As we all know, new advances in Artificial Intelligence are making waves these days, there are rumours that its major reason for Layoffs in industry. Though nothing to fear, its a matter of realignment to explore new ideas of its use.
I have been playing with Machine Learning well before evolution of major frameworks like TensorFlow or PyTorch. Used to work at grass root level doing multidimensional Matrix & its Manipulation, Statistics & Probability.
Strangely during my formative years while learning CS & Algorithms, found the concepts were part of 1860’s Maths books in my library @St. Stephens.
New frameworks & libraries hide all these complexities under the hood & many a times we tend to ignore maths underneath.
However, to be successful, understanding basics will go a long way in this journey. , creating new systems & frameworks by hand helps in long run, builds solid foundation, specially research.
Based on my experiences, it’s Maths makes Machines Learn.
For example in LLMs, interpretation of words based on Vectors a the word tensor in Tensor Flow is matrices and its manipulation..
Numbers (Vectors) help in deciphering interpretation & relationship between words in a sentence, sounds amazing!
Path breaking Transformer Paper in 2017 is all about Maths under hood so is the case with Generative AI , like Diffusion Models & other innovations are basically Mathematics & Probability at play.
All those who want to jump on the new bandwagon, makes sense to brush class XII maths and focus on building blocks Matrices, Calculus, Probability and its Distributions, Statistics. This will makes your journey enjoyable.
You can contact me @ asheesh.mathur@gmail.com for any help and clarifications. I offer trainings and consultancy as well
Billyker
April 2, 2025 — 10:39 pm
Mist and microlightning
solflare
To recreate a scenario that may have produced Earth’s first organic molecules, researchers built upon experiments from 1953 when American chemists Stanley Miller and Harold Urey concocted a gas mixture mimicking the atmosphere of ancient Earth. Miller and Urey combined ammonia (NH3), methane (CH4), hydrogen (H2) and water, enclosed their “atmosphere” inside a glass sphere and jolted it with electricity, producing simple amino acids containing carbon and nitrogen. The Miller-Urey experiment, as it is now known, supported the scientific theory of abiogenesis: that life could emerge from nonliving molecules.
For the new study, scientists revisited the 1953 experiments but directed their attention toward electrical activity on a smaller scale, said senior study author Dr. Richard Zare, the Marguerite Blake Wilbur Professor of Natural Science and professor of chemistry at Stanford University in California. Zare and his colleagues looked at electricity exchange between charged water droplets measuring between 1 micron and 20 microns in diameter. (The width of a human hair is 100 microns.)
“The big droplets are positively charged. The little droplets are negatively charged,” Zare told CNN. “When droplets that have opposite charges are close together, electrons can jump from the negatively charged droplet to the positively charged droplet.”
The researchers mixed ammonia, carbon dioxide, methane and nitrogen in a glass bulb, then sprayed the gases with water mist, using a high-speed camera to capture faint flashes of microlightning in the vapor. When they examined the bulb’s contents, they found organic molecules with carbon-nitrogen bonds. These included the amino acid glycine and uracil, a nucleotide base in RNA.
“We discovered no new chemistry; we have actually reproduced all the chemistry that Miller and Urey did in 1953,” Zare said. Nor did the team discover new physics, he added — the experiments were based on known principles of electrostatics.
“What we have done, for the first time, is we have seen that little droplets, when they’re formed from water, actually emit light and get this spark,” Zare said. “That’s new. And that spark causes all types of chemical transformations.”
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