I just got an invite to try Google's Bard, a ChatGPT competitor.  So, I put ChatGPT GPT-4 and Google's Bard to the test with the same prompts, and see who wins this challenge.



GPT-4 vs Google's Bard - Who wins in a showdown? (Ep. 725)

Hi, I’m Dave Lee and welcome to my investing channel.  I share my journey, lessons and thoughts on investing and personal finance to help people grow their resources and use those resources on what’s good and true.

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I’m joined by James Douma as we discuss Tesla’s latest FSD v12 (supervised) release and how ti compares to previous FSD versions.  We also dive into Robotaxi, Optimus, LLMs, and more.

James Douma on Twitter, https://twitter.com/jamesdouma
James Douma on AI playlist, https://www.youtube.com/playlist?list=PLfibpgBinf9R7KIedEU3y-YjrA63LSKHX

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FSD v12: Tesla's Autonomous Driving Game-Changer w/ James Douma (Ep. 757)

I take to the streets of central/downtown Austin and show some amazing moments where Tesla's FSD Beta v12.3 demonstrating high driving intelligence but also show some moments of hesitation and mistake.

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Tesla FSD v12.3 - Hits and Misses (Ep. 756)

This morning, I received Tesla's FSD v12.3 software update in my car, and here’s my first impressions.

1. Overall, I’m super impressed.  Ride quality is much more human-like than v11 with acceleration, braking and turning all much improved.
2. Smart decisions - overall, v12.3 made better and smarter decisions in challenging situations than v11.  Several places where I know v11 would have difficulty, v12.3 handled with ease.
3. v12.3 handled speed bumps perfectly.
4. Many of my rides today were flawless and exactly how a human would drive.  v11 has a rigidity that is gone with v12.3.

Overall, I’m quite blown away by v12.3.  I was expecting a version that was comparable to v11 - better in some ways and worse in other ways.  But what I’ve experienced (so far) is a system that feels much more confident and capable than v11.  v12.3 is far from perfect and there’s still a lot of work ahead for Tesla’s FSD team but the end-to-end neural net approach looks like it’s clearly the right approach.

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Tesla FSD v12.3 - First Impressions!  (Ep. 755)

I discuss thoughts from Tesla’s Q4 2023 earnings report, shareholder letter, and Elon Musk’s comments to investors.

Tesla Q4 2023 shareholder letter: https://digitalassets.tesla.com/tesla-contents/image/upload/IR/TSLA-Q4-2023-Update.pdf

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Tesla Q4 Earnings - Key Takeaways (Ep. 754)

I discuss why Tesla had to do a complete rewrite of FSD and more importantly, why it should allow them to improve faster and potentially solve autonomous driving.

Narrow Driving Intelligence (NDI) is an approach to autonomous driving where each unique driving challenge, or edge case, is solved individually with a specific solution or algorithm. However, this approach does not improve the vehicle's ability to handle new, unseen edge cases. 

On the other hand, General Driving Intelligence (GDI) aims to develop a holistic driving intelligence that can handle a variety of situations and new edge cases, much like a human driver would. It involves creating a massive neural network that learns from millions of videos of various driving situations, enabling it to intelligently navigate through situations and edge cases it's never seen before.

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GPT-4 vs Google's Bard - Who wins in a showdown? (Ep. 725)

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