Places to discuss Feeds Fun

I continue developing my news reader: feeds.fun. To gather information and people together, I created several resources where you can discuss the project and find useful information:

• Blog blog.feeds.fun
• Discord server
• Reddit r/feedsfun

So far, there is no one and nothing there, but over time, there will definitely be news and people.

If you are interested in this project, join! I'll be glad to see you and will try to respond quickly to all questions.

Grainau: hiking and beer at 3000 meters

For her vacation, Yuliya decided to show me the beautiful German mountains and took me for a couple of days to Grainau — it's a piece of Bavaria that's almost like Switzerland. At least, it is similar to the pictures of Switzerland that I've seen :-D

In short, it's a lovely place with a measured pace of life. If you need to catch your breath, calm your nerves, and enjoy nature, then this is the place for you. But if you can't live without parties, you'll get bored quickly.

What's there:

• The highest mountain in Germany plus a couple of glaciers.
• There's skiing in winter. If you really need it, you can find a place to ski in summer, but the descent is short, and the lifts are turned off.
• A large clean lake and a couple of smaller ones.
• A huge number of trails for hiking.
• A huge number of waterfalls, streams, and a couple of mountain rivers.
• Restaurants with beer.
• Beautiful fallen trees in the forests, private property, fences, cows with bells, and "racing tractors" (I don't know how to name this phenomenon better, but tractors are moving fast there :-D).

This is briefly, and now in detail.

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Migrating from GPT-3.5-turbo to GPT-4o-mini

Recently OpenAI released GPT-4o-mini — a new flagship model for the cheap segment, as it were.

• They say it works "almost like" GPT-4o, sometimes even better than GPT-4.
• It is almost three times cheaper than GPT-3.5-turbo.
• Context size 128k tokens, against 16k for GPT-3.5-turbo.

Of course, I immediately started migrating my news reader to this model.

In short, it's a cool replacement for GPT-3.5-turbo. I immediately replaced two LLM agents with one without changing prompts, reducing costs by a factor of 5 without losing quality.

However, then I started tuning the prompt to make it even cooler and began to encounter nuances. Let me tell you about them.

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Computational mechanics & ε- (epsilon) machines

I found a few new concepts for tracking.

Computational mechanics

There is computational mechanics, which deals with numerical modeling of mechanical processes and there is an article about it on the wiki. This post is not about it.

This post is about computational mechanics, which studies abstractions of complex processes: how emergent behavior arises from the sum of the behavior / statistics of low-level processes. For example, why the Big Red Spot on Jupiter is stable, or why the result of a processor calculations does not depend on the properties of each electron in it.

ε- (epsilon) machine

The concept of a device that can exist in a finite set of states and can predict its future state (or state distribution?) based on the current one.

Computational mechanics allows (or should allow) to represent complex systems as a hierarchy of ε-machines. This creates a formal language for describing complex systems and emergent behavior.

For example, our brain can be represented as an ε-machine. Formally, the state of the brain never repeats (voltages on neurons, positions of neurotransmitter molecules, etc), but there are a huge number of situations when we do the same thing in the same conditions.

Here is a popular science explanation: https://www.quantamagazine.org/the-new-math-of-how-large-scale-order-emerges-20240610/

P.S. I will try to dig into scientific articles. I will tell you if I find something interesting and practical. P.P.S. I have long been thinking in the direction of a similar thing. Unfortunately, the twists of life do not allow me to seriously dig into science and mathematics. I am always happy when I encounter the results of other people's digging.

My GPTs and prompt engineering

I've been using ChatGPT almost since the release of the fourth version (so for over a year now). Over this time, I've gotten pretty good at writing queries to this thing.

At some point, OpenAI allowed customizing chats with your text instructions (look for Customize ChatGPT in the menu). With time, I added more and more commands there, and recently, the size of the instructions exceeded the allowed maximum :-)

Also, it turned out that a universal instruction set is not such a good idea — you need to adjust instructions for different kinds of tasks, otherwise, they won't be as useful as they could be.

Therefore, I moved the instructions to GPT bots instead of customizing my chat. OpenAI calls them GPTs. They are the same chats but with a higher limit on the size of the customized instructions and the ability to upload additional texts as a knowledge base.

Someday, I'll make a GPT for this blog, but for now, I'll tell you about two GPTs I use daily:

• Expert — answers to questions.
• Abstractor — makes abstracts of texts.

For each, I'll provide the basic prompt with my comments.

By the way, OpenAI recently opened a GPT store, I'd be grateful if you liked mine GPTs. Of course, only if they are useful to you.

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