Hacker News: t_serpico

Principles and Practice of Deep Representation Learning [pdf]

t_serpico — Sun, 21 Jun 2026 05:17:36 +0000

Article URL: https://ma-lab-berkeley.github.io/deep-representation-learning-book/assets/book-main.pdf

Comments URL: https://news.ycombinator.com/item?id=48615897

Points: 6

# Comments: 0

New comment by t_serpico in "Nvidia Stock Crash Prediction"

t_serpico — Tue, 20 Jan 2026 17:38:51 +0000

how so? (i'm not too familiar)

New comment by t_serpico in "Launch HN: Tamarind Bio (YC W24) – AI Inference Provider for Drug Discovery"

t_serpico — Tue, 06 Jan 2026 19:40:16 +0000

nice stuff! how do you handle security concerns big pharma may have? wouldn't they just run their stuff on-prem?

New comment by t_serpico in "Ilya Sutskever: We're moving from the age of scaling to the age of research"

t_serpico — Thu, 27 Nov 2025 05:57:28 +0000

I actually thought the opposite - that he seems to be seriously thinking about AGI from a broader intellectual standpoint than most ML researchers. With that said, I was a little confused when he said evolution was more optimized for locomotion/vision than language. Like yes, language is super recent, but communication in general is not.

New comment by t_serpico in "Ilya Sutskever: We're moving from the age of scaling to the age of research"

t_serpico — Thu, 27 Nov 2025 05:45:47 +0000

Yup, Dwarkesh needs to broaden his intellectual scope, and the Sutton interview completely exposed the echo chamber he's been inhabiting. There is no certainty in science, and I don't think building 'AGI' will be any exception.

New comment by t_serpico in "Kosmos: An AI Scientist for Autonomous Discovery"

t_serpico — Fri, 07 Nov 2025 04:43:20 +0000

this is a joke... to even call this a scientist is an insult.

New comment by t_serpico in "Meta Superintelligence Labs' first paper is about RAG"

t_serpico — Sun, 12 Oct 2025 05:55:16 +0000

But there is no way to know who is truly the 'best'. The people who position and market themselves to be viewed as the best are the only ones who even have a chance to be viewed as such. So if you're a great researcher but don't project yourself that way, no one will ever know you're a great researcher (except for the other great researchers who aren't really invested in communicating how great you are). The system seems to incentivize people to not only optimize for their output but also their image. This isn't a bad thing per se, but is sort of antithetical to the whole shoulder of giants ethos of science.

New comment by t_serpico in "The paradoxical efficient market hypothesis (2024)"

t_serpico — Wed, 08 Oct 2025 04:36:59 +0000

My practical interpretation of the EMH is more that easily accessible, public information is already priced in. But non-obvious insights may not be simply because the volume of people trading on that information will be smaller.

New comment by t_serpico in "Baseball durations after the pitch clock"

t_serpico — Sun, 05 Oct 2025 05:22:24 +0000

brilliant

New comment by t_serpico in "Cormac McCarthy's personal library"

t_serpico — Thu, 02 Oct 2025 17:32:25 +0000

The answer stems from McCarthy’s deeply disparaging view of modern society, which he considered lost, divorced from nature, history and tradition and heading toward social collapse and apocalypse. “Cormac considered contemporary fiction a waste of time,” said Dennis, “because contemporary writers no longer have a legitimate culture to feed their souls.”

New comment by t_serpico in "AlphaGenome: AI for better understanding the genome"

t_serpico — Fri, 27 Jun 2025 00:50:18 +0000

'Seeing' inside cells/tissues/organs/organisms is pretty much most modern biological research.

New comment by t_serpico in "Happy 10k Day"

t_serpico — Wed, 12 Mar 2025 04:50:30 +0000

Was going to comment exactly this - funny that it's a literal car salesman.

GPT-4b micro: An AI model for longevity

t_serpico — Mon, 20 Jan 2025 02:17:57 +0000

Article URL: https://www.technologyreview.com/2025/01/17/1110086/openai-has-created-an-ai-model-for-longevity-science/

Comments URL: https://news.ycombinator.com/item?id=42764314

Points: 1

# Comments: 0

New comment by t_serpico in "GPT-5 is behind schedule"

t_serpico — Sun, 22 Dec 2024 23:16:58 +0000

One fundamental challenge to me is that if each training run because more and more expensive, the time it takes it to learn what works/doesn't work widens. Half a billion dollars for training a model is already nuts, but if it takes 100 iterations to perfect it, you've cumulatively spent 50 billion dollars... Smaller models may actually be where rapid innovation continues simply because of tighter feedback loops. O3 may be an example of this.

New comment by t_serpico in "Jeff Dean responds to EDA industry about AlphaChip"

t_serpico — Mon, 02 Dec 2024 00:29:22 +0000

I don't think he got taken for a ride. Rather, he also wanted to believe that AlphaChip would be as revolutionary as it claimed to be and chose to ignore Chaterjee's reservations. Understandable, given all the AlphaX models coming out around that timeframe.

New comment by t_serpico in "General Theory of Neural Networks"

t_serpico — Sun, 14 Jul 2024 21:43:50 +0000

"Topology is all that matters" --> bold statement, especially when you read the paper. The original authors were much more reserved in terms of their conclusions.

New comment by t_serpico in "'Lavender': The AI machine directing Israel's bombing in Gaza"

t_serpico — Wed, 03 Apr 2024 22:53:41 +0000

Exactly my thoughts, the AI shields all responsibility from the humans.

New comment by t_serpico in "Proteins let cells remember how well their last division went"

t_serpico — Sat, 30 Mar 2024 18:16:17 +0000

To call this memory seems like a stretch. By the logic of the article, every daughter cell has 'memory' of the parent cell because some proteins from the parent cell are present in the daughter cell. I would be curious to see p53 complex concentration as a function of cell generation/mitosis time to show how durable this 'memory' actually is.

New comment by t_serpico in "Learning From DNA: a grand challenge in biology"

t_serpico — Thu, 14 Mar 2024 23:18:32 +0000

https://onlinelibrary.wiley.com/doi/10.1002/bies.201300153 tl;dr: metabolism is all you need.

while potentially interesting work, very shortsighted and premature to say this is a "GPT" moment in biology. ML people in bio need to think hard not only about what they are doing, but why are they are doing it (other than this is cool and will lead to a nice Nature publication). Their basic premise (learning from DNA is the next grand challenge in biology) is shaky. Imo, the grand challenge in biology is determining what the grand challenge is, and that is a deep scientific/philosophical question.

New comment by t_serpico in "Neural Network Diffusion"

t_serpico — Thu, 22 Feb 2024 01:27:36 +0000

i'd wager that adding noise to the weights in a principled fashion would accomplish something similar to this.