Recently, I unexpectedly encountered a justice system in the USA.
What conclusions can be drawn from this:
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:
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.
Recently OpenAI released GPT-4o-mini — a new flagship model for the cheap segment, as it were.
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.
Nate Silver — the author of "The Signal and the Noise" — is widely known for his successful forecasts, such as the US elections. It is not surprising that the book became a bestseller.
As you might guess, the book is about forecasts. More precisely, it is about approaches to forecasting, complexities, errors, misconceptions, and so on.
As usual, I expected a more theoretical approach, in the spirit of Scale [ru], but the author chose a different path and presented his ideas through the analysis of practical cases: one case per chapter. Each chapter describes a significant task, such as weather forecasting, and provides several prisms for looking at building forecasts. This certainly makes the material more accessible, but personally, I would like more systematics and theory.
Because of the case studies approach, it isn't easy to make a brief summary of the book. It is possible, and it would even be interesting to try, but the amount of work is too large — the author did not intend to provide a coherent system or a short set of basic theses.
Therefore, I will review the book as a whole, provide an approximate list of prisms, and list some cool facts.
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:
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.