XAI PromptIDE

>Participation in the early access program is currently limited to verified users.

Only paying users.

Isn't Grok their first product? This seems to be tooling for their main product.

I understand what you are saying. When OpenAI's API was still new, there was a LOT of "prompt engineering" required - a lot of proper formatting and tricks to get it to produce the required output, proper ways of formatting prompts with "few-shot" examples, etc. Packages like LangChain sprang up because trying to chain together multiple prompts with different inputs and outputs was becoming a bear.

But then, within a few months, the LLM's got better and better to the point where the average ChatGPT user doesn't need to be a "prompt engineer" to get what they want. Sure, there are tricks with adding specific phrases to a prompt to get it to do a better job, but what we now consider "prompt engineering" and what was "prompt engineering" pre-ChatGPT are very different.

LangChain, for example, has reacted by pivoting away from just prompt chaining and templating and into an ecosystem for agents and automated AI "bots". I think that may be overkill for many use cases, and there are good alternatives (Rivet is now my go-to) if you still want to build an LLM-powered app that just requires a specific logical path and specific inputs and outputs, but honestly if I was working at an "AI startup" I would probably be trying to focus my time on getting away from "prompts" and more just to "doing a good job of what you are told".

I do think that "prompts" (especially chat-style conversations) lack a lot of the nuance that you need for a production-grade app especially when it comes to specific input and output formats, etc. Function calling helps a lot but I don't see why xAI is focusing on an IDE for writing a great prompt instead of building an LLM that can make good, structured output with just an "ok" prompt.

The next year will be interesting - it hasn't even been a full year since ChatGPT was released, and look how far the industry has come since the closed-beta release of GPT-3.

what?

If you want standard responses then presumably LLMs will start to converge on those responses. But if you want a non-standard response then you have to ask for it, and I think that will continue to be a kind of "prompt engineering".

For instance I'm working in math problem generation right now and you could imagine saying "make the problem harder" and you'll get back... something. But what does "harder" really mean? It's very underspecified. If you work in making educational material you probably have some much clearer criteria, and if you are building a product you may have a clear point of view about what you want in the next problem in a sequence... and "harder" is just punting on all these details.

The tricks may stop being as necessary, but the deciding what you want and how to explain what you want seems essential no matter how smart the LLM is.

I suppose it's always a correct decision to vertically integrate and invest heavily in tooling, from a pure monopolist standpoint. Doing so reduces stakeholders and improve control, which should grant more power to management than constantly having to succumb to engineering, market or baseline reality.

But e.g. very few laptop manufacturers are even capable of designing and fabricating own display panels(not sure Apple does?), let alone ones that provide any advantages, so there's that.

Yeah… how much of an advantage is this over putting your prompts under source control?

do some research about how these models work and what prompts are.

It’s the sort of thing an engineering team builds when they have way too much time and no idea what to build. There is zero reason to use something like this over, say Jupyter notebooks and the advantages of notebook are obvious: actual researchers are already familiar with it, you can integrate everything into your data science workflow, visualise results etc

Would you mind posting a screenshot of your phone screentime? Just curious

Unfollow people that follow him and you won't get this content. My content used to be all over the place as well. After I've done the pruning, now it's various people talking about topics that I care about. Obviously it's not perfect - things leak through, but far better.

Same with Facebook, my feed is now pretty much photos and news from friends and family.

It’s your algorithm. I mostly see content where he’s being dunked on or Tesla is the butt of a joke.

This is easily explained but not in a positive way. X Subscribers get up-ranked in replies and For You. 99% of anyone who would subscribe to X are Elon Fans. As a result, you get the fanboys.

I was going to say that I never saw anything like that, but I remembered I followed Musk's advice the day he recommended it: I disabled recommendations and only use the "follows" view.

I dont have that experience at all, and im a tesla owner. I see more negative tesla stuff than positive, especially about stock value and cybertruck quality problems.

I think clicking "Not interested" button is optional. You can just straight up block the content, and adblock any "You might also like".

This is my bigoted view, but my interpretation of "you are the product" principle in freemium model is that they pay you in perceived value. Not the other way around, nor in cash. So, onus is on them to bring you values you recognize.

This is just an ad hominem pretending to be civil discourse. The topic is XAI, and you're talking about Musk instead.

Eclipse, but for Python instead of Java, and a textbox instead of Bonzi Buddy

is there any evidence of this?

even if this is true, to be fair to elon he donated to openai when it was a nonprofit and through some sketchy moves it was turned into a for-profit company where his donation should now be seen as an investment

That's absolutely false. It's trivial to prove that OpenLlama is both more transparent (details on how it's trained), and more open (better license, and public training code).

Llama 2 doesn't even mention the dataset used, so it's not very transparent.