Hacker News: pama

New comment by pama in "Superconducting monolayer cuprate with a single CuO2 plane"

pama — Sun, 16 Aug 2026 11:06:02 +0000

Hmm. I didn’t get that impression from a quick skim. Just curious: what makes you think that?

New comment by pama in "At-home test for infected ticks could improve Lyme Disease diagnosis"

pama — Sun, 16 Aug 2026 10:39:06 +0000

Lower latency, but broader readout of the tick bacteria at: https://nyticks.org/tick-submission/

As mentioned in the article, this is not a safe way to assess Lyme disease. I still want to know what biohazards these tiny critters hold.

Open source, audited by GLM-5.3

pama — Sat, 15 Aug 2026 12:09:49 +0000

Article URL: https://huggingface.co/spaces/zai-org/OpenVuln

Comments URL: https://news.ycombinator.com/item?id=49309938

Points: 3

# Comments: 0

New comment by pama in "Show HN: Woxi - Open-source Mathematica / Wolfram Language reimplementation"

pama — Wed, 12 Aug 2026 13:54:24 +0000

Thanks

New comment by pama in "Show HN: Woxi - Open-source Mathematica / Wolfram Language reimplementation"

pama — Wed, 12 Aug 2026 13:09:39 +0000

You now fully support version 1.0. IIRC, the first version of Mathematica I used back in early 1993 was 2.1 soon followed by 2.2, which was useful for a couple of years. How much extra work is it to reach full compatibility with that version? (I had used MathLink at the time.)

New comment by pama in "Show HN: Scroll through all 43252003274489856000 Rubik's Cube states"

pama — Tue, 11 Aug 2026 11:34:09 +0000

Application error: a client-side exception has occurred (see the browser console for more information).

iPhone; Safari; Lockdown mode.

New comment by pama in "Taxi drivers rarely die of Alzheimer's"

pama — Sun, 09 Aug 2026 22:01:24 +0000

Alzheimers has a very long development stage compared to almost all other dementia (Lewis body also has a long timeline, but none of the other forms has anywhere close to the known length for Alzheimer’s disease). The original study article has no causal analysis, so a simple explanation is that super early Alzheimers symptoms (possibly even undetectable ones outside the context of intense taxi driving) drives people to abandon their taxi- or ambulance-driving jobs and seek other forms of employment.

New comment by pama in "DeepSeek V4 Flash 0731"

pama — Fri, 07 Aug 2026 19:59:28 +0000

No secrets—all published. Very efficient attention. Excellent kernels. Great caching subsystem. Small and well trained model.

New comment by pama in "Changes at Google DeepMind: Demis Hassabis from CEO to Chair, Jeff Dean departs"

pama — Thu, 06 Aug 2026 11:14:01 +0000

Google’s trajectory unfortunately starts to feel similar to when yahoo lost everything in the early dotcom bubble except it owned a huge chunk of Alibaba. Google’s internal decision to stop publishing useful research probably started the slow but sure process of internal decline. I still hope they can recover, given their amazing position in terms of data and infrastructure, but it no longer feels like an obvious or easy task, when only 6 or 7 years ago they felt untouchable.

New comment by pama in "Discovery Loop"

pama — Thu, 06 Aug 2026 07:49:48 +0000

Large groups suffer communication bottlenecks, so by Amdahl’s law will only be as fast as a smaller group.

You can of course have many independent small groups, but this is trivial and best left unsaid in the context of this comparison.

New comment by pama in "When AI Benchmarks Plateau: A Systematic Study of Benchmark Saturation"

pama — Wed, 05 Aug 2026 18:54:49 +0000

My point is exactly that we cannot even begin to start the process that will lead to “know everything” there is to know unless we make it a science first. Ad hoc statistical models are different than understanding or complete knowledge of a subject.

