If you are on react/next.js, defer the client side initialization until after your app has painted. PostHog (especially with their session recording feature) likes to initialize a little before the rest of your app…
> What you're describing is a behavior tree: predefined logic, predefined responses, no learning, no inference, no model. Stop calling everything AI, guys. Depends on how pedantic you want to get, one could argue that…
He is losing a lot of information in that normalization pipeline (whole shell reduced/feature engineered into nothing but an outline). A CNN or something similar would be better and he can maybe get a better depth map…
There is OpenCode and Pi, they both work pretty well
Why not use higher thinking effort?
Elenco is still around. I just bought a XP-720K linear power supply kit last week.
Have you tried Jetbrains Fleet? Their new editor isn't too bad.
We are working on making agentic ads and regulatory compliance scalable. https://hawtads.com Just launched the blog too https://blog.hawtads.com/
The original Kleene Star Regex was invented to model neural networks. Have you tried throwing a transformer at the problem /s? Also O(n²) but at least you get hardware acceleration ¯\(ツ)/¯ Here's Kleene's Representation…
Ooh good find, thanks for the link. This will be my bedtime reading for this week :)
I am more familiar with Bayesian than frequentist stats, but given that they are mathematically equivalent, shouldn't frequentist stats have an answer to e.g. the loss function of a VAE? Or are generative machine…
I think it would be interesting if frequentist stats can come up with more generative models. Current high level generative machine learning all rely on Bayesian modeling.
Well, hope they reinforced the wings, that's a massive weak point for dusters.
50 knots rotation is perfectly fine for a plane that size. A Cessna Skyhawk is certified to rotate at 55 knots fully loaded (and since the stall speed is around 40knots, for specialty take-offs like soft fields it's…
No, Claude on GitHub Copilot is billed at 3X the usage rate of the other models e.g. GPT-5.4 and you get an extremely truncated context window. See https://models.dev for a comparison against the normal "vanilla" API.
We are building an agentic ad tech system optimized for real time and scale. The process of making an ad, from ideation to distribution, is traditionally exceptionally labor intensive. We are making it possible to…
I have been working on the next generation of Canva and Photoshop for highly regulated verticals where there are specific demands placed on the generation and edit flow. https://hawtads.com If you are a brand who needs…
It could have exceeded either its real context window size (or the artificially truncated one) and the dynamic summarization step failed to capture the important bits of information you wanted. Alternatively, the…
Okay, here's the tl;dr: Attention based neural network architectures (on which the majority of LLMs are built) has a unit economic cost that scales (roughly) n^2 i.e. quadratic (for both memory and compute). In other…
Copilot and many coding agents truncates the context window and uses dynamic summarization to keep costs low for them. That's how they are able to provide flat fee plans. You can see some of the context limits here:…
Don't forget volume. Just having well structured content isn't enough, you need large volumes of content such that it makes a statistical difference during the training process.
Google ads are the cheapest yes, but depending on your audience they may not be looking on Google now. For ChatGPT (and similar) you need to have a strong FAQ page and lots of content marketing to increase the…
It's not just Facebook, the entire ads industry is heading in this direction. There's a seismic change going on right now.
If you are on react/next.js, defer the client side initialization until after your app has painted. PostHog (especially with their session recording feature) likes to initialize a little before the rest of your app…
> What you're describing is a behavior tree: predefined logic, predefined responses, no learning, no inference, no model. Stop calling everything AI, guys. Depends on how pedantic you want to get, one could argue that…
He is losing a lot of information in that normalization pipeline (whole shell reduced/feature engineered into nothing but an outline). A CNN or something similar would be better and he can maybe get a better depth map…
There is OpenCode and Pi, they both work pretty well
Why not use higher thinking effort?
Elenco is still around. I just bought a XP-720K linear power supply kit last week.
Have you tried Jetbrains Fleet? Their new editor isn't too bad.
We are working on making agentic ads and regulatory compliance scalable. https://hawtads.com Just launched the blog too https://blog.hawtads.com/
The original Kleene Star Regex was invented to model neural networks. Have you tried throwing a transformer at the problem /s? Also O(n²) but at least you get hardware acceleration ¯\(ツ)/¯ Here's Kleene's Representation…
Ooh good find, thanks for the link. This will be my bedtime reading for this week :)
I am more familiar with Bayesian than frequentist stats, but given that they are mathematically equivalent, shouldn't frequentist stats have an answer to e.g. the loss function of a VAE? Or are generative machine…
I think it would be interesting if frequentist stats can come up with more generative models. Current high level generative machine learning all rely on Bayesian modeling.
Well, hope they reinforced the wings, that's a massive weak point for dusters.
50 knots rotation is perfectly fine for a plane that size. A Cessna Skyhawk is certified to rotate at 55 knots fully loaded (and since the stall speed is around 40knots, for specialty take-offs like soft fields it's…
No, Claude on GitHub Copilot is billed at 3X the usage rate of the other models e.g. GPT-5.4 and you get an extremely truncated context window. See https://models.dev for a comparison against the normal "vanilla" API.
We are building an agentic ad tech system optimized for real time and scale. The process of making an ad, from ideation to distribution, is traditionally exceptionally labor intensive. We are making it possible to…
I have been working on the next generation of Canva and Photoshop for highly regulated verticals where there are specific demands placed on the generation and edit flow. https://hawtads.com If you are a brand who needs…
It could have exceeded either its real context window size (or the artificially truncated one) and the dynamic summarization step failed to capture the important bits of information you wanted. Alternatively, the…
Okay, here's the tl;dr: Attention based neural network architectures (on which the majority of LLMs are built) has a unit economic cost that scales (roughly) n^2 i.e. quadratic (for both memory and compute). In other…
Copilot and many coding agents truncates the context window and uses dynamic summarization to keep costs low for them. That's how they are able to provide flat fee plans. You can see some of the context limits here:…
Don't forget volume. Just having well structured content isn't enough, you need large volumes of content such that it makes a statistical difference during the training process.
Google ads are the cheapest yes, but depending on your audience they may not be looking on Google now. For ChatGPT (and similar) you need to have a strong FAQ page and lots of content marketing to increase the…
It's not just Facebook, the entire ads industry is heading in this direction. There's a seismic change going on right now.