Posts

Featured Post

2026 Is A Year That Stops Pretending

Image
  A set of predictions from someone who has watched the machinery up close Copyright: Sanjay Basu The Year the Illusions Crack Every few years, technology has a year where it stops pretending. 2026 feels like one of those years. Not the kind where a single breakthrough grabs headlines and everyone pretends it was inevitable. This is subtler. More unsettling. A year where systems show their seams. Where slogans give way to spreadsheets. Where the mythology of “infinite scale” collides with power constraints, human limits, and physics that refuses to negotiate. If 2023 was about awe, and 2024–2025 were about acceleration, 2026 will be about reckoning. Not collapse. Adjustment. And for those paying attention, opportunity. What follows are not predictions designed to impress futurists or scare boards. They are grounded guesses. Informed by watching AI infrastructure get built, by sitting in rooms where power budgets matter more than press releases, by reading too much physics late at n...
Post a Comment
Read more

How Nothing Could Destroy the Universe

Image
  Copyright: Sanjay Basu Nothing has always been more dangerous than it sounds. For most of daily life, nothing is a complaint, not a concept. You open the fridge. You sigh. There is nothing to eat. This sort of nothing is negotiable. It depends on hunger, expectations, and how brave you feel about expired yogurt. Physics is not interested in that kind of emptiness. Physics worries about stricter kinds of nothing. There is the modest version, what philosophers might call nothing with a lowercase n. You start with something and remove it piece by piece. Matter goes. Air follows. Radiation fades. What remains is a vacuum. Sparse. Cold. Seemingly empty. But still something. Then there is Nothing, capital N. Absolute absence. No space. No time. No fields. No laws waiting quietly in the wings. Not emptiness, but non-being. It is hard to imagine because imagination itself requires a stage. If true Nothing exists, it cannot be part of the universe. It cannot interact with it. It cannot ev...
Post a Comment
Read more

Fine-Tuning Language Models on NVIDIA DGX Spark

Image
 Complete How-To Guide Copyright: Sanjay Basu Overview This guide provides comprehensive instructions for fine-tuning open-source language models on the NVIDIA DGX Spark personal AI supercomputer. The DGX Spark’s unique 128GB unified memory architecture enables local training of models that would traditionally require cloud infrastructure. Fine-tuning allows you to customize pre-trained models for specific tasks, domains, or response styles while preserving their general capabilities. This guide covers three fine-tuning strategies: Full fine-tuning for maximum customization, LoRA for memory-efficient adaptation, and QLoRA for training even larger models within memory constraints. DGX Spark Hardware Advantages The NVIDIA DGX Spark provides several key advantages for local AI development: 128GB Unified Memory: CPU and GPU share the same memory pool via NVLink-C2C, eliminating memory transfer bottlenecks Grace Blackwell Architecture: Purpose-built for AI workloads with up to 1 PF...
Post a Comment
Read more

The Grammar of Structure

Image
What the Langlands Program Might Tell Us About Learning Machines Copyright: Sanjay Basu I. Introduction There is a persistent mystery at the heart of mathematics. Objects that appear entirely unrelated, defined in different languages, studied by different communities, sometimes turn out to encode the same information. A question about prime numbers becomes equivalent to a question about symmetries of certain functions. A problem in algebra transforms into a problem in analysis. The translation is not metaphorical. It is exact. This phenomenon troubles people who encounter it for the first time. Mathematics is supposed to be about definitions and consequences. If you define two things differently, why should they be the same? And yet they are. Again and again. Robert Langlands, working at the Institute for Advanced Study in the late 1960s, proposed something ambitious: that these scattered coincidences were not accidents but symptoms of a deeper unity. His conjectures suggested that...
Post a Comment
Read more