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Deep insights for enterprise AI, data, and security leaders
How enterprises coordinate and scale AI in production.

GitHub Copilot Fusion mixes models to achieve near-Opus 5.5 coding performance at half the per-task cost

Salesforce expands Agent Fabric with AI evaluations to trigger shutdowns when agents fail

A coding agent’s harness can triple its cost without making it more accurate, study finds

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The best enterprise AI is the AI employees barely notice
Presented by Capital One
The hardware and platforms underneath enterprise AI.

Nvidia and Oracle expand Vera Rubin cloud infrastructure, pitching better utilization as enterprises report idle GPUs

AI bubble update: 79% of companies say their GPUs sit idle at least half the time, yet most plan new AI platforms

Nvidia is pitching AI factories, but 81% of companies say their GPUs run at half capacity or less

AWS just made it way easier to use SageMaker to fine-tune AI models for tool use and your firm's specific tasks

Keeping Pace With AI: The Skills and Workflows Teams Need Now


Cohere's test caught an open source Qwen3.8 model trying to 'phone home' to China: what enterprises should know

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Borderless data architectures: Empowering AI agents where your data lives
Presented by Google Cloud

CTGT releases open source tool Concordance to trace why AI agents make inconsistent decisions

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Agents are rewriting the book on security. Can your data layer keep up?
Presented by Google Cloud

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AI agent access is moving faster than identity controls can govern
Presented by 1Password

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AI agents are about to put least privilege to the test
Presented by JumpCloud

DeepSeek-V4.1-Flash-1017 arrives with improved benchmarks just as the U.S. government bans it from agencies — what enterprises should do
Enterprise tech coverage through the lens of AI adoption.

Google unveils Gemini 4 Carbon, retaking the world's no. 1 spot on updated, harder benchmarks — but access is limited

Liquid AI’s new LFM3 models put browser agents, voice commands, and image recognition onto local devices

Anthropic files to go public on NASDAQ as $ANT with $16.3B in revenue for first six months of 2026

Moonshot's Kimi K3.1 Pro flirts with open weights leadership amid paid influencer scandal allegations
LiveX Unveils AI City - Bringing Physical AI to Everyday Spaces with NVIDIA
Cross Country Appoints Craig Meier as Chairman of the Board
Duets Launches a New Ecosystem for Startups Building in Sports and Entertainment
Brilliant Labs Launches Halo Glasses, A New Generation of Privacy-First Smartglasses
More

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AI agents can have accurate data — and still make the wrong business decision
Presented by SAP

Researchers made AI agents better by turning academic papers into working code — no retraining required

Anthropic’s answer to Muse is here: Claude Duet, a mobile and desktop AI agent that takes actions proactively

Deel launches Pangaea AI models for HR and payroll, betting specialists can cut the cost of answers by 98%
Scaling AI agents requires three things: Inventory, contracts and maintained context
Enterprises that run more than a handful of AI agents in production face risk, cost and oversight burdens that grow exponentially with every agent they add, says Felix Van de Maele, founder and CEO of data governance company Collibra. In a conversation with VentureBeat founder and CEO Matt Marshall at VentureBeat's AI Week event in New York, Van de Maele traced most agent failures to the business context those agents receive — and said companies need deterministic controls on agent behavior before their agent count grows.

Google and Synaptics unveil new AI chips for wearables and industrial devices, powered by open-source Coral technology

fal launches FLUX 3 Max, claiming 22× faster AI video generation than Seedance 2.5

AI cloud security needs to prove control before agents reach production
As confidential computing comes to GPUs, it can protect sensitive workloads, but enterprises also need evidence that they can identify agents, isolate tenants and revoke access without disrupting operations.



