Tag Archives: AI research

Sixteen Claude AI agents working together created a new C compiler

Amid a push toward AI agents, with both Anthropic and OpenAI shipping multi-agent tools this week, Anthropic is more than ready to show off some of its more daring AI coding experiments. But as usual with claims of AI-related achievement, you’ll find some key caveats ahead. On Thursday, Anthropic researcher Nicholas Carlini published a blog… Read More »

From prophet to product: How AI came back down to earth in 2025

To be sure, it’s hard to see this not ending in some market carnage. The current “winner-takes-most” mentality in the space means the bets are big and bold, but the market can’t support dozens of major independent AI labs or hundreds of application-layer startups. That’s the definition of a bubble environment, and when it pops,… Read More »

Syntax hacking: Researchers discover sentence structure can bypass AI safety rules

Researchers from MIT, Northeastern University, and Meta recently released a paper suggesting that large language models (LLMs) similar to those that power ChatGPT may sometimes prioritize sentence structure over meaning when answering questions. The findings reveal a weakness in how these models process instructions that may shed light on why some prompt injection or jailbreaking… Read More »

Meta’s star AI scientist Yann LeCun plans to leave for own startup

A different approach to AI LeCun founded Meta’s Fundamental AI Research lab, known as FAIR, in 2013 and has served as the company’s chief AI scientist ever since. He is one of three researchers who won the 2018 Turing Award for pioneering work on deep learning and convolutional neural networks. After leaving Meta, LeCun will… Read More »

Researchers isolate memorization from reasoning in AI neural networks

Looking ahead, if the information removal techniques receive further development in the future, AI companies could potentially one day remove, say, copyrighted content, private information, or harmful memorized text from a neural network without destroying the model’s ability to perform transformative tasks. However, since neural networks store information in distributed ways that are still not… Read More »

Researchers surprised that with AI, toxicity is harder to fake than intelligence

The next time you encounter an unusually polite reply on social media, you might want to check twice. It could be an AI model trying (and failing) to blend in with the crowd. On Wednesday, researchers from the University of Zurich, University of Amsterdam, Duke University, and New York University released a study revealing that… Read More »

OpenAI wants to stop ChatGPT from validating users’ political views

The timing of OpenAI’s paper may not be coincidental. In July, the Trump administration signed an executive order barring “woke” AI from federal contracts, demanding that government-procured AI systems demonstrate “ideological neutrality” and “truth seeking.” With the federal government as tech’s biggest buyer, AI companies now face pressure to prove their models are politically “neutral.”… Read More »

AI models can acquire backdoors from surprisingly few malicious documents

Fine-tuning experiments with 100,000 clean samples versus 1,000 clean samples showed similar attack success rates when the number of malicious examples stayed constant. For GPT-3.5-turbo, between 50 and 90 malicious samples achieved over 80 percent attack success across dataset sizes spanning two orders of magnitude. Limitations While it may seem alarming at first that LLMs… Read More »

Why iRobot’s founder won’t go within 10 feet of today’s walking robots

In his post, Brooks recounts being “way too close” to an Agility Robotics Digit humanoid when it fell several years ago. He has not dared approach one while walking since. Even in promotional videos from humanoid companies, Brooks notes, humans are never shown close to moving humanoid robots unless separated by furniture, and even then,… Read More »

DeepSeek tests “sparse attention” to slash AI processing costs

The attention bottleneck In AI, “attention” is a term for a software technique that determines which words in a text are most relevant to understanding each other. Those relationships map out context, and context builds meaning in language. For example, in the sentence “The bank raised interest rates,” attention helps the model establish that “bank”… Read More »