jerpint

8 ms·

91.
by jerpint 2y ago
just today using ffmpeg , I was thinking how useful it would be to have an LLM in the logs, explaining what the command you just ran will do
92.
by jerpint 2y ago
There are so many opportunities for google to improve their services. For example, I found myself asking Claude about places to see in a city I’m visiting while switching back and forth to gmaps. This would have been a much better experienc
93.
by jerpint 2y ago
So basically canibalizing Siri ?
94.
by jerpint 2y ago
Airbnb still has better selection than most platforms, especially for longer term rental. also having comments and ratings of hosts is useful when booking overseas. It is always possible to contact the host directly and bypass the platform,
95.
by jerpint 2y ago
I think there will be lessons learned here as well for better agentic systems writing code more generally; instead of “committing” to code as of the first token generated, first generate overall structure of code base, with abstractions, an
96.
by jerpint 2y ago
I should specify that unfortunately I didn’t store the raw output from the LLM, just the parsed code snippets they produced, but the code to reproduce it is all there
97.
by jerpint 2y ago
Author here: the point of the article was only to evaluate zero-shot capabilities. I’m certain that had I used LLMs I would have definitely gotten more stars on AoC (got 41/50 without). Because I chose to solve this year without LLMs,
98.
by jerpint 2y ago
The code they generated and the outputs (including trace back errors) is all included, you can view them on the post itself or from hf space: https://huggingface.co/spaces/jerpint/advent24-llm
99.
by jerpint 2y ago
Author here: all the code to reproduce this is actually all on the huggingface space here [1] https://huggingface.co/spaces/jerpint/advent24-llm/tree/main
100.
Performance of LLMs on Advent of Code 2024(jerpint.io)
135 points by jerpint 2y ago|92 comments
101.
by jerpint 2y ago
It looks much better than Sora but still kind of in uncanny valley
102.
by jerpint 2y ago
This looks like it would be really useful for multimodal LLMs
103.
by jerpint 2y ago
We’re definitely going to need better benchmarks for agentic tasks, and not just code reasoning. Things that are needlessly painful that humans go through all the time
104.
by jerpint 2y ago
The yolo models are “dumb” black box object detectors, it’s a supply chain attack, the model itself was very likely never touched
105.
by jerpint 2y ago
Their docs are very fun to read. I’d probably recommend starting with the “transformers” library for python if you want to play with some language models e.g. Bert: https://huggingface.co/docs/transformers/en/
106.
by jerpint 2y ago
Basically equivalent to GitHub but for models. Anyone can upload anything, but it kind of standardizes tools and distribution for everyone. They also have a team that helps integrate releases for easier use and libraries for fine tuning
107.
by jerpint 2y ago
I have a sneaking suspicion OpenAI will announce something very similar in a few days
108.
by jerpint 2y ago
StyleTTSv2 is pretty good and open source, you can easily traverse its latent space for voice
109.
by jerpint 2y ago
im not sure what you mean - the embedding model is independent of the embeddings themselves. Once generated, the embeddings and vector store should exist 100% locally and thus not part of any secret sauce
110.
by jerpint 2y ago
Somewhat agreed for use cases of text classification, but for anything requiring more language understanding it is a desirable property
111.
by jerpint 2y ago
> In summary, we used a 2.4-million-parameter small language model to achieve accuracy comparable to a 100-million-parameter BERT model in text classification. Neat, but the question will be how the scaling laws hold up
112.
by jerpint 2y ago
I’m really excited for where this is going. From the demo videos, it seems to be a step up from Oasis, which itself came out only 2 weeks ago. I expect to see a lot of innovative use cases in this field
113.
by jerpint 2y ago
Sadly this is seen at so many prestigious ML conferences, a trimmed X axis which makes performance seem significant when it’s sometimes incremental
114.
by jerpint 2y ago
I wonder at what point it will be ~as much overhead to pass through a subset of the data with a small yet capable and fast LLM vs. using a crude dot product when doing retrieval
115.
by jerpint 2y ago
Same here, to be honest I never gave much thought to seeking alternatives, but this one looks really nice, especially having the line numbers and similar layout to GitHub diffs
116.
by jerpint 2y ago
Does anyone know of a “copilot” style autocomplete in the CLI? I don’t want it to run anything for me, just predict what command I might type next
117.
by jerpint 2y ago
Do you have proof for this? Why accuse one team and not the other?
118.
by jerpint 2y ago
This is a very impressive demo, this seems very early in a what might in hindsight be an “obvious” direction to take transformers towards
119.
by jerpint 2y ago
Having a hotkey to access the app removes a lot of friction
120.
by jerpint 2y ago
Just remember that retrieval is the real bottleneck in RAG, so your problem could very much be related to how you create and embed your chunks and not the model you’re using

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