I appreciate that. I am not a position though to advocate for such a change :)
HN user
osm3000
I am a machine learning engineer, with a MSc and a PhD in ML.
I love building systems and processes to collect data and extract value from it.
Probability is fantastic, Statistics is a bitch (although useful sometimes).
https://blog.osm-ai.net/
Data Scientists
I am a machine learning engineer. I've been in the domain almost 12 years now (different titles and roles).
In my current role (and by no means that is unique), I don't know how to write less code.
Here are problems I am facing: - DS generating a lot of code - Managers who have therapy sessions with Gemini, and in which their ideas have been validated - No governance on DS (you want this package? import it) - No governance on Infrastructure (I spent a couple of months upskilling in a pipeline technology that were using: reading documentation and creating examples, until I became very good it...just for the whole tech to be ditched) - Libraries and tools that have been documentation, or too complex (GCP for example)
The cognitive overload is immense.
Back few years ago, when I was doing my PhD, immersing in PyTorch and Scipy stack had a huge return on investment. Now, I don't feel it.
So, how do I even write less code? Slowly, I am succumbing to the fact that my tools and methods are inappropriate. I am steadily shifting towards offloading this to Claude and its likings.
Is it introducing risks? For sure. It's going to be a disaster at one point. But I don't know what to do. Do I need a better abstraction? Different way to think about it? No clue
I benchmarked SoA vs AoS in Python. While SoA was more efficient than AoS, its readability penalty outweighed the gains.
Happy to get some feedback about better ways to do this.
It’s pretty good. I loved it. I recommend it
My only problem is that the creator insists it was factually correct. First test, the tapes, are anything but correct
Hey Nicolas! Very glad to hear from you :)
I honestly don't see a problem with dramatization (not my taste, but people are different I guess).
My issue is with Craig Mazin (the creator of the series) insistence that he stuck to the details and the truth in the series: https://www.youtube.com/watch?v=yY0r1Ln6tkM
I am not sure why you are mentioning historians here. A proper historical view/investigation is way outside of my scope.
My angle is simple: they said it was accurate, and Legasov did so and said that...and in his own words, he negated most of that.
Is Legasov a good guy? I don't know. Was he honest in what he said? I don't know...but he said what he said!
cherry-pick inaccuracies
Feel free to go to the tapes
I wasn't aware of that Dyatlov's interview! Thanks a lot for sharing it
because Legosov isn't even the primary source for the series
I think it was explicit that the series framed the tapes as the "revelation"; the honest message of a dying man to the world to expose what actually happened
That is a very good point
My angle was: HBO series said Legasov's position was something that was by far not true
I've mentioned her article. I think she barely touched the topic of Chernobyl itself. Her points was about what the Soviet life was back then, and some depictions of this was incorrect.
For example (for her article)
In Episode 2, for example, the Central Committee member Boris Shcherbina (Stellan Skarsgård) threatens to have Legasov shot if he doesn’t tell him how a nuclear reactor works. There are a lot of people throughout the series who appear to act out of fear of being shot. This is inaccurate: summary executions, or even delayed executions on orders of a single apparatchik, were not a feature of Soviet life after the nineteen-thirties. By and large, Soviet people did what they were told without being threatened with guns or any punishment.
Her point was: this is not the Soviet way back then. My point is: these two people barely interacted directly, and one of them at least (Legasov) had a lot of respect for the other from the very beginning
I would have accepted that if it wasn't for Craig Mazin (the creator of the series) insistence that he stuck to the details and the truth in the series:
https://www.youtube.com/watch?v=yY0r1Ln6tkM
For the life of me I couldn't figure out what truth he is talking about (other than that Chernobyl happened, and some characters existed)
It seems the main faults that OP finds in the show are that Legasov had issues with his government, when in "reality" he thought they were great. But is that "reality," or oppression?
The tapes were framed in the HBO as an honest message of a dying man to the world to expose the lies that happened. Well, after Going through the tapes, I couldn't find any indication of that...only the opposite.
