While it is a strange metric, the milestone is important for many less-good reasons. It basically means that more storage is going to keep being needed.

The thing is that the current systems do offer some huge opportunities today, and systems in the near future will be able to address specific tasks in a meaningful manner. Of course the challenge is you need a lot of unique training data to make them work.

There are a number of parametric optimization challenges that these tools could be used to address... if you know how to use the ML tools. (Not talking about GPT systems). I can think of a couple things with about 200 to 1,000 parameters to optimize that I would love to have a go at... but way too much work.

...have you thought about running for office?

They want to reduce risk in general. An unkept yard doesn't make grounds for denial of claim, but it increases chances of one... at least in theory.

I am sure things like unpermitted solar falls in there as well.

Isn't that the difference between AI and AGI? Training for a specific task is a finite effort; chaining tasks together also breaks down task identification and processing. To me at least though general inteligence is about using a complete body of knowledge to process and act on information.

Today I have trouble seeing how there is enough quality training data and processing power to make two orders of magnitude improvement towards aGi. My perception is that AI solutions can not economically learn (train) while doing in the context of a large data set. Until that changes I think we will be a long way off.

The thing that gets me with "code is law" is that it is essentially the same as "they just gave me the money at the bank because I asked for it. How was I supposed to know they felt threatened by my finger in my pocket and saying don't push the silent alarm?"

There are ~60,000 "unsold" inventory intended for sale. The rest are cars that are inventory that are part of doing business. Vehicles used for demo rides with over certain mileage cannot be sold as "new" so they never hit P&D reports. Likewise vehicles that are company-owned for purposes other than R&D are not sold. While the number is scary still, it is still lower inventory than legacy manufacturers have via their dealer network.

Retail buyers in the SPAC.

You have mostly retail investors involved. If the cash invested in DJT was meaningful to them then they are likely to sell if it is pushed low enough. If it is $200 x 1 million people then they are unlikely to sell ever. If the SEC starts an investigation then things get interesting.

Not worth putting money at risk on either side of the bet.

No, this whole scam only took about $200 million to pull off. It is really just the 5 million shares that anybody paid actual money for. ...Which is why it is really stupid to try to play this stock on either end. It only takes $200 million to prop up the value of the stock (until the lock-up period ends in 6 months and the shares are all free for sale). So, for $200 million or so you either tank the stock or maintain its value. If you have two parties on either side of the equation with that money then it becomes a matter of who blinks first. ...But, come 10/15/2024 I doubt the stock will be worth anything.

I hope they are doing a lot more statistics coursework. Using generative AI for some things makes sense but knowing when it puts you at risk is what is really important.

Will be fun to watch what happens to them in 5 years as far as who is out of a job first.

Aviation it can be helpful for takeoff thrust, but non-essential for construction. There are plenty of examples of real-world all-electric construction equipment and the huge benefits it can offer. Hybrid electric/hydraulic is also out there for things that use legacy attachments.

Let me guess... you had ChatGPT do that math for you.

My thinking too. Someone wicked smart, humble, and focused... that can communicate. Shame he got pushed out in the first place.