We’ve heard (and written, here at VentureBeat) lots about the generative AI race between the U.S. and China, as those have been the countries with the groups most active in fielding new models (with a shoutout to Cohere in Canada and Mistral in France). But now a Korean startup is making waves: last week, the …
Korean AI startup Motif reveals 4 big lessons for training enterprise LLMs Read More »
Presented by Twilio The customer data infrastructure powering most enterprises was architected for a world that no longer exists: one where marketing interactions could be captured and processed in batches, where campaign timing was measured in days (not milliseconds), and where “personalization” meant inserting a first name into an email template. Conversational AI has shattered …
Why agentic AI needs a new category of customer data Read More »
Presented by Capital One Software Tokenization is emerging as a cornerstone of modern data security, helping businesses separate the value of their data from its risk. During this VB in Conversation, Ravi Raghu, president, Capital One Software, talks about the ways tokenization can help reduce the value of breached data and preserve underlying data format …
Tokenization takes the lead in the fight for data security Read More »
Nvidia launched the new version of its frontier models, Nemotron 3, by leaning in on a model architecture that the world’s most valuable company said offers more accuracy and reliability for agents. Nemotron 3 will be available in three sizes: Nemotron 3 Nano with 30B parameters, mainly for targeted, highly efficient tasks; Nemotron 3 Super, …
Picture this: You’re sitting in a conference room, halfway through a vendor pitch. The demo looks solid, and pricing fits nicely under budget. The timeline seems reasonable too. Everyone’s nodding along. You’re literally minutes away from saying yes. Then someone from your finance team walks in. They see the deck and frown. A few minutes …
Gen AI in software engineering has moved well beyond autocomplete. The emerging frontier is agentic coding: AI systems capable of planning changes, executing them across multiple steps and iterating based on feedback. Yet despite the excitement around “AI agents that code,” most enterprise deployments underperform. The limiting factor is no longer the model. It’s context: …
Why most enterprise AI coding pilots underperform (Hint: It’s not the model) Read More »
In a new paper that studies tool-use in large language model (LLM) agents, researchers at Google and UC Santa Barbara have developed a framework that enables agents to make more efficient use of tool and compute budgets. The researchers introduce two new techniques: a simple “Budget Tracker” and a more comprehensive framework called “Budget Aware …
Google’s new framework helps AI agents spend their compute and tool budget more wisely Read More »
The Allen Institute for AI (Ai2) recently released what it calls its most powerful family of models yet, Olmo 3. But the company kept iterating on the models, expanding its reinforcement learning (RL) runs, to create Olmo 3.1. The new Olmo 3.1 models focus on efficiency, transparency, and control for enterprises. Ai2 updated two of …
OpenAI has officially released GPT-5.2, and the reactions from early testers — among whom OpenAI seeded the model several days prior to public release, in some cases weeks ago — paints a two toned picture: it is a monumental leap forward for deep, autonomous reasoning and coding, yet potentially an underwhelming “incremental” update for casual …
Nous Research, the San Francisco-based artificial intelligence startup, released on Tuesday an open-source mathematical reasoning system called Nomos 1 that achieved near-elite human performance on this year’s William Lowell Putnam Mathematical Competition, one of the most prestigious and notoriously difficult undergraduate math contests in the world. The Putnam is known for its difficulty: While a …