Now I concede that I don't really know what actually happened, and one can't put a price on the intensity of the situation for everyone at that time.
My point is simple: HBO series said Legasov's position was something that wasn't true
That was pretty dope! I love the idea of developing a tool a mid-step to developing another tool.
On a different note: I didn't get though the reason for the need to have an in-browser PPTX viewer. Can you elaborate more on the use case?
I studied prolog back in 2014. It was used in AI course. I found it very confusing: trying to code A*, N-Queens, or anything in it was just too much. Python, in contrast, was a god-send. I failed the subject twice in my MSc (luckily passing the MSc was based on the total average), but did a similar course in UC Berkeley, with python: aced it, loved it, and learned a lot.
Never again :D
I am learning Godot engine, going through the list of 20 games in order to build up my experience https://20_games_challenge.gitlab.io/
I am almost done with flappy bird (2nd challenge)
Why? I love the old arcade and game boy games, and I want to recreate them to my liking. I also love mechanical systems and space rovers, and I want ro build worlds to explore and simulate these things
A shoutout through the time, to those friends that went away, for the good and bad times
Because I mainly work with python, I am using Kivy (https://kivy.org/).
Earlier I was HTMX, Jinja templates, Flask, Tailwind and little vanilla JS. It was too inelegant for my taste.
I am considering moving to either Swift, or JS/Svelete
I am working on RL (with evolutionary algorithms) and artificial life, and I am trying to find the right setup (software, hardware) to accelerate my experiments. This benchmark is a step to illuminate the search space for me. Happy to hear your thoughts
Gosh this awesome! Thank you! That put a huge smile on my face ♥
I just read it in the referenced book section from the parent comment. It shocked the imaginary bubble where my mind is a bit. I want to reflect more on it.
Somehow, in the midset of all these LLM and diffusion models, the only thing that seems to catch attention is creativity. I've not thought of experience.
Why Tor is graded C, even though there are no downsides?
Of course humor :D
It was just cool to see it as the one odd point :)
I am curious too
I can't believe any of this made a difference in privacy. There is ZERO chance that the law can be enforced here. I've worked in few startups in Europe, no one understand their obligation, let alone the consequences from third party services.
This whole cookie banners, and GDPR in general, is as good as literature.
What is the name of that search engine?
I agree that this is what an effective search strategy is. But it is difficult to imagine an exploration this way. Exploration always imply that I don't know what I am looking for.
I am working on a plugin to filter DuckDuckGo the search results with LLM (the magic word). Perhaps that will help
I loved Keras at the beginning of my PhD, 2017. But it was just the wrong abstraction: too easy to start with, too difficult to create custom things (e.g., custom loss function).
I really tried to understand TensorFlow, I managed to make a for-loop in a week. Nested for-loop proved to be impossible.
PyTorch was just perfect out of the box. I don't think I would have finished my PhD in time if it wasn't for PyTorch.
I loved Keras. It was an important milestone, and it made me believe deep learning is feasible. It was just...not the final thing.
I am working on Omie, https://webapp.omie42.com/, yet another language learning tool :D
You start by learning the words: It augments the repetition aspect of Anki with added context to the words (random example sentences for each work, each time). I curated / generated the set of words in advance. Then you move to practice these words in chat about different topics (soon voice conversation as well). You get a feedback in each turn about what your mistakes, without interrupting the chat.
I am using DeepL for translation (I am not liking it though, since it is very narrow strict definitions. I will be exploring OpenAI for that soon). For chat, OpenAI GPT-4o.
This is my first webapp. I used HTMX + AlpineJS, Python, Supabase (Auth, S3, DB), and hosting on my PI.
It's work in progress, but I need to start finding core users to give feedback. I am not really sure how though. I had some tough experiences on Reddit and Discord (understandable tbh).
That was a lot of fun! Thank you :)
True, but if we take their word on it https://openai.com/enterprise-privacy
then i don't see an issue