😺 GPTs (pt. 3)

PLUS: this AI hallucinates 27.2% of the time!

Welcome, humans.

And welcome to The Neuron. Think of us as the CyberTruck of AI, expertly steering you through the rough terrain of AI with bulletproof security and swagger.

Here’s what you need to know about AI today:

  • GPTs are now emerging for a variety of use cases.

  • GPT-4 hallucinates way less than Bard (read on for a full list).

  • Google could invest 9 figures into Character AI’s next round.

  • OpenAI is dangling millions to lure top AI researchers to their team.

GPTs have huge potential but are still in infancy.

The only three-letter word being preached to more than “God” right now is “GPTs”.

If you missed our pt.1 and pt.2 on GPTs, here’s the lowdown: anyone can create a custom ChatGPT with added prompts and/or context, like your go-to recipes.

Gone are the days of Ctrl+C for great prompts...now it’s all about tapping into a GPT pre-loaded with your chosen prompt.

but wait, wasn’t that already possible?!

Yeah, but the cool part about GPTs is that anyone can create one (no code required) and use it right inside ChatGPT.

Most GPTs today are essentially just prompts with names—ChatGPT that always uses a given prompt (like this storyteller). So not exactly curing world hunger…

But over the coming months, we’ll see GPTs trained on specific knowledge for specific use cases (here’s a how-to for building GPTs). For instance, lawyers will use a GPT trained to draft contract clauses according to specific legal standards, aka robots doing robot sh*t.

BTW, here are a few GPTs worth checking out today:

  • ConvertAnything—convert images, audio, videos, PDFs, files, & more.

  • editGPT—edit any writing (like Grammarly inside ChatGPT).

  • Grimoire—a coding assistant that helps you build anything!

And here’s a GPT that finds you the best GPT to use out of 15,000 GPTs!

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This is how often leading AI models make stuff up:

As you can see, not all AI models are created equal.

Models like GPT-4 and GPT-3.5 are far less likely to hallucinate (i.e. lie) than other models like Google’s Palm, which powers Bard.

This list, while not an end-all-be-all, is a handy guide for companies deciding which Large Language Models (LLMs) to use for business applications.

We’ve heard whispers that hallucinations are nearly a thing of the past at top AI startups, but here are some savvy tricks to ensure AI doesn’t slip you false info:

  • Put into custom instructions/prompts: do not respond if you are unsure of the answer.

  • Ask yes/no questions when possible to limit responses.

  • Instruct your AI to reference sources when necessary.

  • Direct your AI to ask follow-up questions if it does not understand a task.

Around the Horn.

  • Google might invest 9 figures into Character AI.

  • Nvidia unveiled its flagship GPU for powering AI applications, H100.

  • OpenAI is offering some top AI researchers millions of dollars to join their company.

  • r/ChatGPT: Plus users, what do you use ChatGPT for that makes it worth the 20$?

  • Check out these free breakout sessions from OpenAI DevDay.

This Should (Probably) Exist.

Every pet owner is familiar with that twinge of guilt when leaving their furry friend at home while out and about.

This got us thinking…

Imagine an AI pin like Humane for dogs, recording their daily activities and creating a highlight reel for owners to enjoy later.

The results would inevitably be a lot of sleeping and staring at birds, but ideally, the AI would spotlight the fun moments, like that sneaky bacon heist (we’ve all been there).

Tuesday Ticker.

Here are the results from last week’s poll:

Eager to hear your thoughts on the impact of GPTs on prompt engineering!

If the best prompts simply become GPTs, is prompt engineering still a worthwhile skill to learn? Why or why not?

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A Cat's Commentary.

That’s all for today, for more AI treats, check out our website.

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