Hello HN,

This is a simple web app for creating basic paper based plans using A4 paper.

A short write up: https://madebyenzo.com/#a4list

Hello HN,

This is a simple web app to test the Microsoft AI 2 transcription model.

It is quite interesting because it is both fast and highly accurate.

Hello HN,

This is a macOS app for offline transcribing.

You can use the new Apple Speech APIs or Whisper.

It has a batch queue interface, so you can watch many input sources, including external drives.

It is completely sandboxed in the App Store, so it is isolated from your system and can only read the files you explicitly give it access to.

It stores its transcription data in plain files, so they can be read without the app on any machine.

Hope you find it useful. Thanks, Enzo.

Hello HN.

This is an experiment of creating a simple progressive web app (can be installed as a mobile app) to test Microsoft's new MAI 1.5 transcription model.

The standout features of the MAI model are accuracy and speed.

The app converts your speech into plain text lists.

No sign up required.

I think this comes down to higher competition and practice in Europe.

A football is the default “toy” given to young lads, and you can play anywhere with anyone.

So much so there are custom “no ball games” signs in many neighbourhoods due to noise averse residents getting annoyed.

There are also many supporting elders who try to improve and guide skill development.

Related: I created an app to track the molecules in your foods:

https://kg.enzom.dev/

You specify your foods in grams with plaintext (no pictures).

I never liked the "take a picture to measure calories" approach, as you could have 10 table spoons of olive oil which would drastically change the calories but would not show in a picture.

This is really cool. I vibe coded almost exactly the same app, mine also tracks saturated fat, cholesterol, sodium, and fiber (I'm getting older so these macros are pretty important to me). One of the really cool things you can do if you have tool calling hooked up is to have the LLM analyze your diet and tell you what you can do better to hit your targets - swap pizza for pasta, decrease the amount of cheese you put on your sandwich, if you're gonna have fast food don't get the fries and eat low fat/low sodium the rest of the day, etc. What model are you using? I have found Qwen Flash to be really good for my app - smart enough, tool calling works really well, and very cheap.

Thanks.

It is using Gemini Flash 3 at the moment.

There is a lot to learn in nutrition. The glycemic load metric is quite revealing for pizza vs pasta (slow digesting carbs are supposed to be better). Al-dente cooked pasta is also slower digesting than well cooked pasta.

Another interesting thing is how each plant food has unique molecules that can be health promoting in humans. That was one aspect I wanted to reveal/compare for the foods I ate.

Dr Weil / Perfect Health Diet / Marks Daily Apple are three sources I like to check for information on nutrition.

esbuild has been very stable for my projects too.

I think it is the only tool in the JS ecosystem that has not broken after a few years.

PKCE protects the auth token from interception by making it so that only your code that started the flow can redeem it by proving they have the secret code_verifier on the redeem_token() call.

The code_challenge == sha256(code_verifier). You will share the code_challenge at the start of the flow.

I just watched this, it is very good.