Self-Driving Cars: The Final Lap

Navigating the road to full automation; Ask AI for feedback then incorporate it

Welcome to another edition of the best damn newsletter in AI.

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Here's what we're covering today:

  • A juicy update from the self-driving car industry and what we can learn as we think about the progression of AI in our work

  • A simple but powerful way to use ChatGPT to make you a better presenter

  • Regulatory capture, AI ethics and more…

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Let’s get to it! 👇


Navigating the Road to Full Automation: Lessons from the Self-Driving Car Industry

As a business owner or executive, you're probably wondering how AI can help you do more with less, or how it can give you a competitive edge. Or perhaps you're a product manager looking to leverage AI for career advancement. Whatever your situation, the self-driving car industry offers valuable insights.

The Big Players: Cruise, Tesla, and Waymo

These big names are all battling it out in the final stages of automation. If you look at the autonomous vehicle industry's 6 levels of automation, they're all trying to cross the distance between 4 and 5.

Waymo is making strides, rolling out in Ubers across Phoenix. It's a bold move that shows their confidence in their technology.

Cruise, on the other hand, has hit a roadblock. After an unfortunate incident where a Cruise vehicle ran over and dragged a pedestrian 20 feet, they've suspended all driverless operations to rebuild public trust. But there's a twist. Apparently, Cruise didn't provide all relevant footage to the DMV for their investigation.

What to learn from self-driving cars to sound smarter about AI:

1) Many companies will get close to full automation on problems, but the final 1-2% is what matters. And what’s not great - the race to full automation often causes companies to make bold moves to secure their place at the top.

2) Public trust is incredibly important for any AI project. Any missteps can lead to a loss of faith and a halt in operations. This is why we recommend you focus on internal applications of AI, over customer-facing solutions. The risk is significantly more when you involve end-users.

3) Transparency is key. Withholding information can lead to further complications and damage to reputation. And as the Executive Order came out this week, we are glad to see transparency as a top demand across more AI applications than just self-driving.

We'll continue to watch this space.


Ask AI for feedback, then incorporate it

Large language models are great for many things. One of the best - quickly acting as a feedback source.

Building a presentation and need feedback? But it’s late at night and everyone else is sleeping? **ahem, not like this was a real story

The general process of:

  1. Ask an LLM for criteria of what makes a good X (in our case, a presentation)

  2. Then, ask the LLM for a critique using that criteria

  3. Then, ask for the LLM to rewrite based on that feedback


You are a world class TED Talk Coach. You believe deeply in the power of a clear Story Arc. You are going to review the following presentation outline, analyze it, and articulate the Story Arc. Then you are going to suggest improvements.

# Presentation Outline


# Instructions

Review the presentation outline, analyze it, and articulate the Story Arc. Then, suggest 5 ways to make the Story Arc stronger.


For your reading list 📚

More on the self-driving car industry headlines...

On AI ethics and regulation…

And if you’re really nerdy…

  • Google's throwing a cool $2B into backing Anthropic - because if you can't build it… buy 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].

... and if someone forwarded this email to you, thank them 😉, and subscribe here!


🪄 The AI Exchange Team