I worked in adtech. It's often true.

Yeah, he made enough public statements that you could include a lot of coverage just by quoting public statements. US government reports generally have no copyright, you can use them in your own work however you want.

Absolutely. Don't take my word for it, here's a detailed NASA press release about some of the changes they were making as a result. The review board went far beyond just looking at the launch process. They took a comprehensive review of the entire program, and most of their suggestions had nothing to do with not launching in cold temperatures.

>combining these technologies is a no brainer

Agreed. I look at the GPT family of models as infrastructure. The real potential comes from layering specific applications on top of it. Imagine every random high school baseball game got a writeup on the local news website. You'd need to ingest sports data and do other pipeline work, but the result could be profitable.

It'll be something entirely new, but not capable of doing everything that my toddler can do. Systems will be designed to avoid those weaknesses. Again, think about replacing meter readers with cheap sensors instead of expensive robots.

I'm talking about where the funding is going. Anything remotely approaching AGI would require billions and billions of dollars of funding.

>I don't think the edge cases matter

Being able to handle those weird edge cases is what distinguishes AGI from the kinds of AI that companies are currently developing...

I think "AGI" is a silly concept overall and never really happening. Computers are good at doing things in different ways from humans. Rather than chasing AGI, you can make a lot more of an impact by leveraging a computer's strengths and avoiding its weaknesses.

For my example, I picked an occupation with an average salary south of $30,000/year (source). I'm not saying everybody can do it, but the market puts a price on this kind of labor that suggests many people can do it. A true AGI system could replicate how a low-salary human does a job. In reality, a computerized system would use a few wireless sensors that call home instead of physically driving around looking at fields.

Similarly, consider meter readers, another low-wage job. Imagine what it would take to create a robot that could drive from house to house, get out of the car, find the power meter, gently move anything blocking it, and take a reading. Instead, utilities use smart meters that call home. It's cheaper, more reliable, and simpler.

It's beyond hard to create a true AGI system, and there are plenty of ways to make tons of money with application-specific systems.

A true AGI has way too many edge cases to be possible in the timeframe you describe. It's also not necessary to create AGI in order to make a lot of money from AI. You can find the specific jobs that you want to replace and create a task-specific AI to do it.

Artists are hardly obsolete. Photoshop didn't make them obsolete and generative AI won't either. And I say that as someone who has extensively used Stable Diffusion for work and personal projects.

Regarding valets, I'm referring to the ability to toss your keys to a robot and have it drive your car. Even when true self driving cars are first produced (which always seems to be ten years away), we'll be a long way away from a robot being able to park a non-automated car. That's just one example of a task that seems really easy for humans but is shockingly hard for robots. Folding laundry is another one, which is especially relevant since I'm ignoring the fact that my dryer just finished a load.

Check out this comment. Some things that we take for granted from low-wage humans are incredibly hard for computers and robots. Think about valet parking. Our society doesn't think "Oh my goodness, valet parkers are geniuses!!!" But it's really really hard to build a robot that can do what they do.

There are some things that are incredibly hard. Imagine you work on a farm. You toss the keys to the ATV to a 17yo farmhand who's never worked for you before. You say, "Head over to field 3 and tell me if it's dry enough to plow. You can see where it is on this paper map. Radio back using this handheld." The farmhand duly drives the ATV to field 3, sees that it's muddy, picks up the radio, and says, "Sorry boss, field 3's a no-go."

We're a long way from a robotic farmhand being able to perform those skills, certainly not for a price comparable to a farm laborer.

You could definitely train an application-specific AI to monitor fields and report on their moisture levels. You could even have an algorithm that schedules all of your farm equipment based on current conditions and other factors. So it's not that AI can't revolutionize how we work, it's just that it'll be different from true AGI.

I don't think AGI will ever happen, but with enough task-specific applications, the difference may become academic.

What made you decide to run an on-prem server instead of going to the cloud? I'm a data science manager and I'm currently looking at our options. I like self-hosting for most things, but I'm up in the air about training deep learning models.

The real question is how people can invest who would otherwise keep extra cash in their savings account. An index fund exacerbates some bad behaviors, but it preserves value better than keeping cash, which is how most people are taught to save when they start working.

That was an interesting article. From a corporate governance perspective, it's very bad. I look at things like Apple's multi-billion dollar headquarters and wonder why they didn't shave a billion off the cost and issue a dividend instead.

For typical people with a few grand in the bank, using a broker and an index fund remains good advice. Especially when you can get a tax benefit (401k, HSA, 529, etc).

The problem with any investing strategy is that... you have to make an investing strategy. Keeping your cash under the mattress is as much a strategy as dumping it all into cryptocurrency. The nice thing about an index fund is that there are a bunch of methods that are tax preferred, so you can come out ahead of the mattress strategy even if the market stays flat.

Yes. If you're looking for a high-risk place to make a bet, you could do worse than a penny stock.

My answer was "massive returns." Not sure how that's dishonest. I also linked to a chart quantifying what "massive returns" meant for 5-year holding at various points in time.

Sometimes I get letters in the mail saying there's an upcoming shareholder vote. They tell me which way management wants me to vote. Sometimes I log on to vote and sometimes I don't. There are plenty of small-dollar investors who will ignore all of those letters if they hold stock in their own name, which means there's no practical difference for them to own stock outright. Telling people "Don't spend beyond your means and put the excess money in a tax-preferred index fund" is still generally good advice.

If you had gotten in right at the beginning, you could have made massive returns. I recently modeled the 5-year returns based on sale date. The days of getting filthy rich from buying $100 of Bitcoin are long past. If Bitcoin soared to $100,000 by the end of next year, you'd have roughly a 100% return over three years. There are plenty of penny stocks that offer a similar risk/reward profile.

If you DCA every paycheck for a 40-year career, you're likely to see better returns than any other passive strategy.

Five years ago, Bitcoin's price was $15,145. Right now it's $16,849. That's an 11% increase. In the same timeframe, the S&P 500 has increased 41%.

EDIT: If you include inflation and S&P dividend reinvestment, Bitcoin looks even worse.

Bitcoin gave up almost all of its five year gains. It's astonishing how quickly it fell. I wonder how much of the 2021 price runup was driven by wash trading and other shady activities that couldn't be kept up when some of the major traders failed.

You'd have to drop Bitcoin, but I think it would make stocks look better, USD worse, bonds meh, and real estate all over the place.