3 days ago6 min read
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Jan 267 min read
Reinforcement learning vs “regular” training: the real difference is not the math, it is the loop
Most ML people grow up on a simple mental model: you have a dataset, you define a loss, you run gradient descent, you ship a checkpoint. That covers supervised learning and a lot of self-supervised pretraining. The model is learning from a fixed distribution of examples, and the training pipeline is basically a linear flow from data to gradients. Reinforcement learning (RL) breaks that mental model because the model is not only learning from data, it is also actively creating
Jan 1, 20267 min read
2025: The Year I Bet on Myself
On December 30th, 2024, I finished my last day at IBM. It was the kind of ending that looks simple from the outside, but internally it carried years of thought and a lot of quiet pressure. I wasn’t leaving because I hated the work, and I wasn’t leaving because something broke. I was leaving because I could feel myself outgrowing the comfort of a structured path. IBM gave me discipline, exposure, and a solid environment to sharpen my skills, but I kept feeling a stronger pull
Dec 14, 202539 min read
Dec 13, 20250 min read
Dec 2, 202510 min read
From Scaling To Research: Reflections On The Ilya Sutskever Conversation With Dwarkesh
There is a moment in the recent Dwarkesh Podcast episode with Ilya Sutskever that captures a turning point in how the AI community understands its own progress. Sutskever, one of the central figures behind modern deep learning and now the founder of Safe Superintelligence Inc., looks back at the last few years and says, in effect: the era when simply scaling models was the main engine of progress is ending. It is time to return to the age of research, only this time with very
Oct 15, 20253 min read
My thoughts on Sora 2
Sora 2 isn’t just another milestone in AI video generation it’s a revolution that changes how we define creativity, truth, and even perception itself. What OpenAI has achieved with Sora 2 is beyond impressive; it’s transformative. For the first time, we’re seeing a model that doesn’t just generate a sequence of moving images it generates understanding . It sees the world, reasons about it, and simulates motion, lighting, emotion, and cause and effect as if it were directing r
Oct 10, 202536 min read
Oct 3, 20259 min read
Sep 30, 20250 min read
Sep 23, 20253 min read
Why GPUs and Computation Define the Future of LLMs
Because GPUs are so critical, the AI industry has entered what some call the “compute race.” Companies like OpenAI, Anthropic, and Google...
Aug 28, 20253 min read
Aug 21, 20253 min read
Aug 17, 20253 min read
Aug 12, 20254 min read
Supervised Learning vs. Reinforcement Learning: The Core of AI and How They Power Modern LLMs
When you interact with ChatGPT, Claude, or LLaMA, you are engaging with a model that is the product of decades of research in two major...
Aug 4, 202528 min read
Analysis of Large Language Models for Medical Question Answering and Summarization
Introduction Large Language Models (LLMs) have recently demonstrated remarkable abilities in understanding and generating natural...
Jul 31, 20254 min read
How AI Will Truly Transform the Medical Field
In the coming decade, artificial intelligence will not just improve the medical field—it will redefine it. What we’re witnessing isn’t...
Jul 25, 20253 min read
Agent Mode: A Modular Intelligence Framework, Not a Revolution
Introduction In the rapidly shifting field of applied AI, Agent Mode has entered the spotlight as a powerful yet misunderstood...
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