venturebeat
Scaling AI into production is forcing a rethink of enterprise infrastructure

Presented by NutanixAcross industries, organizations are focused on how to move from AI pilots, proofs of concept, and cloud-based experimentation to deploying it at scale — across real workloads, for real users, in real business environments. VentureBeat spoke with Tarkan Maner, president and chief commercial officer at Nutanix, and Thomas Cornely, EVP of product management, about what that transition demands, and what it will take to get it right.“AI in general is shifting everything we do, not only in technology, but across all vertical industries, from regulated industries like banking, health care, government, education to non-regulated industries like manufacturing and retail,” Maner said. “As a complete platform company, we welcome this change. It’s creating more opportuni [...]

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venturebeat
Vercel rebuilt v0 to tackle the 90% problem: Connecting AI-generated code to existing production infrastructure, not prototypes

Before Claude Code wrote its first line of code, Vercel was already in the vibe coding space with its v0 service.The basic idea behind the original v0, which launched in 2024, was essentially to be ve [...]

Match Score: 97.60

venturebeat
Perplexity takes its ‘Computer’ AI agent into the enterprise, taking aim at Microsoft and Salesforce

Perplexity, the AI-powered search company valued at $20 billion, announced on Wednesday at its inaugural Ask 2026 developer conference that its multi-model AI agent, Computer, is now available to ente [...]

Match Score: 93.89

venturebeat
Train-to-Test scaling explained: How to optimize your end-to-end AI compute budget for inference

The standard guidelines for building large language models (LLMs) optimize only for training costs and ignore inference costs. This poses a challenge for real-world applications that use inference-tim [...]

Match Score: 87.06

venturebeat
5% GPU utilization: The $401 billion AI infrastructure problem enterprises can't keep ignoring

For the last 24 months, one narrative justified every over-provisioned data center and bloated IT budget: the GPU scramble. Silicon was the new oil, and H100s traded like contraband. Reserve capacity [...]

Match Score: 83.17

venturebeat
Mistral AI launches Workflows, a Temporal-powered orchestration engine already running millions of daily executions

Mistral AI, the Paris-based artificial intelligence company valued at €11.7 billion ($13.8 billion), today released Workflows in public preview — a production-grade orchestration layer designed to [...]

Match Score: 77.33

venturebeat
GitHub leads the enterprise, Claude leads the pack—Cursor’s speed can’t close

In the race to deploy generative AI for coding, the fastest tools are not winning enterprise deals. A new VentureBeat analysis, combining a comprehensive survey of 86 engineering teams with our own ha [...]

Match Score: 69.02

venturebeat
Cheaper tokens, bigger bills: The new math of AI infrastructure

Presented by NutanixAs enterprises move from AI experimentation into production deployment, the primary cost driver has shifted away from foundation model training and toward the infrastructure requir [...]

Match Score: 66.80

venturebeat
New memory framework builds AI agents that can handle the real world's unpredictability

Researchers at the University of Illinois Urbana-Champaign and Google Cloud AI Research have developed a framework that enables large language model (LLM) agents to organize their experiences into a m [...]

Match Score: 65.67

venturebeat
NanoClaw and Docker partner to make sandboxes the safest way for enterprises to deploy AI agents

NanoClaw, the open-source AI agent platform created by Gavriel Cohen, is partnering with the containerized development platform Docker to let teams run agents inside Docker Sandboxes, a move aimed at [...]

Match Score: 64.20