New comment by pama in "Position: LLMs Can't Jump"

pama — Wed, 05 Aug 2026 12:36:33 +0000

The early physics background is messy and incorrect. I didnt read the full position paper, but from its start: The Lorentz transformations were by Lorentz, well before Einstein’s paper on special relativity; the principle of relativity also existed before the Einstein paper. The math was all there, with steps taken by Maxwell, Voigt, Larmor, Lorentz, and Poincare. Einstein supplied a clean physical interpretation, making all inertial frames equivalent, making simultaneity frame dependent, and explaining length and time deformations without the need of the concept of ether. Skimming the end of the paper with the arguments about lack of abduction or inability to make the analogy without sensory experience, I see that this paper is unfounded speculation rather than solid/hard philosophical logic. As a position paper it is OK to appear, but i think it misses the point of how LLMs or other autoregressive learners of future states can build analogies and intuition that can help them formulate new theories of the world. Soon it will be more obvious to everyone, so I am not very worried about these writings.

New comment by pama in "No Data Centers in My Backyard"

pama — Wed, 05 Aug 2026 12:08:54 +0000

Agreed in principle for today’s new ones, though with all the buying frenzy it quickly becomes hard to procure anything but the latest hardware and the economics of older generation hardware makes little sense for new data center deployments.

New comment by pama in "No Data Centers in My Backyard"

pama — Wed, 05 Aug 2026 11:34:06 +0000

The new ones will be though. Look up the specs for the NVIDIA Vera Rubin: no fans; recycled liquid cooling.

New comment by pama in "When AI Benchmarks Plateau: A Systematic Study of Benchmark Saturation"

pama — Wed, 05 Aug 2026 06:20:40 +0000

The paper suggests the opposite of your first statement. The benchmarks become useless because the successive models keep saturating them.

New comment by pama in "When AI Benchmarks Plateau: A Systematic Study of Benchmark Saturation"

pama — Wed, 05 Aug 2026 06:17:29 +0000

I agree these are central components, but to avoid oversimplification and the mistaken belief that modern LLMs do a lot of search during inference: If it was so simple, the traditional computer algebra systems would have reached similar breakthroughs when deployed at large supercomputer centers. This didnt happen because the search space is huge. You definitely also need a fancy learning algorithm. Although these ingredients would suffice (depending on what the learning algorithm is), you probably also want to learn in the absense of a strong verifier at every step, to allow building a fuzzy/erratic sense of the search space that can lead to planning/intuition and allow distant jumps in a targetted direction.

New comment by pama in "When AI Benchmarks Plateau: A Systematic Study of Benchmark Saturation"

pama — Wed, 05 Aug 2026 06:01:48 +0000

I wish we knew everything about how LLMs work! We only know very basic elements related to their construction and traning dynamics, and pretty much every major question we would like to address still has unknown or vague heuristic answers. This is expected for such a young field of study. In physics, we know the Schrodinger equation, but we dont know everything about how the world works or how to create new materials even though we know that these materials are composed by atoms and we can simulate small collections of them. In cell biology, we know the sequences that make up the DNA of a cell and we approach the time we can build minimal synthetic cells with pieces we understand, but we only scratch the surface of our level of understanding of how the cells actually work and new discoveries are added every day. In biology at large we still keep finding new types of tubes inside human brains—not sure what you mean by plenty, but we certainly have an extremely limited understanding of human cognition compared to what we might have in 50 years from now. It is not just anout LLMs and intelligence—I would like us to be able to answer practical questions about how LLMs work in order to improve general or specialized LLMs even faster than today. We “know” about scaling in an empirical sense, and it certainly has a long way to go, but it does not feel close to a complete understanding.

New comment by pama in "Ten advances in mathematics and theoretical computer science"

pama — Tue, 04 Aug 2026 15:23:34 +0000

I agree boring problems exist; bounds may have a fare share of them. None of the bounds problems in this set are even close to this category; many of them are closer to the type of contributions that in the past got recognized by special awards. Your initial replies were misleading.

New comment by pama in "DeepSeek V4 Flash on a Single AMD MI300X"

pama — Tue, 04 Aug 2026 12:13:10 +0000

Use nvidia hardware instead and use a larger cluster serving many more users concurrently. Easily 10x–20x higher token rate per GPU with public solutions like dynamo and sglang.

New comment by pama in "Ten advances in mathematics and theoretical computer science"

pama — Tue, 04 Aug 2026 05:08:30 +0000

Your inverted logic does not hold. The fact that such useless problems for bounds exist does not mean that improving bounds is useless. 9 fields medals in the last twenty years, including the one to Terrence Tao, were for improvements on bounds. 3 of the 4 medals in 2022 were for bounds; 2 of these medals were in combinatorics.