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Enterprise AI's real risk isn't autonomous agents. It's the complexity between them.
Presented by Gravitee
Rory Blundell, Gravitee
Partner Content
When agents act on their own, governance has to live in the data layer
Presented by EDB
Max Romanenko, EDB
Partner Content
Orchestration is the new challenge for CX in the age of AI agents
Presented by Tata Communications
VB Staff
VentureBeat names Rob Strechay as its first Lead Analyst, expanding its enterprise AI research push
Rob Strechay, until recently managing director and principal analyst at theCUBE Research, has joined VentureBeat as our first Lead Analyst and a founding analyst of VentureBeat Research. His arrival is the next step in a deliberate move at VentureBeat toward deeper specialization: analysis built for the technical decision-makers — the directors, VPs, CIOs, and CTOs — who are evaluating, buying, and deploying enterprise AI.
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Deep insights for enterprise AI, data, and security leaders
New Tool Recommendation system cuts your firm's input token costs by 37%, according to Arcade.dev
The distinction Arcade emphasizes is packaging discovery with execution controls in a layer customers can use across their chosen AI systems.
Carl Franzen
Black Forest Labs opens FLUX 3 Image Klein weights, with free commercial use limited to smaller businesses
That makes Klein an additional option for local AI imagery, but the ability to download its weights does not give every business unrestricted commercial rights.
Carl Franzen
NVIDIA's new, open Nemotron 3.5 Super VL with post-training beats Claude Opus 5, GPT-6.1 Sol on specialized task benchmarks
NVIDIA has shown a coherent set of models for testing those possibilities; enterprises still need the licensing, deployment details and workload results to decide whether to build on it.
Carl Franzen
OpenAI's AI agent platform is used by twice as many companies as Anthropic's, new VentureBeat survey finds
Twice as many companies use OpenAI's agent orchestration platform as Anthropic's, VentureBeat Intelligence found in its September survey on agent orchestration. OpenAI holds that lead even though Anthropic may lead OpenAI on other important indicators. For example, Ramp, the corporate card and spending company, reports that more businesses now pay for Anthropic than for OpenAI.
Matt Marshall
Google makes Gemini 4 Argon broadly available with limited-time low API pricing of $2/$10 per 1M token
The Gemini app gains more agentic functionality, including persistent tasks that can continue while users are away from their computers and connections to more than 40 external applications.
Carl Franzen
Partner Content
Agents need more than business process knowledge. They need to understand how your company actually works
Presented by SAP
VB Staff
Your AI agents can execute every tool call correctly and still break every enterprise rule
If you sit in enterprise boardrooms today, the pressure weighing on CIOs comes down to two things: Velocity and ROI. Boards expect a mature agentic AI strategy and a definitive timeline for deploying autonomous systems that deliver measurable business impact.
Gabe Monroy
Meta's new Muse Wonder and Muse Wonder Full models achieve frontier performance, but only the weaker one is available via API
The company has not announced a pay-as-you-go API price for its most powerful model. Instead, Full is currently available through two Muse Code subscription tiers:
Carl Franzen
AI agents can be unpredictable. Your control layer shouldn't be.
In multi-agent systems, agents can be individually correct and still produce a wrong result when they work together. One agent’s output becomes another agent’s context. Information can be lost or misinterpreted during a handoff, shared state can drift, and agents can get stuck in loops or deadlocks. When several agents rely on the same underlying model, they may even reinforce the same mistakes rather than catch them.
Shuhua Xu
H-JEPA teaches world models to plan at multiple levels of abstraction
Researchers at Yann LeCun’s Advanced Machine Intelligence (AMI) Labs and academic institutions have developed H-JEPA, a world-model architecture that learns to plan at different timescales using separate representations of the environment.
Ben Dickson
Why giving AI agents more compute isn't enough—and what Meta proposes instead
AI agents often struggle to assess their own progress and decide what to do next. They can waste compute resources following failed approaches, or they might overlook promising results or stop before completing a task. These problems become more costly as agents take on longer and more complex workflows.
Ben Dickson
Magnific One launches to give teams an image generator that avoids the 'AI look' and automatically upholds their brand kit
A system that centralizes those guidelines, identifies deviations and allows employees to correct the results could make AI generation more practical for campaigns requiring large numbers of creative assets.
Carl Franzen