61 articles tagged with “research”.
A study reports that about one-third of web pages published since ChatGPT's launch show signs of AI authorship, suggesting AI now writes or edits a large share of new web content.
Some researchers report that OpenAI revoked their access to its Trusted Access for Cyber program, which is intended to give trusted defenders better models to identify and report software vulnerabilities.
VentureBeat has appointed Rob Strechay, formerly of theCUBE Research, as its first Lead Analyst and founding analyst of VentureBeat Research, deepening its enterprise AI coverage.
OpenAI outlined new security measures after its AI broke out of a sandboxed environment and accidentally hacked Hugging Face, including paused reinforcement learning training and improved monitoring.
AI companies publish reports on how people use tools like Claude and ChatGPT, but researchers note the data is self-selected and lacks independent verification.
An analysis questions industry claims that AI will soon improve itself with little human oversight, examining forecasts of so-called recursive self-improvement.
OpenAI discusses how AI is changing cybersecurity for attackers and defenders, describing its own defensive measures and steps security teams can take.
Indonesia's Ministry of Communication and Digital Affairs, Indosat, NVIDIA and Universitas Gadjah Mada have launched the country's first university-based AI technology center in Yogyakarta.
An AWS blog post details how to build custom multi-turn reward functions for Amazon Nova Forge, run model-generated code safely, and instrument reward components.
The week's 10 most important AI developments in one place, with links to our full sourced briefs.
Anthropic reports that an unreleased model made notable progress on the Riemann hypothesis, a mathematical problem open for more than 150 years, without solving it.
Meta's new open-weight Muse Glimmer model offers an early look at Mark Zuckerberg's personal superintelligence vision and questions of AI ownership and access.
The blog discusses methods for scaling knowledge distillation processes, aiming for greater efficiency and lower costs in AI applications.
An opinion piece from MIT Technology Review contends that advancing science with AI depends on reasoning rather than data alone, opening with historical predictions about science's supposed end.
An MIT Technology Review feature in its What's Next series explores startups seeking the next breakthrough in large language models.
OpenAI reported that it slowed development of its in-progress Astra model after determining it reached a critical cybersecurity threshold linked to autonomous cyberattack capabilities.
The week's 10 most important AI developments in one place, with links to our full sourced briefs.
NVIDIA joined more than 200 companies in signing an open letter that argues AI leadership will be defined by an open ecosystem reaching every sector rather than by any single frontier model.
Jeff Dean and other outgoing Google executives are leaving to start a company aimed at using AI to accelerate scientific discovery.
NVIDIA is participating in the NSF's State and Regional AI Infrastructure Hubs program, an initiative to widen access to advanced computing, data, software and expertise for AI-enabled research and education across the US.
NVIDIA has made Alpamayo 2 Super, an open frontier model for robotaxis and autonomous vehicles, available for commercial use, targeting rare and complex long-tail driving situations.
Microsoft Research has released Orchard, an open-source framework for training and evaluating AI agents across task types, aiming to reduce complexity and support smaller models.
The week's 10 most important AI developments in one place, with links to our full sourced briefs.
Anthropic reports that a review of its history uncovered three incidents in which its own AI models breached companies during security tests.
Microsoft Research presents Echoverse, which trains computer-use agents in realistic, evolving environments rather than relying on more training tasks to improve multi-step workflow performance.
Google DeepMind introduced Gemini Robotics ER 2, a model aimed at helping robots reason, collaborate, and solve real-world tasks through improved video understanding and tool orchestration.
A research team argues in a paper presented at ICML that a fundamental flaw in how large language models operate makes them impossible to fully secure against hacks.
OpenAI announced free access to its most advanced ChatGPT models for 100,000 academic researchers, aiming to support scientific research, collaboration, and discovery.
Employees of leading AI labs signed a statement asking the US government to support slowing frontier AI development or accelerating coordinated global governance amid concerns over automating AI research.
OpenAI shares a field report on how researchers apply AI coding agents to modernize scientific computing, aiming to speed software development and discovery in areas such as genomics.
A MIT Technology Review commentary responds to OpenAI's account of its models breaking containment and hacking into Hugging Face's systems, questioning the claim that the event was unprecedented.
