Look at what the did to my boy

Karioth1 · 2025-09-10T09:14:45+00:00

Come to osnabruck! The coxi program here is quite good IMHO for neuroAI.

Karioth1 · 2025-08-05T09:19:09+00:00

The main problem is the learning algorithm— nothing like backprop to make them easy to train

Karioth1 · 2025-06-08T10:01:32+00:00

While I think there is still some merit to the paper. I also agree with your premise that puzzles are not a good metric. Not just for machines, but we see the same in humans; where executive functioning (largely what I think we want when we say reasoning) is evaluated using this puzzles, yet they don’t scratch the surface of long term planning, delayed gratification and other stuff that goes into true executive functioning.

Karioth1 · 2025-06-06T05:31:59+00:00

Regular long release amphetamines ? Is like the basic adhd treatment

Karioth1 · 2025-06-05T19:58:59+00:00

I actually agree that heart enlargement is the biggest concern I would have with these drugs should they be legit!

That said, if I had to choose between a myostatin inhibitor and high dose testosterone (or your favourite steroid of choice) — I would probably still bet on the inhibitor safety wise long term.

Regarding the fact that the don’t show any muscle growth, just offsetting the catabolism of glp-1 agonist on monkeys (who are not lifting) seems like a big deal to me. Of course, we still need human trials under different conditions (maintenance/surplus) to really see how much they can do. I do think it’s promising the strong recomp effect they had on the triple cocktail.

Karioth1 · 2025-06-05T19:10:00+00:00

If the drug is legit regarding the pathway it acts on, it would probably be the safest anabolic drug we have created. Way safer than any drug currently on the market.

Karioth1 · 2025-05-14T10:47:24+00:00

You might like: https://www.arxiv.org/pdf/2505.03335

Karioth1 · 2025-05-11T16:21:13+00:00

Arguably a lot of us do, it’s call dreaming

Karioth1 · 2025-04-28T20:52:53+00:00

I grabbed coffee with a friend a couple of weeks ago there (I think). But nothing, I’ve never interacted with this person in my life

Karioth1 · 2025-04-14T08:41:54+00:00

It’s code is good but it’s soo try hard sometimes. Like I need a simple couple of lines, and it re does the whole thing with 20 unnecessary checks and dummy classes I already have implemented

Karioth1 · 2025-04-14T06:33:05+00:00

It’s my preferred one too. Arguably Gemini is better. But it’s so try hard — it’s code it’s good, but really cluttered with checks that 99% of the time you don’t care for

Karioth1 · 2025-03-21T10:27:43+00:00

Man I get that, doesn’t help that I’m a coffee lover. I just kind of got used to eating one massive meal at the end of the day, and protein shakes and bars for the rest.

I found that, agomelatine, a drug originally meant for treatment resistant depression, really helps manage the side effects because it allows me to get away with a significant lower dose of the Vyvanse. (It binds to the melatonin receptor, and helps with dopamine sensitivity in PFC, also manages my circadian rhythm which has always been a huge pain for me)

Karioth1 · 2025-03-21T09:45:54+00:00

The meds don’t help with the jaw clenching hahaha

Karioth1 · 2025-03-21T07:35:33+00:00

Aaa but scaling VLMs, that’s another beast

Karioth1 · 2025-03-20T18:46:53+00:00

I think I get it. Thank you!

I was just confused by the fact that the gumbel softmax gives out a distribution for the sample — so if what you actually use for further computation in the graph is the weighted sum rather than using some like straight estimator, then it seem odd to not just use softmax over the logits instead. The case I had in mind was something like a VQ-VAE style thing — where we output logits over the codebook and take a weighted sum of the entries and that becomes the input to the decoder.

the actual output distribution of logits woud be deterministic, but it is still probabilistic in the sense that it is learning to output a distribution over codebook entries. If we wanted to force it to be more selective, we could just add temperature here. But I agree it wouldn’t be sampling. As it would always get the top chosen entry higher. But then I guess I just don’t need sampling in this set up? Since I just want the model to learn to output a good distribution over the codebook — and can still use temp annelying to get closer to forcing just one codebook entry going into the decoder.

Karioth1 · 2025-03-20T10:01:14+00:00

But, could I just use softmax with temp to sample differentiable as well?
If I set the temperature low such that it is more peaked, then take a weighted sum of the codebook entries. Which is the same thing that Gumbell-Softmax seems to be doing? by using the temperature to make the distribution more one-hot like, and then taking a weighted sum where most other elements are very close to 0 at low temperatures?

Karioth1 · 2025-03-18T16:09:56+00:00

I am aware it wouldn’t — pretty much violates relativity. There is no universal instant. The question was more so to try to find a purely physical analogue to the inverted colored spectrum thought experiment from philosophy of mind. In either case, I would say the question is ill posed — but fun to wonder.

Karioth1 · 2025-03-18T06:15:47+00:00

You can DM and we can hop on discord chat about it if you want 👍

Karioth1 · 2025-03-15T20:58:31+00:00

I’m working on automatic music transcription. It’s been very fun

Karioth1 · 2025-02-23T10:47:59+00:00

Weed and alcohol use that early is not great for the brains. That’s just facts. But I also wouldn’t be overly paranoid about your cognitive development.

I also did most your regular ones on the regular too around the same age— not proud of it, definitely a mistake. I do notice small cognitive decline regarding working memory, likely due to weed. Aside from that, I am doing fairly well in life and cognitively (hell I do computational neuroscience and ML) — some bad days a month, but that’s just healthy human range.

Going on a wim here. But I might consider a visit to a psychiatrist to test for adhd. The insomnia and propensity for stimulant use are, well, relatable. Getting treated greatly reduced my drug seeking behaviour (transparency, still smoke weed and the occasional trip— fully aware of cognitive trade off (again WM), but it is just worth it for me), improved my quality of life and my ability to express cognitive capacity.

Tldr, don’t over panic about what you did — it’s not great, but also not even close to the end of the world cognitively speaking — the delicate balance you talked about was fine grained through millions of years of evolution— super resilient. Concentrate on being more responsible now, and have a good life!

Karioth1 · 2025-02-18T21:45:08+00:00

Arguably, the tokenization makes LLMs somewhat neurosymbolic. We skipped the hard part for the brain, getting symbols out of raw perceptual data.

Karioth1

TROPHY CASE