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With respect to marketing hype, it's comparable to the now-reduced scale of hype for quantum computing, which has mostly vanished from the headlines compared to a year or two ago.

https://www.technologyreview.com/2022/03/28/1048355/quantum-...

The main difference is that LLMs have a lot of immediately valuable use cases in their current iteration, which has lead to widespread adoption. The hype cycle may have reached its peak and will now start to relax a bit.

> I think the author is far too pessimistic about the capabilities of ML.

Why do you have to be pessimistic or optimistic? How about measuring? Most of us are engineers of some kind here. We don't need to believe or disbelieve.

Being pessimistic or optimistic doesn't preclude measuring things. Many people are pessimistic about climate change precisely because we're measuring the amount of CO2 being released and because we're measuring changes in temperature, weather, etc. over time.

Same with believing and disbelieving - sure, some people believe in religious-type stuff that has an absence of evidence, but there are lots of other things to believe or disbelieve based on evidence. I believe that Covid vaccines help to prevent serious illness precisely because there is a tremendous amount of evidence to that end.

> some people believe in religious-type stuff that has an absence of evidence

That's what I see with LLMs. Religious fervor.

No one can measure the future.

We all measure the future past.

The practical applications of AI is undoubtedly overblown, but I do agree that it's ability to generate content is impressive and will (or rather, already is) being used for practical things.

> I think the author is far too pessimistic about the capabilities of ML. I think we're already beyond the "it might not live up to the hype" stage and well into - "holy moley this is actually really well (for certain things) already - now let's figure out how to use and iterate upon it" stage.

I think we are rather in the "oh wow there is a slight possibility that chatbots are not a waste of cpu cycles with this" stage.

The first 80% of AI tasks will be easy enough. The next 20% will be increasingly difficult with the last 1% virtually impossible. Same with driverless cars.

Folks who are pessimistic on driverless cars appear to move the goals on the last 1% repeatedly. Self driving cars are driving themselves around Phoenix and SF right at this minute.

They are indeed driving around SF this very minute causing unique disruptions, roughly two per day last year:

https://www.sfmta.com/sites/default/files/reports-and-docume...

https://www.sfchronicle.com/projects/2023/self-driving-cars/

https://www.sfchronicle.com/bayarea/article/san-francisco-wa...

I love when people share this stat not realizing they’re proving these vehicles are already better drivers than humans. A human disrupts traffic on the road in front of my home every 10 minutes

That's just a local bias. I used to live where a street turned from two-way to one-way, and people drove the wrong way all the time.

But that doesn't change the fact that human beings are extremely safe drivers. NHTSA reports less than 2 deaths per 100 million miles driven each year from 2010 to 2020: https://cdan.nhtsa.gov/tsftables/National%20Statistics.pdf

Safe compared to Waymo?

Feel free to check my math, but Waymo's 2 accidents in 1,000,000 driverless miles (https://blog.waymo.com/2023/02/first-million-rider-only-mile...) is higher than the rate for human drivers in any of the years from my quick NHTSA stats search.

They've had no fatalities, which is great (and certainly better than other "self-driving" car options)! But it's hard to make really good comparisons as long as Waymo is off by a factor of millions of miles.

Driverless cars aren't the solution to a lot of the problems their companies market them for. Work and shop local. Build public infrastructure.

Mo cars - Way Mo problems.

They should take away their driver's license!

Guess how many disruptions humans are causing per day in SF

Without knowing the VMT of driverless vehicles it's impossible to compare their safety to drivered vehicles.

The last 1% is actual self driving. Not "allowed to control the vehicle as long as human supervisor is glued to steering wheel with eyes on road". Or "closely monitored test conditions". We're about 7 years later than Tesla predicted on this already, and not all that much closer even without moving the goalpost an inch.

In SF and Phoenix, Waymo has cars driving around with no drivers.

It's here. Tesla (and maybe Cruise) may well be sucking at it, but Waymo isn't.

I passed a driverless car from Cruise in San Francisco on my commute just the other day.

Call me when they have them driving around Syracuse, NY. In winter.

If that's the bar, half of the humans in CA, TX and FL can't drive.

sigh

This argument again. It's so incredibly obvious that it does not apply, but so many people seem to think "oho, but some humans can't do <thing no AI can do>! That means you think those humans aren't intelligent either!" is such a gotcha.

Just about any human can be taught to drive in the snow. The capability is there; the skill just hasn't been developed. Take a Californian to Upstate NY, force them to commute 40 minutes to work for several winters, and they will learn (or they'll die, I guess).

Take a self-driving car from LA to Syracuse and force it to drive in snow for years, and all it will do is crash or refuse to try. We do not yet (to the best of my knowledge) know if it will be possible to teach self-driving cars to drive in snow. It seems likely, but it hasn't yet been achieved, and in a field like this, "haven't achieved it yet, despite trying" and "don't know if it can be done" are very close together.