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Well said!

Great, this is unique trait and helpful one - Firefox is here to stay

This "hidden knowledge" is fun to read but pain to remember and use, especially when working with multi-platform environments //

Switched from bash to plain python scripts for shell stuff everywhere several years ago, and never looked back into bash zoo anymore. Stable syntax across Win/Mac/Linux, no bash/zsh/msys2 obscure differences, normal errors and Clause writes scaffolds quick and flawless anyway

... Today its "Claude just needs to write it" and the "hard part" is the prompt :)

Current situation exist presisely due researches of 20th century though. This is largely connected things

There are still problems though - in Chrome translation addon simply no way to login properly so its broken //

Also represents good test coverage

It's the opposite, engineers do know. Claiming otherwise is way too generous and over confident.

I mean between this two "knowings" the Claude inner workings are much more clear for engineers, including many side effects, alternatives, custom shortcuts in processing etc. It's a magic only for people looking at it as black box

Well, at the very least we have a base to distinct different kinds then.

Probably the main problem of people implying LLM consciousness is that they imply LLM have human-kind of consciousness. Judging only on "how they speak", generally, they insist on using the same word that labels human consciousness (exclusively), etc.

But there are so many instrinic differences that such claim is not feasible despite similar "talking abilities".

It is useful, so yes

MOE basically work that way already, QWEN/etc with low active params (A-number in name) allows to inference big models locally (only active params have to fit into memory)

With both cases the agent doing something is human. And human beings are indeed conscious. Outside human needs LLM are useless.

Math, as a tool, is just a proxy for people using LLMs, as well as GPUs spending cycles on calculating the math

> weak reasoning once you get off the beaten path

Yep. And LLM engeneers improving this issues see perfect correlation with only one thing - data quality and quantity through training pipeline. LLM internals are secondary on many metrics for improving that

Humanity just reached the point where collective accessible knowledge covers semi-full perturbations of all main concepts that human consiousness ever produced, with additional associative expanding (math handles this). Full perturbations with current communication complexity are written down and recorded one way or another, LLMs just capitalizing on that tipping point, imho

Math used in LLMs is perfectly reducible and Gödel have nothing to do with it - inside commonly used axioms (which sufficient for LLM to exist and outside of Kurt Gödel scope) there are ZERO questions/uncertainties how it works, it's just a fact :)

+100, companies certainly have direct interest in pumping asset evaluation, and emotional attachment is financial valuable thing. Emotional attachment sells better than xxx this days

Imho no, math itself have no conciousness. Quite confidently its a helpful tool that does not act by himself.

I can not simulate my brain, it's a huge stretch to imply this.

But with LLMs - anyone can simulate LLM. LLM can be simulated without any uncertainties in pen and paper and a lot of time. Does it mean that 100 tons of paper plus 100 years of time (numbers are just examples) calculating long formulae makes this pile of paper consiousness? Imho answer is definitive no.

Since the times GPT-2 was reimplemented inside Minecraft - its quite obvious LLMs are just math. Nothing else, by nature. Modern LLMs have the same math as in GPT-2 - just bigger and with extra stuff around - and math is the only area of human knowledge with perfect flawless reductionism, straight to the roots. It was build that way since the beginning, so philosophy have no say in this :) And because of that flawless reductionism, complexity adds nothings to the nature of math things, this is how math working by design - so it can be proven there are no anything like consciousness simply because conciousness was not implented in the first place, only perfect mimicry.

And the real secret is in the data, not math. Math (and LLMs running it through billions of weights) is just a tool.

With current standartization the issue of "page not working on non-Chrome browser" is non-existent. Thanks god nowadays everything (pages) work everywhere in very similar manner, I am using chrome, firefox, safary and opera and have zero problems last 5+ years. Old days are gone.

But on the other hand, adding LLM with strong guards (not yet here but doable for popular attack vectors) into the human loop can drastically eliminate insider factor, imho.

probably 8M params are too much even :)

Well, this is a business model, not a coincidence... They are in the battle of selling fresh hardware each and every year consistenly

Exactly!

Interesting! Can it be used in Google Colab to open temporary access to python server? NGROK can be attached this way in 6 lines of code

biology plays the role, certainly, but nature was trying to capture a model for 3D physical interactions first of all, physics first. And final choice of two 2D sensors is explicitly optimal and minimally effective for 3D - so it can not be similarly descriptive for 4D, just not fair to expect results on same level imho.

For meaningful 4D perception on similar level our body need three volumetric sensors, separated, to define volume with 4D direction

Our 3D visualization relies havily on photons doing the heavy lifting of traversing 3D space in straight lines, people get, you know, accustomed to it. In fact how we see things is frozen by physics, not brains - they are just accommodated to reality

There are no such utility particles doing any heavy lifting in 4D, so nothing to accommodate to.

Interesting research, but it is still fascinates me why AI devs of current SOTAs ignore possibility to add numbers as first-grade citizens to AI. like for example suggested here: https://huggingface.co/papers/2502.09741

clean separation matter, it’s really strange to force models to mimic numbers and math via incredibly unfit token-mangling stuff, imho

Seems the team and working conditions worth mentioning it twice, nonetheless.

Good there are places to work with normal knowledge culture, without artificial overfitting to “corporate happiness” :)

They definitely does not aware of soviet reality that “roof over head” usually is not in the place where human want to live, same with job. if student after university decided (not by student, by state distributing workforce) to go work at city on polar circle - that means that student will go live and work here, without sunlight for the rest of his life! not joking, personal story with soviet collapse as happy ending (moved to normal place after that)

turns out - no, by intuition they should do this for sure - but no.

UPD: Found the paper: - https://huggingface.co/papers/2502.09741 - https://fouriernumber.github.io/

in paper mentioned “number” is a single sort-of “token” with numeric value, so network dealing with numbers like real numbers, separately from char representation. All the math happens directly on “number value”. In majority of current models numbers are handled like sequences of chars