Best AI Blogs & Experts to Follow in 2025

As artificial intelligence continues reshaping industries from finance to healthcare, staying updated with cutting-edge insights, research breakthroughs, and expert perspectives has never been more essential. Whether you’re a builder, investor, researcher, or policy observer, the right sources can be your unfair advantage.

Top 10 AI Blogs to Follow in 2025

1. LessWrong / AI Alignment Forum
   Focus: AI safety, alignment, long-term consequences
   Why follow: Home to critical thinking on alignment theory and existential AI risk. Insightful discussions by MIRI researchers, Eliezer Yudkowsky, and others.
2. Hugging Face Blog
   Focus: Open-source models, NLP, transformers
   Why follow: Industry-defining releases like BLOOM, transformers, Diffusers. Great for both developers and researchers.
3. Distill
   Focus: Visual explanations of deep learning concepts
   Why follow: Legendary for articles like “Attention Is All You Need — Illustrated.” Rare updates, but worth every read.
4. The Gradient
   Focus: AI research summaries, industry critiques, ethics
   Why follow: Authored by PhDs and insiders. Makes academic work readable, plus strong opinion pieces on ethics and AI misuse.
5. Andrej Karpathy’s Blog
   Focus: Deep learning, practical ML, AI system design
   Why follow: Former Tesla Director of AI. His “Neural Networks: A 1D CNN from scratch” post is a rite of passage for many.
6. Sebastian Raschka’s Blog
   Focus: Applied ML, PyTorch, tutorials
   Why follow: One of the best instructors in the field. Clean explanations, reproducible code, ideal for serious learners.
7. BAIR Blog (Berkeley AI Research)
   Focus: Cutting-edge academic research
   Why follow: Authored by grad students and profs from UC Berkeley. Frequent posts on robotics, generative models, RL, and foundation models.
8. EleutherAI Blog
   Focus: Open-source LLMs, model interpretability
   Why follow: Behind models like GPT-J and Pythia. Unfiltered research perspectives outside Big Tech.
9. Redwood Research Blog
   Focus: AI safety, interpretability experiments
   Why follow: Experiments around adversarial robustness and circuit-level model understanding.
10. Lambda Labs Blog
    Focus: ML infrastructure, training cost optimization
    Why follow: Practical tips for running large models. Covers GPU clusters, distributed training, and open-source releases like “Lambda Stack.”

Top 10 AI KOLs You Should Be Reading in 2025

1. Andrej Karpathy (@karpathy)
   Ex-OpenAI, ex-Tesla. Deep learning pioneer. Mixes code, memes, and insights into next-gen AI systems.
2. Lex Fridman (@lexfridman)
   AI researcher turned podcast giant. Conversations with nearly every AI thought leader. Longform, but rich in ideas.
3. Yann LeCun (@ylecun)
   Chief AI Scientist at Meta. One of the “Godfathers of Deep Learning.” Sharp, contrarian takes on AGI timelines and system architectures.
4. Andrew Ng (@AndrewYNg)
   Co-founder of Coursera, founder of DeepLearning.ai. Practical AI advocate. Ideal for those building AI into products.
5. Eliezer Yudkowsky (@ESYudkowsky)
   MIRI founder, philosopher of AI doom. Essential for understanding alignment, timelines, and existential safety.
6. Cristóbal Valenzuela (@cvalenzuelab)
   Founder of RunwayML. At the creative AI frontier. Champion of generative video and visual applications.
7. Sharon Zhou (@sharonzhou)
   Stanford lecturer, founder of Lamini (LLMs for enterprises). Sharp insight into fine-tuning, interpretability, and productization of LLMs.
8. Jim Fan (@DrJimFan)
   NVIDIA Research Scientist. Explores embodied AI, agents, and general intelligence with incredible clarity and visuals.
9. Emily M. Bender (@emilymbender)
   Linguist and critical voice in AI ethics and language model critique. Thoughtful counterbalance to hype cycles.
10. Abeba Birhane (@Abebab)
    Cognitive scientist & philosopher. Key voice in algorithmic justice, AI colonialism, and sociotechnical risks.

Final Words

Whether you’re building LLMs, designing AI tools, or navigating policy and ethics, these blogs and voices form the pulse of the AI frontier in 2025. Balance the hype with critique, and the code with caution. True mastery comes not just from reading — but from reflecting on what’s missing between the lines.