tkellogg

9 ms·

61.
Python library for logging carbon footprint(codecarbon.io)
2 points by tkellogg 2y ago|1 comments
62.
by tkellogg 2y ago
I think Claude is on AWS
63.
by tkellogg 2y ago
Perplexity is also out for me. That uses `gpt-3.5-turbo` via the API, so I assume the API might be having trouble too, but `llm` seems to work fine with `gpt-3.5-turbo`
64.
by tkellogg 2y ago
The OpenAI philosophy is that adding modes improves everything. Sure, it’s astronomically expensive, but I tend to think they’re on to something.
65.
by tkellogg 2y ago
not OP, but for the "unique identifiers", you can think of it like the footnote style of markdown links. Most of these models are fine-tuned to do markdown well, and a short identifier is less likely to be hallucinated (my philoso
66.
by tkellogg 2y ago
This is obviously a joke, but I wonder if there's something to it. A recommendation engine to surface interesting jobs to a candidate, and quality candidates to an employer. It seems like recruiters/sourcers are inefficient at doi
67.
by tkellogg 2y ago
what even is “a model”? I’m not sure there is a technical definition that corresponds to how it’s used by the tech public - single interconnected neural network (LLM attention layers break this, autoencoders complicate this) - single traini
68.
by tkellogg 2y ago
I’m immediately skeptical of the methods. When I was a kid, doctors would shove antibiotics on you if you even coughed. The families where that wasn’t the case had a definite vibe , so this is screaming confounded variables to me. Who know
69.
by tkellogg 3y ago
looks like they have it now https://optuna.readthedocs.io/en/stable/reference/generated/...
70.
by tkellogg 3y ago
I recall when my team chose MongoDB ~2011, Postgres & friends didn't have JSON columns, so there was a lot of extra data modelling that probably was unnecessary. The biggest use case for MongoDB was for huMongous data. Obvs MongoDB
71.
by tkellogg 3y ago
Yeah, I'd argue that transformers created such capital saturation that there's a ton of opportunity for alternative approaches to emerge.
72.
by tkellogg 3y ago
OTOH having the chart start at zero would REALLY emphasize how saturated this field is, and how little this announcement matters.
73.
by tkellogg 3y ago
wow, so easy!
74.
Fossil: Social Media Optimized for Your Time(fossil-social.com)
2 points by tkellogg 3y ago|0 comments
75.
by tkellogg 3y ago
It depends what problem you're solving. If it's a high frequency request, like a chat response, it's far too inefficient. Most web APIs would consider it bad practice to read 2MB of data on every request, even worse when you
76.
by tkellogg 3y ago
costs rise on a per-token basis. So you CAN use 10M tokens, but it's probably not usually a good idea. A database lookup is still better than a few billion math operations.
77.
by tkellogg 3y ago
researchers don't read tutorials, they cross check each other's work. You need details to do that.
78.
by tkellogg 3y ago
are you pushing PHI/PII through github actions?
79.
by tkellogg 3y ago
Why did WPF go out of style? (or did it? idk) It seems like a good pattern, but it's always good to look at historical cases for the gotchas
80.
by tkellogg 3y ago
nah, it's just proof that I didn't LLM my blogs into existence ;)
81.
by tkellogg 3y ago
FYI for windows, I made this a long time ago: https://github.com/tkellogg/Jump-Location Which was fun and all, but eventually replaced by a pure PowerShell implementation that's become far more active: https:&#x2
82.
Htmx Is Composable?(timkellogg.me)
85 points by tkellogg 3y ago|68 comments
83.
by tkellogg 3y ago
I made fossil for this purpose. Sometimes the good stuff is regular social posts, sometimes it’s links. The only way to separate the wheat from the chaff is AI (imo) https://timkellogg.me/blog/2024/01/03/
84.
It's Application Phishing, Not Prompt Injection(timkellogg.me)
1 points by tkellogg 3y ago|0 comments
85.
Birb and Fossil: An RSS Revival?(timkellogg.me)
49 points by tkellogg 3y ago|54 comments
86.
by tkellogg 3y ago
OP here. Sorry you had that experience. I recently started doing it. Prior to the AI images, I got a lot of complaints about a “wall of text”, so I was looking for a way to break it up, but also not invested enough to spend much time on it.
87.
by tkellogg 3y ago
OP here. Yeah, it’s also extremely low-risk. The sensitive part of the algorithm is the embeddings. This part is just making the group human readable. The reason I didn’t do mistral the first time is because I’m lazy. I gave myself 3-4 hour
88.
A better Mastodon client?(timkellogg.me)
88 points by tkellogg 3y ago|45 comments
89.
by tkellogg 3y ago
anyone out there generating fediverse feeds for their static site?
90.
by tkellogg 3y ago
not sure, but you could also look at the inverse. e.g. a 90% to 95% improvement could also be interpreted as 10% failure to 5% failure, i.e. half the amount of failures, a very big improvement. It depends on a lot of things, but it's p

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