So they’ve failed at pushing full return to office and now they’re commissioning unscientific studies to try to make hybrid seem necessary?

These results really can’t be applied to all jobs. Some jobs obviously require in-person but many white collar jobs can be done entirely remotely saving workers time, money and freeing up infrastructure for those that need/want to go in. Not to mention other benefits to mental health and reduction of emissions involved in commuting.

Oh yeah agree, he has the reverse Midas touch at the mo. Might add it coincided with the media flipping sides when they saw it was a foregone conclusion.

One of the admittedly minor things I dislike about his tetchy interview answers is when he starts going “blah blah blah…that’s why we’ve done things such as…” and then proceeds to list the one and only example of said thing.

Nowadays?!

I have somewhat of a pet extension to projection theory… Many people who are anti-gay think that it is a choice as they themselves have made that choice. ie. They are repressed bisexual/gay.

Completely unsubstantiated with no evidence but I find it fun to think about as it would explain their complete misunderstanding of it not being a choice. “I made the tough choice and am living with it, why can’t they?!”

We are just recovering from a similar situation here but the Overton window has shifted so far the supposed left-wing workers’ party now look like centre-right conservatives.

Right on cue, the descent into fascism begins ahead of the impending climate disasters.

It’s so depressing to see France like this, I always held it up as a prominent antifa nation.

Cavity protection ain’t gonna cut it where they’re going.

🇺🇸 “Baadel a waader” 🇺🇸

✅ Math is hard

❌ This math is hard

“I am educated and this is my guess.”

So if all world leaders collectively agreed to put aside their differences, ditch capitalism and mobilise their entire populations to actively work to reduce emissions tomorrow we might stand a slim chance of preventing the worst case scenario…

Yep my sentiment entirely.

I had actually written a couple more paragraphs using weather models as an analogy akin to your quartz crystal example but deleted them to shorten my wall of text…

We have built up models which can predict what might happen to particular weather patterns over the next few days to a fair degree of accuracy. However, to get a 100% conclusive model we’d have to have information about every molecule in the atmosphere, which is just not practical when we have a good enough models to have an idea what is going on.

The same is true for any system of sufficient complexity.

Oh yeah no regrets, was bound to happen eventually and still a decent month for me with the Boltgun and NMH additions.

Seems after years of avoiding buying games that end up on Game Pass it was finally my turn to appease the Game Pass gods. Bought Control Ultimate over the holidays and am yet to play.

This article, along with others covering the topic, seem to foster an air of mystery about machine learning which I find quite offputting.

Known as generalization, this is one of the most fundamental ideas in machine learning—and its greatest puzzle. Models learn to do a task—spot faces, translate sentences, avoid pedestrians—by training with a specific set of examples. Yet they can generalize, learning to do that task with examples they have not seen before.

Sounds a lot like Category Theory to me which is all about abstracting rules as far as possible to form associations between concepts. This would explain other phenomena discussed in the article.

Like, why can they learn language? I think this is very mysterious.

Potentially because language structures can be encoded as categories. Any possible concept including the whole of mathematics can be encoded as relationships between objects in Category Theory. For more info see this excellent video.

He thinks there could be a hidden mathematical pattern in language that large language models somehow come to exploit: “Pure speculation but why not?”

Sound familiar?

models could seemingly fail to learn a task and then all of a sudden just get it, as if a lightbulb had switched on.

Maybe there is a threshold probability of a positied association being correct and after enough iterations, the model flipped it to “true”.

I’d prefer articles to discuss the underlying workings, even if speculative like the above, rather than perpetuating the “It’s magic, no one knows.” narrative. Too many people (especially here on Lemmy it has to be said) pick that up and run with it rather than thinking critically about the topic and formulating their own hypotheses.

And again…

You’ve just copied my arguments yet again.

Seek help, your projections are concerning.

You don’t really have one lol. You’ve read too many pop-sci articles from AI proponents and haven’t understood any of the underlying tech.

All your retorts boil down to copying my arguments because you seem to be incapable of original thought. Therefore it’s not surprising you believe neural networks are approaching sentience and consider imitation to be the same as intelligence.

You seem to think there’s something mystical about neural networks but there is not, just layers of complexity that are difficult for humans to unpick.

You argue like a religious zealot or Trump supporter because at this point it seems you don’t understand basic logic or how the scientific method works.

Nonsense opinion proves unpopular.