Migrating from GPT-3.5-turbo to GPT-4o-mini
Guess when I switched models.
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.
Concept document for a space exploration MMO
The expected poster for the game. (c) DALL-E
As a hobby, I write concept documents for games. This is first in English. I have a few more in Russian and will eventually translate them.
One more concept for The Tale 2.0.
Title
Lords Captains MMO
Yep, it's a rip-off from Warhammer 40k and Rogue Trader, but it will do for the concept.
One-liner
Explore the infinite universe on a starship with millions of souls on board, unite and develop abandoned worlds.
Platforms
Browsers, mobile.
Genre
Exploration-driven trade-political MMO PVE sandbox.
Closest analogs
EVE, Sim City, Crusader Kings, 4X games, Rogue Trader.
My GPTs and prompt engineering
Ponies are doing prompt engineering (c) DALL-E
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.
Simulating public opinion in a game
The demonstration (in Russian) of a technical prototype of manipulating public opinion and explanation of how it works.
I continue participating in World Builders school. For the last month, I've created a technical prototype of game mechanics for manipulating public opinion.
You play as the chief editor of a news agency, who sends journalists on quests and publishes articles based on the results of investigations focusing on themes that you want to promote.
The top video is in Russian, so I'll go through the main points below.
Procedural news headlines without complex text generation
A screenshot of the interface for selecting a news connotation (from the prototype of the game about a news agency). News: the arrest of a teenage witch for drunk driving.
From the player preference survey, I gradually moved on to working on a game prototype.
The game will be about a news agency. You will be the chief editor, and your task is to manipulate public opinion by investigating events and choosing a connotation of news: where to draw the public's attention, what to hide, in what tone to present themes, etc.
Therefore, the whole game will be around the text of news.
Creating large blocks of detailed text for each news item looks pointless — the game is not about reading news but about managing them. Therefore, it makes sense to build interaction only around headlines.
But how can we make the displaying of news both interesting and simple?