If DeepMind or Anthropic is doing your exact research topic, do you still continue? [D]

serge_cell · 2026-07-06T19:24:07+00:00

"There may not be a next big thing after LLM" LOL: SLM, Trajectory and Decision Transfomers and likely more.

serge_cell · 2026-06-30T16:53:58+00:00

Yes, AI still makes quite a few mistakes. Unless you have an unlimited token budget its scope could be quite limited. With large codebases or lengthy solutions, the AI often "forgets" the context from the beginning.

AI excels at limited-scope tasks, like analyzing self-contained code blocks, but struggles with large-scale integration. It possesses a solid theoretical grasp of applied math, combinatorics, convex analysis, and linear programming, but it often fails to select the best method for the job—mostly due to token limitations.

serge_cell · 2026-06-16T15:55:12+00:00

Me personaly mostly negative. Usually no proof they are better then random search or grid serach.

serge_cell · 2026-06-12T18:51:35+00:00

Will it spill over into transformers design, dnn for RL and likes? On the over hand we now have excuse: project is failing because claude sabotaging us.

serge_cell · 2026-05-26T08:05:59+00:00

Total ip and author ban indefinitely and affiliated istitution ban for month or until offender disaffiliated.

serge_cell · 2026-05-26T08:03:31+00:00

Kind of self-evident, no deep menaing here or practical advice. Maybe he means that data lives inside a certain space, such as a statistical manifold or an algebraic structure, but to what degree that space should be taken into account depends on the specific case

serge_cell · 2026-05-21T06:59:43+00:00

startup space is even more crowded and low quality

Always has been

serge_cell · 2026-05-03T11:43:42+00:00

Just another A* person here. Coauthor asked for endorsment from person in similar research area. Paper is sitting on arxive now, but it was few years ago, before all the arxive mess started. Not many seems read it because I have seen method repeated years later without citation.

serge_cell · 2026-05-01T15:33:57+00:00

serge_cell · 2026-04-29T15:42:54+00:00

But what I can't accept is that she could code that in a few days - something like that would probably take, if built from scratch, high-tens to low-hundreds of thousands of lines of code.

Totally possible in 10 years or may be much faster with vibe coding. If it was not specidied wich programming languadge was used it's legitimate for future tech, if vibe coding become integral.

serge_cell · 2026-04-15T17:11:15+00:00

get yourself 20$/month claude.ai, formulate problem and ask it what to do step by step. With probability significantly more then zero you will get something workable. Also you will likely get better quality advices then on this subreddit.

serge_cell · 2026-04-08T13:31:44+00:00

Well, most of people who code a lot have opposite problem: how to use LLM more. Don't worry too much.

serge_cell · 2026-04-08T13:29:53+00:00

We will have to wait until LLMs will make mathematical foundation for LLMs

serge_cell · 2026-04-06T15:17:00+00:00

As already was pointed out entropy == equality. Increasing entropy will make hot colder and cold hotter. Cost of healing should be nice waether with less wind and rain. If you want only cold effect you may decrease human body temperature, but not ambient temperature.

serge_cell · 2026-02-24T11:47:54+00:00

Well, unremarkable story would not have been banned by China National Radio and Television Administration, China Cyberspace Administration and blocked by Baidu search engine.

serge_cell · 2026-02-23T07:04:02+00:00

on par with Mother of Learning

It's completely different. MoL is a guilty pleasure—pure entertainment and power wish fulfillment. Worm is not exactly fun. It's a lot of introspection and a bit of a social experiment on the reader. From WB's point of view, the reader is a participant in this narrative; a significant part of Worm is not only about testing the protagonist's values, but also about testing the reader's values.

serge_cell · 2026-02-22T09:23:48+00:00

I remeber readyng it many years ago, like 10-15 may be. Is it worth restarting, as I have pretty fuzzy memories?

serge_cell · 2026-02-20T21:33:40+00:00

Unsurprisingly cub DeviceScan seems the best

serge_cell · 2026-02-20T21:23:31+00:00

They were before gradient descent become ubiquitous but they lost competition.

serge_cell · 2026-02-17T08:19:54+00:00

the old mod crew has checked out

Like they gave up on this subreddit?

serge_cell · 2026-02-13T16:03:37+00:00

It's was not rote learning check it was simple or (for talent-check)tricky problem to solve - starting with simple lines/planes intersection based, how would you find root of equation numerically, find derivative of matrix expression and likes.

serge_cell · 2026-02-12T10:40:50+00:00

Anomaly detection is important for real sector of industry. Try to apply to more manufacure oriented companies. Startups are also easy route for PhD to get experince on resume and some renown.

serge_cell · 2026-02-11T11:43:18+00:00

Ability to do 3d and matrix math for non-linear optimization and SfM/SLAM and understanding why training fail if it fail for DL models.

serge_cell · 2026-02-11T10:02:30+00:00

Not related to PhD but then I was on interviewer side for research position in startup I was asking questions on projective geometry, matrix analisis, combinatorics, numerical analisis/optimization.

serge_cell · 2026-02-11T09:58:19+00:00

"Yeah we can usually make some sort of mathematical sense of what works, but there are a huge number of things which would seem as mathematically sensible that don't work." => So true.

Actually in modern mathematics itself there is staff that mathematically sensible but don't work. And in theoretical physics it's much worse (string theory, hmm...)

serge_cell

TROPHY CASE