Unless you have a balanced diet that anticipates your workouts and gives you the proper amount of sodium, potassium and magnesium. Sports drinks are just selling you those at a big premium. Stick with water. Eat a banana.

Isn’t it the opposite then? Since your windows will have vertical scrolls, it makes sense to tile them horizontally in order to maximize vertical space for each window, imo.

There are lots of people who could use them. Schools, libraries, poor people.

No.

It does more than that, it magnifies, feeds and perpetuates them. It’s not just simple exposition.

OP sounds like he’s making a data compression pitch, but I think you have the better idea. I think surrounding the picture with a lot of contextual data about when/why/how this picture was taken will absolutely help recall and connecting to related concepts.

Essentially, you don’t ask them to use their internal knowledge. In fact, you explicitly ask them not to. The technique is generally referred to as Retrieval Augmented Generation. You take the context/user input and you retrieve relevant information from the net/your DB/vector DB/whatever, and you give it to an LLM with how to transform this information (summarize, answer a question, etc).

So you try as much as you can to “ground” the LLM with knowledge that you trust, and to only use this information to perform the task.

So you get a system that can do a really good job at transforming the data you have into the right shape for the task(s) you need to perform, without requiring your LLM to act as a source of information, only a great data massager.

I’ve been using LLMs pretty extensively in a professional capacity and with the proper grounding work it becomes very useful and reliable.

LLMs on their own is not the world changing tech, LLMs+grounding (what is now being called a Cognitive Architecture), that’s the world changing tech. So while LLMs can be vulnerable to bullshitting, there is a lot of work around them that can qualitatively change their performance.