Pinging @stevenbyrnes : do you agree with me that instead of mapping those protoAGIs to a queue of instructions it would be best to have the AGI be made from a bunch of brain strcture with according prompts? For example "amygdala" would be in charge of returning an int between 0 and 100 indicating feat level. A "hypoccampus" would be in charge of storing and retrieving memories etc. I guess the thalamus would be consciousness and the cortex would process some abstract queries.

We could also use active inference and bayesian updating to model current theories of consciousness. Even use it to model schizophrenia by changing the number of past messages some strctures can access (i.e. modeling long range connection issues) etc.

To me that sounds way easier to inspect and align than pure black boxes as you can throttle the speed and manually change values like make sure the AGI does not feel threatened etc.

Is anyone aware of similar work? I've created a diagram of the brain structures and its roles in a few minutes with chatgpt and it seems super easy.

This reminds me of an idea : I think it would be great to hold a bi-monthly competition where people try to do something as incredible as possible in just 30 minutes using LLMs or other AIs. The winner being decided by a select few.

To reduce my sleep inertia I've created an app for my 25$ micropython smart watch (Pinetime from Pine64). Here's the link: https://github.com/thiswillbeyourgithub/sleep_tracker_pinetime_wasp-os

Aside from the motion tracking, it's able to vibrate very faintly at T minus 10 minutes, 7, 5, 2, 2, 1, 0.5 minute from waking up. Then vibrates gradually to wake me up gently.

It also automatically tells you when you should set your wake up time to optimize sleep cycle.

I think it works very well but I'm very biased.

Sharing my setup too:

Personnaly I'm just self hosting a bunch of stuff:

• litellm proxy, to connect to any llm provider
• langfuse for observability
• faster whisper server, the v3 turbo ctranslate2 versions takes 900mb of vram and are about 10 times faster than I speak
• open-webui, as it's connected to litellm and ollama, i avoid provider lock in and keep all my messages on my backend instead of having some at openai, some at anthropic, etc. Additionally it supports artifacts and a bunch of other nice features. It also allows me to craft my perfecr prompts. And to jailbreak when needed.
• piper for now for tts but plan on switching to a selfhosted fish audio.
• for extra privacy I have a bunch of ollama models too. Mistral Nemo seems to be quite capable. Otherwise a few llama3, qwen2 etc.
• for embeddings either bge-m3 or some self hosted jina.ai models.

I made a bunch of scripts to pipe my microphone / speaker / clipboard / llms together for productivity. For example I press 4 times on shift, speak, then shift again, and voila what I said was turned into an anki flashcard.

As providers, I mostly rely on openrouter.ai which allows to swap between providers without issue. These last few months I've been using sonnet 3.5 but change as soon as there's a new frontier model.

For interacting with codebases I use aider.

So at the end all my cost comes from API calls and none from subscriptions.

Very interesting of you to think of it that way. It turns out that it's very in line with recent results from computation psychiatry. Basically in depression we can study and distinguish how much the lack of activity is due to "lack of ressource to act" vs "increased cost of action". Both look clinically about the same but underlying biochemical pathways differ, so it's a (IMHO) promising approach to shorten the times it takes for a doctor to find the appropriate treatment for a given patient.

If that's something you already know I'm sorry, I'm short on time and wanted this to be out :)

Just a detail : Haven't retinoids been discovered when looking for cancer treatments? I thought it was the origin story behind isotretinoin.

My personnal solution to this is to mostly use Anki for everything and anything.

1. It helps not loose my momentum: if I see my cards about the beginning of the articles about transformers it increases my chance of finishing the article
2. It garuantees that I never get the dreaded my knowledge is limited to a couple of related keywords ("self-attention", "encoder"/"decoder") with no real gears-level understanding of anything. feeling. Making it all the more easier to get back to reading.

In fact I hate the number 2 feeling so much that it was a huge motivation to really master Anki. (1300 day streak or so with no sign of regret whatsoever)

I think very cheap carabiners are extremely fragile especially for repeated use. I saw a failing mode where the mobile axis just opens in the wrong way by going around the stator. Keep that in kind when choosing which carabiner to use.

Might be better to keep using ring keyholders but have one decently strong carabineer to hold the rings together instead of what you did : tiny carabiners that hols onto a ring no?