Open-Weight LLM Showdown: RTX 5090 Finally Delivers, But You Can't Buy One
Two weeks after our last roundup, the 5090 benchmarks are in and Qwen 3.5 Small models are running on phones. Here's the real performance picture.
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Grok 4.20 Turns AI Into a Debate Team: Four Agents Argue Before Answering
xAI's new multi-agent architecture pits four specialized AI agents against each other in real-time debate, claiming 65% fewer hallucinations
Your Anonymous Internet Account Isn't Anonymous Anymore
New research shows AI can link your Reddit burner account to your real identity for under $4. The era of casual online pseudonymity may be ending.
Your Burner Account Won't Save You: AI Can Unmask Anonymous Users for $4
New research from ETH Zurich and Anthropic shows AI can identify pseudonymous online accounts with 67% accuracy at just $1-4 per person - and there's no easy fix.
MiniMax M2.5: The Open-Source Model That Rivals Claude at 1/20th the Cost
Chinese AI startup MiniMax has released M2.5, an open-weights model matching Claude Opus performance for coding and agentic tasks while costing 95% less to run
Open-Weight LLM Showdown: What Actually Runs on Your GPU (March 2026)
GLM-5, Qwen 3.5, DeepSeek V3.2, and MiniMax M2.5 are rewriting the rules. Here's what they actually deliver on consumer hardware.
PsychAdapter: The AI That Can Fake Your Personality With 98% Accuracy
Researchers have created an AI system that can generate text mimicking specific personality traits and mental health conditions. The implications for manipulation and misinformation are troubling.
The Invisible Censor: How China's AI Chatbots Are Programmed to Forget
Stanford and Princeton researchers found Chinese AI models refuse politically sensitive questions at rates up to 60% compared to under 3% for Western models - and the censorship goes beyond training data.
MIT's AI Learns Yeast DNA Language to Cut Protein Drug Manufacturing Costs
An LLM trained on yeast genetics outperforms commercial tools at optimizing codon sequences for protein production. Five out of six test cases beat existing solutions.
Longer Isn't Smarter: Google Research Shows Token Count Predicts Failure, Not Success
New research from Google and UVA reveals that longer AI reasoning traces actually correlate with wrong answers. The fix: measure how deeply the model thinks, not how much it writes.
AI Chatbots Analyzed Medical Data Faster Than Human Teams, UCSF Study Finds
Half of the tested AI tools produced prediction models that matched or beat human researchers. A master's student and high schooler built working code in minutes.
88% of AI-Generated Passwords Can Be Cracked Within an Hour
Kaspersky research reveals that passwords from ChatGPT, DeepSeek, and Llama lack true randomness. The same prediction capability that makes LLMs useful makes them terrible at generating secure passwords.
DeepRare AI Diagnoses Rare Diseases Faster Than Doctors
Chinese researchers built an AI system using 40+ specialized tools that correctly identifies rare diseases in first attempt 64% of the time vs 55% for experienced physicians.
GLM-5: China's 744B Open-Source Model Trained Entirely on Huawei Chips
Zhipu AI releases GLM-5 under MIT license, a frontier model rivaling Claude and GPT-5 while proving China can build top-tier AI without NVIDIA hardware.
AI Models Accept Medical Misinformation 32% of the Time, Study Finds
Mount Sinai researchers tested 20 LLMs with over a million prompts and found they readily accept false medical claims embedded in clinical-looking documents.
Google's Gemini 3.1 Pro Doubles Reasoning Performance, Retakes Benchmark Crown
Google's latest model scores 77% on ARC-AGI-2, more than double its predecessor. At $2 per million tokens, it undercuts competitors while outperforming them on most tests.
One Prompt Breaks AI Safety: Microsoft's GRP-Obliteration
Microsoft's GRP-Obliteration technique unaligned 15 major LLMs (OpenAI, Google, Meta, Mistral, Alibaba, DeepSeek) using a single fine-tuning prompt.
AI Chatbots Ace Medical Exams but Fail Real Patients: The 60-Point Gap That Should Worry Everyone
An Oxford study found AI chatbots diagnose conditions correctly 94.9% of the time on paper, but only 34.5% when talking to actual people. The implications for AI benchmarks extend far beyond medicine.