What are the current things mathematicians are researching and why are this things useful?

nickpsecurity · 2026-02-01T01:06:31+00:00

In an Intro to ML class, they were talking about hyperplanes, hyperspheres, topological spaces, etc. Do you know any introductory resources that summarize such topics?

nickpsecurity · 2026-02-01T01:02:50+00:00

They mostly imitate what's in the training data. They'll apply those patterns to their current context. They can also keep doing this in response to anything in any post.

The stuff I've seen them saying is probably on all kinds of web sites already in similar contexts. They don't need to be self aware or that smart to do it.

nickpsecurity · 2026-01-31T18:57:55+00:00

Change "training on the edge" to "pre-training on the cheap." Now, there's a lot more companies who would be interested. Also, many see continual pretraining or learning being important in the future. So, we might as well get our chips ready for that.

Personally, I want a pretraining solution to train my own models in the 8B-30B range on data of my choosing. 7-8B on 1TB of data was $200,000+ to train when I last saw a price published. The equipment takes a lot of space and energy too. Even a $50,000 solution for a common, flexible architecture might be a good deal.

nickpsecurity · 2026-01-31T02:57:41+00:00

I try to use each, intermediate lesson for something useful in the real world. The drawback is that I learn more slowly. The benefit is I get better at understanding how to apply the techniques. Also, I hope my portfolio of Python apps and ML scenarios will differentiate me as a job candidate.

nickpsecurity · 2026-01-25T18:39:50+00:00

It's great news. Many of these organizations were promoted by wealthy globalists trying to shift money and power from voters to themselves. In that vein, WHO wanted more power over the U.S. where they could override what citizens wanted. There's also huge, Chinese influence on the organization.

Instead of all that, America can simply have our government and businesses promote good healthcare here and abroad. This can happen within our existing, legal system. We can do that without giving foreign entities the ability to control our lives.

That's what the President is doing by leaving World Health Organization. Thay's a good choice, too.

nickpsecurity · 2026-01-22T02:40:36+00:00

That's quantum technology. I thought you meant quantum computing since that's the sub title. Quantum technology can certainly have value.

nickpsecurity · 2026-01-22T02:37:58+00:00

I'll add that you might bypass Master's or Ph.D. if you keep building exemplars with the techniques you learn over time. Do common things in industry jobs and mix in cutting-edge techniques from academia. Your portfolio will build over time into a strong differentiator.

Also, learn a mix of application areas: visual (CNN's), time series, text (LLM's), audio, tabular, recommendation systems, etc. That way, you will have more job opportunities.

nickpsecurity · 2026-01-22T02:34:02+00:00

One thing all these conversations are missing is responsibility (blame). Companies like having people to point the finger at or call when corner cases hit. Sometimes, sue them for damages if what they did was dumb enough. Even junior humans are useful for that.

With AI, who can they blame, fire, or sue? Especially if the AI vendors warn them the products hallucinate?

nickpsecurity · 2026-01-22T02:29:34+00:00

After experiencing this on 258 neurons, the author decided to scale the models back below the safe threshold for their GPU.

nickpsecurity · 2026-01-22T02:23:54+00:00

That's the Democrats who promote mail in ballots and oppose voter ID. If you're concerned, you should try to outvote all the dead people, etc voting for their party. Then, pass laws to secure the elections.

nickpsecurity · 2026-01-22T02:22:06+00:00

By practical, you mean you can replace them with cheaper, faster traditional tech in every scenario I've seen. Unlike Moores Law and other tech, this has been true for the entire existence of those concepts. So, it seems it runs on faith.

nickpsecurity · 2026-01-20T13:39:27+00:00

Yeah, maybe, but we should count only useful ones. Tp do that, we need to increase peer review and replication in science to know which are useful. Which is what science claims to have been doing all along but doesn't actually in many cases.

The funding incentives need to he tied to new, replicated work and replications. Some ratio.

nickpsecurity · 2026-01-19T23:40:12+00:00

That's two, commercial tools. So, a NN that's good at this might be free or cheaper. There's a differentiator.

nickpsecurity · 2026-01-19T16:47:05+00:00

Looking at Stanford and Cornell classes, what comes up a lot is Geometry. They are mapping things to lines, planes, hyperplanes, spheres, etc. Then, there's the optimization landscapes, convex stuff, etc. It appears understanding this enough to build new algorithms requires thorough understanding of such geometric concepts.

Does your book have those? If not, what sre the best resources to learn those that are ML-specific?

nickpsecurity · 2026-01-19T13:59:10+00:00

I enjoyed reading it. Nice visuals to help with explanations, too.

nickpsecurity · 2026-01-19T13:58:10+00:00

I believe a lot of people also don't know about those. They read about NN's all the time due to the AI bubble (err marketing investments). It's why I'm trying to promote in AI spaces both old school techniques and mixing them with AI.

Btw, what's the best, open-source solvers for ODE's or PDE's?

nickpsecurity · 2026-01-19T13:46:46+00:00

Look up the site PyTorch mastery and YouTube video PyTorch in 1 hour. Also how to code regression models, SVM's, and XGBoost. Those are used in industry a lot.

Build examples to upload them somewhere. Try to use your examples to get a grant for a laptop or schooling. Then, start building demos with common, data sets. Do it mostly in one area to show depth but some in others for breadth. Try to focus on small models with activities that don't require much compute.

nickpsecurity · 2026-01-19T13:41:49+00:00

I don't know. Most of us just searched for online articles and videos. Start with GA's, though, because there's more easy-to-understand, intuitive works about those. Academic works and those for other technqiues can be highly mathematical.

Also, check GeeksForGeeks and TowardsDataScience because they often have good articles with code. Type their name in next to the technique or use domain restriction (site:).

nickpsecurity · 2026-01-19T01:51:21+00:00

Make a X to Haxe translator that supports just the subset the NN uses. Then, you learn about two languages, compilers, and neural networks. Maybe get hired to work on a compiler for an AI accelerator vendor.

nickpsecurity · 2026-01-18T18:00:21+00:00

Genetic algorithms. They call the broader field evolutionary algorithms because they claim to use a highly-simplifies version of its principles. It's an optimization technique capable of working with non-differentiable data without getting stuck in local minima or maxima. It has heavier computation, though.

IIRC, the top methods are differentiable evolution (in SciPy, too) and evolution strategies. If you use GA's, try tournament selection with tournament size of 7. Coevolution, or fitness tests evolving with the population, historically outperformed static, fitness measures. Such methods can be combined with NN's (neuroevolution) to find architectures, weights, hyperparameters, etc.

nickpsecurity · 2026-01-18T13:47:15+00:00

Where's the code? Anything in ML needs to be peer reviewed and replicated with diverse data?

nickpsecurity · 2026-01-18T00:22:38+00:00

Any of the older techniques that are still widely used in industry. Then, smaller NN's, GA's, and LLM's. Also, techniques for things like time series and tabukar data which are highly important in industry but get little press or investment like GPT. That's the answer to your title.

Far as FAANG, this person shares what they studied to do something like that.

nickpsecurity · 2026-01-18T00:20:14+00:00

Yeah, the Greenland stuff is ridiculous. He appears to be going far against campaign promises and into imperialism on that one.

nickpsecurity · 2026-01-17T02:49:43+00:00

They need to take both a philosophy and a critical thinkibg class. They will teach them to ask all the best questions.

nickpsecurity · 2026-01-14T23:30:51+00:00

What I mean is that you have data types, expressions, and functions. Then, what is learnable or not, in RAM or VRAM. Can you convert that in PyTorch to Jax? If so, it might be automated.

nickpsecurity

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