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Fine-tuning a large language model (LLM) is the process of taking a pre-trained model — usually a vast one like GPT or Llama models, with millions to billions of weights — and continuing to train it, exposing it to new data so that the model weights (or typically parts of them) get updated. Source link
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Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More AI is a critical competitive advantage — and it’s time to find out how your company stacks up. The annual VentureBeat AI survey is back. The survey is brought to you by ActiveFence, a leader in…
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Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Google DeepMind today pulled the curtain back on AlphaEvolve, an artificial-intelligence agent that can invent brand-new computer algorithms — then put them straight to work inside the company’s vast computing empire. AlphaEvolve pairs Google’s Gemini large…
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Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Patronus AI launched a new monitoring platform today that automatically identifies failures in AI agent systems, targeting enterprise concerns about reliability as these applications grow more complex. The San Francisco-based AI safety startup’s new product, Percival,…
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Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Productivity platform Notion is betting on large language models (LLMs) powering more of its new enterprise capabilities, including building OpenAI’s GPT-4.1 and Anthropic’s Claude 3.7 into their dashboard. Even as both OpenAI and Anthropic start building…
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Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Generative AI is creating a digital diaspora of techniques, technologies and tradecraft that everyone, from rogue attackers to nation-state cyber armies trained in the art of cyberwar, is adopting. Insider threats are growing, too, accelerated by…
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Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Poe‘s latest usage report shows OpenAI and Google strengthening their positions in key AI categories while Anthropic loses ground and specialized reasoning capabilities emerge as a crucial competitive battleground. According to data released today by Poe,…
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Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More A new report released by the publicly traded market research and intelligence firm SimilarWeb—covering global web traffic patterns for AI-related platforms for 12 weeks through May 9, 2025—offers a helpful look for enterprises and interested users…
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Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Anthropic released Model Context Protocol (MCP) in Nov. 2024. In its seven months of existence, MCP seems to have become the winning protocol choice for the AI industry. Despite the number of companies announcing MCP servers, MCP…
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Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Hallucination is a risk that limits the real-world deployment of enterprise AI. Many organizations have attempted to solve the challenge of hallucination reduction with various approaches, each with varying degrees of success. Among the many vendors…