Zeth0s @ Zeth0s @lemmy.world

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666

Joined

2 yr. ago

You are most probably wrong. How old are you?

Time really cures such feelings. In 20 years you'll watch back to these events with a very different perspective

It borrowed the concept from old editor such emacs. It is a modern emacs. A single editor to do literally everything via plugins. The idea is that one needs to learn a single editor to master everything.

It is very powerful for people who do multiple things. It's not worthy if the whole job is to simply writing java or c#. In that case a dedicated ide is better

VSCode is a modern emacs. Similar concept, a single editor to do everything via extensions. That's the selling point. "young people" never had the chance to work with a similar concept, this is why they found it so revolutionary (despite being a concept from the 70s).

I use it because I am forced to use a windows laptop at work, and emacs on windows is a painful experience

Common Reinforcement learning methods definitely are.

LLMs are an evolution of a markov chain as any method that is not a markov chain... I would say not directly. Clearly they share concepts as any method to simulate stochastic processes, and LLMs definitely are more recent than markov processes. Then anyone can decide the inspirations.

What I wanted to say is that, really, we are discussing about a unique new method for LLMs, that is not just "old stuff, more data".

This is my main point.

A markov chain models a process as a transition between states were transition probabilities depends only on the current state.

A LLM is ideally less a markov chain, more similar to a discrete langevin dynamics as both have a memory (attention mechanism for LLMs, inertia for LD) and both a noise defined by a parameter (temperature in both cases, the name temperature in LLM context is exactly derived from thermodynamics).

As far as I remember the original attention paper doesn't reference markov processes.

I am not saying one cannot explain it starting from a markov chain, it is just that saying that we could do it decades ago but we didn't have the horse power and the data is wrong. We didn't have the method to simulate writing. We now have a decent one, and the horse power to train on a lot of data

We do. I pay to work with it, I want it to do what I want, even if wrong. I am leading.

Same for all professionals and companies paying for these models

It's a bit like saying a human being is a fancy worm. Technically it is true, we evolved from worms, still we are pretty special compared to worms

LLMs are not markovian, as the new word doesn't depend only on the previous one, but it depends on the previous n words, where n is the context length. I.e. LLMs have a memory that makes the generation process non markovian.

You are probably thinking about reinforcement learning, which is most often modeled as a markov decision process

This is just because we produce too much co2, not because it's not the best way. We should reduce co2 production and increase transformation via photosynthesis

I'd like to go back to basic scientific research. Unfortunately modern "scientific system" have pushed most of us out of meaningful research, to do short term, low value work in private sector. I hope to retire early, having enough money to set up my own small lab (in my field of expertise it is possible thanks to cloud providers), doing meaningful (for me) research, and publishing in honest way, for free, out of the main corrupted channels (established publishers).

That's my dream. It's not much, I will probably be ridiculed by many, but at least I will enjoy what I am doing feeling as I am "doing the right thing", not a cog in the scientific mafia system

The right way!

The problem is not carbon, it's CO2. They are 2 very different things. Carbon is fine, carbon is literally life, CO2 has to be transformed in some other carbon-based substances, otherwise capturing it is literally doing nothing on the big scale.

Unless they are converting the captured CO2, this thing is useless overall.

Newspapers, companies and politicians should stop talking about carbon. It is confusing and plain wrong. No one needs de carbonization of anything, we need transformation of CO2

AI they are talking about is most likely completely different than chatgpt.

They are likely labeling people "at risk" using some very reliable old-school ML algorithm, such as xgboost.

Biases are clearly a problem, but they are more manageable than human biases, because of the mathematical form that help finding and removing them. This is why for instance EU regulations force to have mathematical models in many area, to replace "human intuition". Because mathematical models are better for customers.

They aren't doing anything new, just calling it AI

I simply don't care. I am in a position lucky enough that I can trust distro maintainers, without the need to care about the details, as long as my system behaves as I expect, satisfying my requirements of reliability and stability

It should be done via automod. Also on many subreddit it is banned. It is a garbage tabloid.

And no friction or gravity. Will stay in perpetual motion, forever flying around the room

Can we ban links to the sun? It's notoriously not trustworthy

Pretend it's in the "supplementary information". Nobody reads it, with the exception of phd students

What? The reason is that academia does not rewards competency and innovative research. It rewards ability to gather funds, and to streamline paper production. Professors nowadays are often "technically" average, but extremely good startup ceos

We, as society, have become dumb and mean... It's a pity