will to code

I just finished understanding how the image encoder works 😅 Ya this project ain't getting finished today

#friday

SuperTonic a TTS model that can run on an e-reader Huggingface | Website

I ran qwen-3 0.6B model which is only 500mb on my laptop and it generated this website for a restaurant we are at the precipice of something

Insane price to quality ratio

There's so much stuff coming out right now its hard to keep up $0.0025/image 0.84s/image ⚡️ 6B parameter https://huggingface.co/Tongyi-MAI/Z-Image-Turbo

So far African tech bros were making a very decent living doing the usual programming jobs. Now AI is one shotting them and we will all be forced into doing the real hard technical jobs that AI isn't good at Net benefit for the continent everything is e/acc everything is adaptation

Great ads worked because they were rare and hard to make If everyone can make great ads then people will just get desensitized to it Ads already have such a low conversion rate. The reason that huge companies like coca cola show ads is to subconsciously influence your decision making. They are maintaining a brand not trying to grow it. So just because you can make an amazing high quality ad, it doesn't mean you'll get users. I'm very skeptical on media generation. I'm willing to change my mind but only when I see it's utility in the future. Let the dopamine rush die out and let's see people use it then.

Today's project was an interesting experiment When Copilot first launched, LLMs were relatively weak and slow. We were forced to train custom, small-parameter code completion models, and that became the industry standard. But why are we still doing that? General purpose llms have become powerful and we now have inference providers that deliver 2000+ tok/sec So, I decided to test a new approach. I used gpt-oss-120b on Cerebras to build a tab-autocomplete extension for VSCode. Its as fast as copilot and sometimes faster (with reasoning enabled lol) The major advantage here is flexibility. For instance, I was able to get the model to treat comments as prompts and actionable instructions, rather than wasting tokens (like copilot) auto-completing them. The sky is the limit here. This approach could eventually replace chat interfaces, have a auto-complete.md, and make agentic decisions. Much more to explore in the future! 🤟 [Code]

#friday is here

Quick update I'm pivoting to two products

An epic open source contribution from meta

The only real way to benchmark it is when you run into difficult problems you yourself can't solve All the fancy websites don't really mean anything... they just trained the model on a better dataset

Lets see what the hype was all about

There shall be no projects for this Friday I got caught up in something and now I'm too tired to code

Its already #friday

My YouTube algo is peak Ya we normally don't have the mental model that lets us comprehend exponential growth. Rewatched the ending multiple times

Something you will never hear in Apple "We need to release X product quickly before the competition" They are literally just cooking they dgaf about competition