VentureBeat

Forget data labeling: Tencent’s R-Zero shows how LLMs can train themselves

A new training framework developed by researchers at Tencent AI Lab and Washington University in St. Louis enables large language models (LLMs) to improve themselves without requiring any ...
The Hindu

How are Indian firms training LLMs? | Explained

At the AI Impact Summit, the Bengaluru-based startup Sarvam AI released two Large Language Models (LLMs), which are the foundation for AI systems that power services like Google’s Gemini and OpenAI’s ...
XDA Developers on MSN

Local LLMs didn't save me time until I gave them a job they're actually good at

I'd been sleeping on local LLMs all this time ...
VentureBeat

Researchers find you don’t need a ton of data to train LLMs for reasoning tasks

Large language models (LLMs) can learn complex reasoning tasks without relying on large datasets, according to a new study by researchers at Shanghai Jiao Tong University. Their findings show that ...

How Narrow LLMs Are Powering Agentic AI Systems

Just as general-purpose models opened the era of practical AI, narrow, orchestrated models could define the economics and ...
TechRepublic

Cisco Talos Researcher Reveals Method That Causes LLMs to Expose Training Data

Cisco Talos Researcher Reveals Method That Causes LLMs to Expose Training Data Your email has been sent In this TechRepublic interview, Cisco researcher Amy Chang details the decomposition method and ...
SiliconANGLE

OpenAI finds DeepSeek used its data to train R1 reasoning model

OpenAI believes its data was used to train DeepSeek’s R1 large language model, multiple publications reported today. DeepSeek is a Chinese artificial intelligence provider that develops open-source ...
Forbes

Powering LLMs: Four Considerations When Building A Data Infrastructure

As more organizations implement large language models (LLMs) into their products and services, the first step is to understand that LLMs need a robust and scalable data infrastructure capable of ...
Security Boulevard

Inference protection for LLMs: Keeping sensitive data out of AI workflows

Inference protection is a preventive approach to LLM privacy that stops sensitive data from ever reaching AI models. Learn how de-identification enables secure, compliant AI workflows with ...
Futurism

If Even 0.001 Percent of an AI’s Training Data Is Misinformation, the Whole Thing Becomes Compromised, Scientists Find

It’s no secret that large language models (LLMs) like the ones that power popular chatbots like ChatGPT are surprisingly fallible. Even the most advanced ones still have a nagging tendency to contort ...