Showing page 49 of 55
IBM’s Granite 4.0 Nano loads smarter AI onto your laptop, phone, or potato PC, banishing the cloud to the bargain bin of bad ideas.
Why Alibaba’s new vision-language models are terrifying competitors and deployment nightmares
How Big Tech’s liability paranoia is turning creative AI tools into overcautious censors
Samsung’s Tiny Recursive Model with microscopic 7M parameters beats massive LLMs on reasoning tasks, challenging the ‘bigger is better’ dogma.
GitHub, Google, and Anthropic are betting big on terminal AI assistants. But which CLI actually delivers on the promise of AI-driven development?
PaddleOCR-VL delivers SOTA performance with 80x fewer parameters than competitors, redefining OCR capabilities
How a government-backed AI assessment framework ignited controversy over bias, security, and the future of global tech standards.
SWE-rebench results reveal Claude’s decisive 55.1% pass@5 advantage and unique bug-fixing capabilities that left OpenAI’s flagship coding model behind
Alibaba’s Qwen3-VL 4B/8B models deliver enterprise-grade vision-language AI that runs locally on consumer hardware via GGUF, MLX, and NexaML.
REAP pruning outperforms merging in MoE models, enabling near-lossless compression of 480B giants to local hardware
Microsoft’s UserLM-8b flips the script by training AI to think like messy, inconsistent humans instead of perfect assistants.
Tracing the historical pattern of wealth-creating industries from oil to AI, and speculating on what comes next when the bubble bursts.
