A new study from Arizona State University questions whether large language models can truly "think" like humans, suggesting their apparent reasoning is just pattern-matching that quickly breaks down when faced with unfamiliar data.<br /> The article Yet another study doubts that LLM reasoning shows true logic over pattern imitation appeared first on THE DECODER. [...]
Microsoft on Tuesday released Phi-4-reasoning-vision-15B, a compact open-weight multimodal AI model that the company says matches or exceeds the performance of systems many times its size — while co [...]
AI engineers often chase performance by scaling up LLM parameters and data, but the trend toward smaller, more efficient, and better-focused models has accelerated. The Phi-4 fine-tuning methodology [...]
Training a foundation LLM from scratch costs millions and requires internet-scale data — which is why most enterprises don't bother. Sapient thinks it has a cheaper path.To overcome this brute- [...]
Deploying AI agents for repository-scale tasks like bug detection, patch verification, and code review requires overcoming significant technical hurdles. One major bottleneck: the need to set up dynam [...]
Researchers at MiroMind AI and several Chinese universities have released OpenMMReasoner, a new training framework that improves the capabilities of language models in multimodal reasoning.The framewo [...]
AI coding agents are rapidly accelerating data engineering by generating transformations, pipelines, orchestration workflows, validation tests, and infrastructure configurations from prompts. However, [...]
This weekend, Andrej Karpathy, the former director of AI at Tesla and a founding member of OpenAI, decided he wanted to read a book. But he did not want to read it alone. He wanted to read it accompan [...]