-source model, with adjustable reasoning levels under the hood. Small 4 enters a crowded field of small models — including Qwen and Claude Haiku…

The hit open source autonomous AI agent OpenClaw may have just gotten mogged by Anthropic. Today, Anthropic announced Claude Code Channels, a way to hook up its own powerful Claude Code AI agentic harness to a human user’s Discord or Telegram messaging applications, letting them message Claude Code directly whenever they want while on the…

The future of AI isn’t just agentic; it’s deep personalization.  Rather than simple recommender systems that correlate user behavior to identify patterns and apply those to individual workflows, large language models (LLMs) and AI agents can analyze users directly to create deeply personalized experiences.  It’s this kind of aggressive customization users are increasingly demanding —…