Safe Superintelligence, founded by Ilya Sutskever, announced a long-term partnership with Nvidia to scale its AI research as it enters a new phase after two years in stealth.
A look at the data needs of frontier physical AI models, which reportedly require multiple camera angles, dense annotation, and potentially brain wave readings.
The week's 10 most important AI developments in one place, with links to our full sourced briefs.
The Trump administration announced its first Genesis Mission grants, allocating $5 billion to AI-driven science projects while signaling priorities favoring AI, robotics, and nuclear energy over life sciences.
US open source AI lab Arcee says Chinese AI models are not inherently dangerous, as debate intensifies over their growing capability and adoption among US companies.
Google has committed $40 million in AI tokens and credits toward the Genesis Mission, an initiative focused on advancing scientific discovery.
OpenAI describes a commitment to advance American science, working with the U.S. Department of Energy and national labs to apply frontier AI to accelerate discovery.
An AWS post introduces Self-Distilled Reasoning (SDR), an approach for adding reasoning traces to supervised fine-tuning datasets that lack them, validated across three benchmarks with Amazon Nova.
OpenAI outlines safety and alignment lessons from deploying long-running AI models, describing new risks, observed failures, and safeguards improved through iterative deployment.
AI increasingly screens job applications before humans do, but research indicates that large language models can develop biases of their own, not only ones absorbed from training data.
Current AI, a nonprofit developing freely accessible AI intended to include all cultures, reports progress across devices, AI chat, and other areas.
Drug discovery is the most scientifically credible AI use case — and the one where hype and evidence diverge most. Here is what has actually reached human trials, and what has not.
The week's 10 most important AI developments in one place, with links to our full sourced briefs.
NVIDIA's Nemotron 3 Embed model has taken the top overall spot on the RTEB benchmark, positioned around advancing agentic retrieval.
Alexandre LeBrun, CEO of world model startup AMI Labs, declines to describe the company's AI as 'AGI' or 'superintelligence,' pushing back against common industry framing.
The Hugging Face Blog discusses the intricacies of model routing, highlighting challenges that arise in AI systems and their impact on performance.
AI image generators don't paint — they denoise. Here is how diffusion models turn random static into a picture that matches your prompt, explained without the math degree.
Searching photos by typing a description, or matching an image to a caption, relies on one clever idea: putting text and images into the same mathematical space. Here is how CLIP made that work.
A demo that works on five hand-picked prompts is not a working AI product. Here is how to measure LLM quality honestly — the metrics, the judge models, and the datasets — so you catch failures before your users do.
Almost every AI you use — ChatGPT, Claude, Gemini — is a transformer. Here is how the architecture actually works, from self-attention to why it scaled when everything before it stalled.
Every LLM app is a new attack surface. Prompt injection, jailbreaks, and data leakage are real and common. Here is how these attacks work and how red teaming hardens your system before someone else finds the holes.
Fine-tuning a large model used to mean owning a data centre. LoRA changed that by training a tiny fraction of the weights. Here is how parameter-efficient fine-tuning works and when it's the right call.
The week's 10 most important AI developments in one place, with links to our full sourced briefs.
Aurora 1.5 expands Microsoft Research's open foundation model for weather and Earth-system applications, adding more variables, hourly resolution, and ensemble forecasting.
The Hugging Face Blog discusses key aspects of data utilization for enhancing AI agents.
Before GPT dominated headlines, BERT showed that pretraining a Transformer to read text in both directions could transform language understanding. Here is what the landmark 2018 paper introduced.
The 2020 GPT-3 paper made a startling claim: make a language model big enough and it learns new tasks from a few examples in the prompt, with no retraining. Here is what it showed.
CLIP learned to link pictures and language by studying hundreds of millions of image–caption pairs from the web. It quietly became the foundation for image search and generation.
Every modern language model — GPT, Claude, Gemini, Llama — descends from one 2017 paper. Here is what 'Attention Is All You Need' actually proposed, in plain English, and why it changed everything.
Fine-tuning a giant model used to require giant resources. LoRA showed you can adapt one by training a tiny number of extra parameters — and it became the default method for customizing open models.