jstx1

21 ms·

211.
by jstx1 3y ago
Very cool, I want to experiment with building something similar. Is there any point in using langchain for this or can you add your own glue code to the API results?
212.
by jstx1 3y ago
I'd rather have more concrete documentation of the API, the current version is structure more like a long tutorial.
213.
by jstx1 3y ago
Compare it to reading stackoverflow or a tutorial on something that you can't quite do yet - the answer on SO might be wrong, or it might work in a different context from yours, or might work but not be the optimal solution; the tutori
214.
by jstx1 3y ago
How can a person read this?
215.
by jstx1 3y ago
You're arguing with a point that I haven't made. > I'm seeing rampant use of ML now for problems we already know how to solve in much simpler ways: linear control theory, bayesian statistics, Kalman filters, etc. How many
216.
by jstx1 3y ago
You can use libraries like faiss or ann for the search, you don't need a vector database when you work at small-to-medium scale.
217.
by jstx1 3y ago
Anyone who wants this can implement their own library themselves? When has this worked for any problem ever? Searching efficiently is a problem, and there's several open source and proprietary solutions but I don't get how you can
218.
by jstx1 3y ago
You should really know that there's more to ML than neural networks. Those are the simpler approaches I was referring to (like linear models, ensemble models etc). They are 1. Machine learning. 2. Not neural networks. 3. Not in Norvig&
219.
by jstx1 3y ago
There's nothing intrinsically nuclear about ML and it includes a bunch of simple approaches too. The advice to spend your limited time and attention on outdated approaches seems counterproductive. The things in this book aren't ju
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by jstx1 3y ago
The metaphor only works if you assume that software has only aesthetic utility.
221.
by jstx1 3y ago
If it's for work or for building something useful, the book is a waste of time. If it's for your personal interest, you can read and learn anything you want. Personally I avoid books like this one (similar to how I avoid very esot
222.
by jstx1 3y ago
There's many keywords that make good column names though - user, id, name, date, version, timestamp.
223.
by jstx1 3y ago
> We realized (...) that we can dramatically improve its ability in math and tutoring if we allow the AI to think before it speaks. This is from Sal Khan's TED talk on how they're integrating ChatGPT into Khan Academy - https:
224.
by jstx1 3y ago
I asked the question knowing that he's a co-founder and chief scientist at OpenAI. Being in his position doesn't automatically mean that he's contributed meaningfully.
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by jstx1 3y ago
Has he contributed that much personally? I thought a lot of the success of ChatGPT is some good ideas from lower ranked researchers + great engineering.
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by jstx1 3y ago
The number of games does influece the stability of the ratings but the result is the opposite - classical ratings are more reliable because there are regular organised events while there are very few serious blitz and rapid events. Most top
227.
by jstx1 3y ago
How good you are at your job is by far the smallest factor out of the 3 you listed.
228.
by jstx1 3y ago
They offer products and services, companies pay for their products and services. When everyone else was inflating massively, they didn't, so now that the markets have turned they don't have a lot of deflating to do.
229.
by jstx1 3y ago
> And don't get me started on Humans Need Not Apply. Well now you have to tell us. :) Many of the concrete examples in that video are exaggerated and/or misunderstood but the general question it asks - what to do when automatio
230.
by jstx1 3y ago
Does stuff like this help anyone? I still haven’t forgiven CGP Grey for changing the title to his 2017 ML video to “How AIs, like ChatGPT, learn”. The video is about genetic algorithms and has nothing to do with ChatGPT. (or with anything e
231.
by jstx1 3y ago
IBM (without RedHat) still have hundreds of thousands of employees doing work and generating tens of billions of revenue. Whether it's of value depends on how cynical you feel today but IBM is very far from being just RedHat.
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by jstx1 3y ago
1. In-context learning - you can teach the model things without retraining the underlying model parameters. 2. Actual model updates (it's not like we'll be stuck with the 2023 version forever).
233.
by jstx1 3y ago
1. Very expensive - why do you care? 2. Opinionated - not necessarily bad, and can be tuned. 3. Politically biased - that's a bullshit criterion. You want a tool that's reasonably objective - being in the middle between the two cu
234.
by jstx1 3y ago
ChatGPT with GPT4 has made me much better and faster at solving programming problems, both at work and for working on personal projects. Many people are still sleeping on how useful LLMs are. There's a lot of related things to be skept
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by jstx1 4y ago
This announcement, including the leadership changes, sounds more like they've shut down DeepMind and moved everyone over to Google Brain. Keeping the DeepMind name for the new team is a clever trick to make it look like more positive n
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by jstx1 4y ago
It's like bragging about earning a good salary and then it turns out that you work for your dad.
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by jstx1 4y ago
> It's tough for me to compare Google DeepMind to OpenAI GPT4. Is it tough because one of these is a newly merged and rebranded team and the other is a machine learning model?
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by jstx1 4y ago
Is it bad that I can't tell which one was focused on products? It seems like neither of them was.
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by jstx1 4y ago
Smaller % of training data doesn't necessarily mean lower quality.
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by jstx1 4y ago
Ilya Sutskever from OpenAI saying that the data situation is good and there's more data to train on - https://youtu.be/Yf1o0TQzry8?t=657

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