OpenAI inference cost reduction cut ChatGPT guest traffic from tens of thousands of Nvidia GPUs to just a couple hundred, ...

Local AI inference at 32B-parameter quality, no cloud API required: University of Waterloo researchers released PAW on July 2, 2026, a system that compiles any natural-language task spec into a 23MB ...

While a patient is fully anesthetized and unresponsive, neurons in the hippocampus continue to process language, distinguish different types of words, and generate neural activity consistent with ...

NVIDIA diffusion language model Nemotron TwoTower achieves 2.42x LLM inference throughput without a full retraining run, ...

Context graphs, graph memory, and ontologies for AI are converging. What does this mean for enterprise AI in 2026?

What happens when we die? It's one of the single greatest questions in the history of humankind, silently driving science and ...

Industry discussions about what’s holding back AI often focus on security, graphics processing unit availability and other ...

With a 23% holdings overlap as of April 2026, WTAI and WQTM offer complementary exposure to the shared pursuit of greater ...

LFM2.5-230M proves that while 3-billion-parameter models like VibeThinker are solving advanced calculus, a ...

Deploying DFlash block diffusion on NVIDIA hardware accelerates autoregressive LLMs during latency-sensitive inference.

Abstract: Large scale iterative graph computation presents an interesting systems challenge due to two well known problems: (1) the lack of access locality and (2) the lack of storage efficiency. This ...

Abstract: Advanced deep learning architectures, particularly recurrent neural networks (RNNs), have been widely applied in audio, bioacoustic, and biomedical signal analysis, especially in data-scarce ...