1000+ new AI tools in 2 months: What did we learn?

Welcome to another edition of what we’re determined to make the best damn newsletter in AI. Here we’ll break down AI topics that matter, open your mind to use cases, and keep you ahead of the curve.

Our #1 goal is to be useful. So please shoot us an email 📩 if you have questions or feedback, and especially if you implement something we share!

Here's what we're covering today:

• What we can learn from the 1,000+ new AI tools in the past 2 months

• A list of exciting use cases for current AI voice cloning tech

• Stay up to date on the Bing + ChatGPT saga

Let’s get to it! 👇

TODAY'S PERSPECTIVE

Boiling down the ocean of AI products into three common AI UX patterns

We’ve heard these questions from you:

• “What types of things should I be looking for AI products to help me with?”

• “What types of AI features should I look at building into my product?”

In this email, we’ll give you a framework for how to think about it.

⚠️ warning - this is a bit nerdy, but it’s been a major question across the board so we’re going to try out best to answer. hit reply & email us if you have follow-up questions. ⚠️

In short, the type of AI product you build or use…

• Depends if you’re enabling an expert

• Or - if you’re building for a beginner

• And - how much flexibility you’re able to bring into the process while still being helpful

Good news for us? There is an abundance of AI tools and products to study.

From our data sources, 1000+ new AI tools have launched in the past 2 months. We are clearly in the exploratory phase of this technology. And there’s a lot to learn from observing what is being launched.

Introducing 3 main UX (User Experience) patterns for AI tools

1. Copilots

2. Workflows

3. Chatbots

Copilots

• Purpose: Assist users in completing tasks faster, typically by predicting how the task will be completed and suggesting.

• Value prop: Get a task done faster.

• Example products: Github Copilot is one of the best examples here, which helps developers write code faster by offering an autocomplete-style interface. Lex.page is a similar product for writers. What you’ll notice in these tools is that they enable people who are already experts and good at a job, to get that job done faster.

Workflows

• Purpose: More rigid than copilots, and the product takes the lead rather than the user.

• Value prop: Get a task done that you might not have been able to do yourself otherwise.

• Example products: Jasper and other AI copywriting tools, particularly that do long form content like Moonbeam are good examples here. AI video editing tools like Runway ML are excellent examples of helping people become video editors even if they had no prior skills. Coda and Notion appear to be going in this same direction, but it’s still early for those products.

Chatbots

• Purpose: Serve as a flexible interface on top of information, or soon - tasks to be done.

• Value prop: Even less friction to get the information you need, or the task done.

• Example products: ChatGPT is an obvious example, especially when integrated into search like Bing or Perplexity.ai. There’s also an explosion of products that help with question and answering over your own datasets like Kili.so for support and Paper QA over PDFs. I expect we’ll see the same explosion for AI for actions in the near future.

Ok wait a second - so, should everything be a Chatbot?

It’s quite possible we’re moving towards a world where more and more things can be done via a chat-style interface. However, there are some major drawbacks in chat products that make copilots and workflow tools more feasible in the near term:

1. Chatbots are super flexible, sometimes too much so

2. Chatbots are heavily reliant on the quality of the “chat” or prompt, meaning it can be harder to get an awesome result out of them

Give me the takeaway

1. If you’re building an AI product or feature - be clear about who you are serving and what level of experience you’re ready to deliver to them. That can guide which UX pattern makes sense to explore.

2. If you’re looking for tools - ask yourself what you’re expecting and look for tools that match the associated UX pattern.

USE CASE DEEP DIVE

Voice cloning tech is already crazy good 🤯

Today’s use case is going to pretty broad - cloning your voice.

What does that mean?

With tools like Eleven Labs and Resemble.Ai all you need to do is upload a file of you speaking, then input a new “script” for your voice to read, and voila - you’ve got your own voice clone.

We’ve been testing it over the past week and already found the following use cases:

• Creating voiceovers for video tutorials

• Creating an audio version of blog posts, which could be turned into a podcast

• Sharing personalized messages with customers

• Improving employee training and onboarding with audio versions, especially to add a little more excitement

• Having fun with voice cloning of celebrities or friends (ethical use advised)

• Once they get good enough - creating voiceovers for social media content (!!)

Reply to this email and tell us how you'd use voice cloning!

LINKS

For your reading list 📚

ChatGPT is coming back into the spotlight...

• Open AI published the guidelines they use to control what ChatGPT will and will not talk about - and Rachel posted a recap video on TikTok of the biggest takeaways

• And Bing added more control to their new ChatGPT-powered search system by limiting the number of replies to 5, aiming to prevent Bing from going “off the rails”

And if you're really nerdy...

• If you're looking for a quick and simple way to perform Q&A over a PDF, definitely check out this tool on Hugging Face

• Runway ML’s AI film festival results are debuting over the coming weeks. This will give us a peek into how good this tech is getting for creatives who are investing time in it.

That's all!

We'll see you again on Thursday. Thoughts, feedback and questions are much appreciated - respond here or shoot us a note at [email protected].

Cheers,

🪄 The AI Exchange Team