What are Large Concept Models (LCMs)? Learn how Meta's AI research predicts concepts instead of tokens, how LCMs compare with LLMs, and what comes next.
Learn how to use AI for more than everyday tasks. Discover a practical framework for tackling harder problems, testing assumptions, and producing better work.
Anthropic says Chinese AI labs harvested millions of Claude interactions to train competing models. Here's what happened and what it means for the AI arms race.
Sam Altman says we should trust AI companies. Dario Amodei wants a slowdown. Recent AI-agent incidents reveal a deeper problem: who should decide when AI is safe?
Ornith-1.5 explores AI self-improvement by generating tasks, strategies, and solutions, creating an adaptive training loop for increasingly capable AI agents.
AI needs more than model checkpoints. Explore how version control could track models, memory, tools, knowledge, policies, and self-improving intelligence.
Kerala is building GPU infrastructure and an AI ecosystem, from shared compute and Agentic AI to localized models, robotics and government applications.
Kerala is building an ambitious AI ecosystem. The Kerala AI Mission and K-AI platform could reshape AI startups, government innovation and technology in the state.
India's Gnani Artha is betting that the future of AI isn't bigger models, but cheaper, faster, Indian-language intelligence built specifically for India's scale.
Kerala has created India’s first dedicated AI ministry. Here’s what the AI Minister means, how it works, and how it could reshape Kerala’s future.
Learn how to become an AI engineer without a CS degree, what skills employers actually want, and a practical roadmap for building projects and getting hired.
Tokens per second can be misleading for AI agents. Prefill, KV cache, context length, tool calls, and latency often matter more than raw generation speed.