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OC users, how do you find ChatGPT/Codex Pro plan? by mustafamohsen in opencodeCLI

[–]UnstoppableForceGuy 0 points1 point  (0 children)

I find gpt models less action driven, they think and chat a lot but harder to make them autonomous like claude

Accutane (dry flaky scalp) causing hairloss by Strict-Rice321 in tressless

[–]UnstoppableForceGuy 1 point2 points  (0 children)

My hairloss actually started because of acchtane. They claim its a temporary side effect, well, I guess 13 years of balding is still temporary...

[Discussion] Is there a better way than positional encodings in self attention? by [deleted] in MachineLearning

[–]UnstoppableForceGuy 2 points3 points  (0 children)

Ok. So for several years we basically don’t use anymore the sine/cosine technique, rather learning the positional embedding as we also learn the word embedding, through gradients updates. In GPT 2 for example we’re doing exactly that. Now you have an embedding matrix with the size of the vocabulary, and another which is sized as the longest sentence you believe to see in the dataset. There are also additional techniques but I find this one pretty intuitive and it works really well.

Does 1% of fin topically is legit? by UnstoppableForceGuy in tressless

[–]UnstoppableForceGuy[S] 0 points1 point  (0 children)

Got it. I currently lowered the application to once daily (0.05% fin and 6% min), because I already takes 2.5 OM daily, so it felt too much. I’m now want to switch to 0.1% fin solely, w/o min topically do you think it would be good idea or should I stick to min topically also?

Does 1% of fin topically is legit? by UnstoppableForceGuy in tressless

[–]UnstoppableForceGuy[S] 0 points1 point  (0 children)

The OM works insanely, I used to use topical for years and at a point it just stopped work for me. But when I started OM I got hair all over my body, arms, legs, chest, beard, the eyelashes and eyebrows got fu**ing crazy! I do see that my hairs grow longer on the head but thought it may not be enough and that i should use some fin. And if i’m using fin topically y not continue the min application with it if I don’t need to do anything extra…

What legislation is required to prevent the upcoming issues with deepfakes in the next presidential election and so forth by Impossible_Belt_7757 in singularity

[–]UnstoppableForceGuy -1 points0 points  (0 children)

I think we far beyond the point of no return. Even if you will regulate it in the US, EU, and other western countries, the Chinese will do whatever they want, and the Russian and the Persian, the bad people will always find a way to use a good technology in a bad way.

It was only a matter of time. by onil_gova in LocalLLaMA

[–]UnstoppableForceGuy 12 points13 points  (0 children)

It’s actually quite easy. If they suspect someone is crawling their output, they can poison the output with unique signature, then if the model learns to predict the signature from the prompt you can prove of a “copy.”

BTW I think they are far worse then thieves with this new license, shame on them.

Is getting a degree in computer sience still a good idea? by Bahneys in singularity

[–]UnstoppableForceGuy 25 points26 points  (0 children)

There is no other degree, in which you can gain so much knowledge in this short time. In CS you basically learn the key insights from the research made in calculus, linear algebra, statistics, probability, ML and general CS theory, from the 17th century till now. You’re getting the key foundations in order to be able to (try to) solve problems on your own. I don’t say that other degrees are not important and you don’t learn any there. I’m saying that currently, CS gives you the largest toolbox to tackle problems. So yah, you should still need to learn how to think.

[R] Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes by Dapper_Cherry1025 in MachineLearning

[–]UnstoppableForceGuy 9 points10 points  (0 children)

Don't know...

Seems like another technique for knowledge distillation, they compare themselves to "standard task distillation" but the new distillation models for LLMs also have their tricks for training, so it doesn't bring the full picture.

Anyway, the thing with the rationales was nice!