also in my experience, while a lot of Germans are happy to chat with you in English in a social setting, business talk is usually expected to be held in German

“people” buying ads? In 2035? What a delightfully vintage concept!

Fun fact: Nadella has been replaced with an AI agent a couple of months ago and nobody has noticed yet. “Copilot, while I’m away, generate bs on AI adoption and fire a bunch of employees, ok?”

which one ?

prompt engineering does require skills. It’s just that, rightly or not, they are now seen by companies as foundational skills for a lot of jobs and worth investing in training for most employees (rather than hiring a team of prompt specialists).

Like if you work in certain roles you need to have good knowledge of spreadsheet software, you don’t go to your company’s “Excel guru”.

“it drove right through my kitchen wall. And I hadn’t even ordered one!”

Would you say you are good at creating a meal plan or a work schedule by yourself, with no AI? I suspect if you know what a good meal plan looks to you and you are able to visualize the end result you want, then genAI can speed up the process for you.

I am not good at creative tasks. My attempts to use genAI to create an image for a PowerPoint were not great. I am wondering if the two things are related and I’m not getting good results because I don’t have a clear mental picture of what the end result should be so my descriptions of it are bad

In my case, I wanted an office worker who was juggling a specific set of objects that were related to my deck. After a couple of attempts at refining my prompt, Dall-E produced a good result, except that it had decided that the office worker had to have a clown face, with the make-up and the red nose.

From there it went downhill. I tried “yes, like this, but remove the clown makeup” or “please lose the clown face” or “for the love of Cthulhu, I beg you, no more clowns” but nothing worked.

I am not using it for this purpose, but churning out large amounts of text that doesn’t need to be accurate is proving to be a good fit for:

• scammers, who can now write more personalize emails and also have conversations

• personality tests

• horoscopes or predictions (there are several examples even on serious outlets of “AI predicts how the world will end” or similar)

Due to how good LLMs are at predicting an expected pattern of response, they are a spectacularly bad idea (but are obviously used anyway) for:

• substitute for therapy

• virtual friends/girlfriend/boyfriend

The reason they are such a bad idea for these use cases is that fragile people with self-destructive patterns do NOT need those patterns to be predicted and validated by a LMM.

Yes, it’s like the rubberducking technique, with a rubber duck that actually responds.

Sometimes even just trying to articulate a question is a good first step for finding the solution. A LLM can help with this process.

Meeting notes are the ideal use case for AI, in the sense that everyone thinks someone needs to write them but almost nobody ever goes back and actually reads them.

But when I got curious and read the AI generated ones (the ones from Zoom at least)… According to the AI I had agreed on an action that hadn’t been even discussed in the meeting and we apparently spent half of the meeting discussing weather conditions in the various locations (AI seems to have a hard time telling the difference between initial greetings or jokes and the actual discussion, but in this one it became weirdly fixated with those initial 5 minutes)

I like it a lot but I need two physical SIM slots so it doesn’t work for me, unfortunately. But great idea and love the price drop

Thanks, I understand better now.

On a related note, I wish I had known of the “just because I said it and I did it, doesn’t mean I succeeded” line of defense when I was a kid

Meta argued that “the FTC’s case rests almost entirely on emails (many more than a decade old) allegedly expressing competitive concerns” but suggested that this is only “intent” evidence, “without any evidence of anticompetitive effects.”

Not sure I understand the argument. if I write that I’m going to buy another company instead of competing with them, then I go ahead and I do buy that exact company, are they arguing that the two things are not necessarily related?

That’s true but at least one of these things needs to happen:

1. the forklift costs billions and consumes tons of energy, but it can lift a whole mountain, which no group of humans can do

2. the forklift helps a team of 10 do the work of 50 and, while still relatively expensive, it costs less than the 40 people it’s replacing

3. the forklift becomes an inexpensive commodity and it augments human capabilities and creates new possibilities for society as a whole

This is roughly what happened with mainframes to personal computers to mobile devices. LLMs are stuck between 1 and 2, they are not good enough forklifts to lift a mountain and not cheap enough to replace 40 people and save money. There are some hints that they could at one point move to 3 but the large players that could make it happen are starting to be scared by the amount of investment to get there.

On a related note, lot of people are being fooled by this hype machine mixing GenAI with good “old” machine learning and you now read about all these “AI wins” like “student discovers new galaxies with AI” or “scientist discover new medicines with AI” that make it sound like these people just asked ChatGPT “how would you go about discovering a new galaxy?” or “could you make up a new drug for me pretty please?”.

yes, but with at least $100M of additional VC funding

“organic AI”

yes, there are clearly unfair trade practices here. EU has been making money for Google and Amazon, but the US are not using our services. I hear the best solution to this are tariffs: EU users have to pay to use gmail until enough US users start using EU email providers and we rebalance the services trade!

You make a great point. But just to stay on the example of cars: besides the innovation on EVs, there’s this horrible tendency to consider cars as tablets on wheels, both in the sense that you can forget about repairing them by yourself and in the sense that they are now increasingly becoming low-margin hardware to run higher margin subscription services. If anything warrants high valuation for a car company it would arguably be the innovation on EVs, rather than the SaaS model.

I hope the idea of Car Software As a Service dies before becoming too widespread. But if it doesn’t, maybe car companies wouldn’t become “Tech” companies, just more shitty subscription vendors. And their stock should be valued as such, not for the largely unwanted “Tech innovation”.

By that measure shouldn’t Disney be considered a Tech company too? Or I guess banks and insurance companies.

I hadn’t thought of it that way, but maybe the article (at least the small part I can read with no paywall) is on to something, Companies that sell access to technology or rely on technology to sell something else (he does give the example of e-commerce) should not be “Tech” companies.

The part I didn’t get to is where the author draws the line to tell what companies ARE Tech. I guess OpenAI or Google would qualify. They sell services but they are services they invented and made, with considerable researxh and investment. But what about Amazon or Netflix?

Agree. The MO is totally different: funding for bis research would be cut, he would be fired and then deported very publically.