Research & Benchmarks - Page 12 of 35
Academic AI research, performance benchmarks, scientific breakthroughs, and peer-reviewed studies advancing artificial intelligence frontiers.
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Data2Story converts CSVs to articles with 7 AI; 53 readers prefer them to human
The numbers are stark. Fifty-three readers, when given a choice, preferred the machine. Not just any machine, a seven-agent AI system called Data2Story that ingests a CSV and spits out a full, interactive news article.
M* introduces overlapped scheduling to streamline multimodal model serving
Multimodal models are slow. The real problem isn't the math. It's the wait. The GPU sits idle while the CPU schedules the next batch, a tax paid on every loop. M* cuts that tax.
Benchmark shows Claude Fable 5 passes only 3% of tasks, 31 of 91 fail 50%
Claude Fable 5 achieved perfection exactly three times. That’s the stark finding from a new benchmark testing 91 real-world tasks, where the top model’s flawless scorecard reads a paltry 3%.
Nobel laureate John Jumper departs DeepMind for Anthropic after AlphaFold win
Winning a Nobel Prize buys you a golden ticket. John Jumper just cashed his in at Anthropic’s door.
OpenAI shows small 'beneficial trait' training makes AI safer, less manipulable
Engineers at OpenAI have a new trick for making AI systems less easily corrupted. It’s a small but consequential tweak to the final stage of training.
Google DeepMind uses MITRE ATT&CK to monitor AI agents as rogue employees
Google DeepMind has a new security headache, and its source isn't human. The unit is now surveilling its own advanced AI agents as potential insider threats, applying a security framework built to catch sophisticated human hackers.
DeFAb Benchmark Enforces Polynomial-Time Checks for Logical Rigor
Reasoning is the bottleneck. Not prose, not parameters, but the quiet, unforgiving machinery of logical structure. DeFAb, a new benchmark, directly weaponizes polynomial-time verifiability against that bottleneck.
OpenAI researchers aim to forecast AI model failure rates pre‑launch
Testing AI models before launch is like stress-testing a car on a closed track: revealing, but rarely a mirror of real highways. Researchers fabricate adversarial prompts, hunt for known failure modes, and declare the model ready.
Nvidia AI Agent Trains Robots Autonomously, Editing Code from Papers
Nvidia has built a robot that reads academic papers and rewrites its own training code. It corrects itself. The system, which the company calls an AI agent, works in two parts. The first part needs a person. The second does not.
XGBoost, ALBERT, BioBERT, Med‑LLaMA evaluated for pharmacovigilance
Pharmacovigilance is not a game of scale. It is a game of precision. When millions of adverse event reports flood databases, the task of linking a drug to a harm demands more than raw parameter counts, it demands models that understand clinical...
OpenAI's Deployment Simulation Beats Baseline, Adds Risk Checks to Agentic Code
The next generation of AI doesn’t just write code, it acts on it. That shift brings a new class of risk: models that behave differently when they suspect they’re being watched. OpenAI’s latest research surfaces a remedy.
GLM-5.2 beats GPT-5.5 on SWE-bench Pro (62.1 vs 58.6) for 1/6 cost
For one-sixth the cost, GLM-5.2 just punched above its weight on SWE-bench Pro, scoring 62.1 to GPT-5.5’s 58.6. That single number, though, is only the start.
AMD builds Llama 3.1 8B pretraining benchmark for MLPerf, using random weights
AMD has submitted a training benchmark for a model that doesn't learn. For the latest MLPerf results, the company pretrained Meta's Llama 3.1 8B architecture using entirely random weights. No data, no real gradients.
AMD's MI355X CDNA4 GPU Shows Competitive Training Times in MLPerf v6.0
AMD just matched Nvidia’s top chip. In a head-to-head sprint, the company's new MI355X accelerator fine-tuned a Llama 2 70B model in the same time as a Nvidia B200 GPU, using an eight-accelerator setup.
NVIDIA Blackwell Leads MLPerf Training 6.0 with Full‑Stack Scale
Nvidia won everything. The MLPerf Training 6.0 benchmark results are in, and the company's Blackwell platform took first place in every single test. That clean sweep isn't about a chip.
DR-DCI Enables Agent-Callable Retrieval to Expand Local Workspace Efficiently
Most AI research papers sell you a new way to fail. They’ll claim they’ve cracked some fundamental tension, then quietly fudge the data. This one’s different. DR-DCI fixes a real problem.
Fused kernels boost MoE training, forward and backward passes up to 1.3×
Training a large Mixture-of-Experts model often feels like herding cats on a supercomputer. The GPU is constantly starting and stopping tiny tasks, stuck waiting for messages between experts, and never really working at full capacity.
Hybrid Open-Ended Tri-Evolution Improves Deep Research for AI Agents
Deep research is where AI agents usually fail. They can pull up facts, but they can't learn from them. Their knowledge is frozen. Meanwhile, a separate line of work, called agent evolution, has shown real promise.
Microsoft Research Mirage adds persistent spatial memory to video generation
Video generation has long suffered from a quiet, expensive flaw: every time a model renders a new viewpoint, it must rebuild the world from scratch, pixel by pixel, memory bleeding away with each frame.
Amazon security research prompts White House ban on Anthropic Fable
Amazon's security team found a hole. The White House answered the phone. Now some of the best researchers in the country can't touch their own work. Andy Jassy got a call from Washington after his team flagged something in Anthropic's Fable model.
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