But despite the hype (and… oh boy!), not in a good way. So-called artificial intelligence – no relation to intelligence, but the word just seems so suggestive – is actually just machine learning. And who teaches the machine to learn how they learn what they learn? Humans. Thus, AI/ml also includes all the joys of human foibles.
Oh, and not just the racism + sexism. Also, the burning:
For example, recommendation and advertising algorithms are often used in advertising, which in turn drives people to buy more things, which causes more carbon dioxide emissions. It’s also important to understand how AI models are used, Kaack says. A lot of companies, such as Google and Meta, use AI models to do things like classify user comments or recommend content. These actions use very little power but can happen a billion times a day. That adds up.
It’s estimated that the global tech sector accounts for 1.8% to 3.9% of global greenhouse-gas emissions. Although only a fraction of those emissions are caused by AI and machine learning, AI’s carbon footprint is still very high for a single field within tech.
With a better understanding of just how much energy AI systems consume, companies and developers can make choices about the trade-offs they are willing to make between pollution and costs, Luccioni says.
I know – that’s your shocked face. But move fast because it’s important to keep up with the language as it changes and the conditions do not, or are made worse. Because the investment society that cultures large language models and the like already feels three steps ahead, because they never under-invest in PR. Relying on ‘companies and developers to make the right choices about trade-offs’ is only in any way reliable to the extent we change the end of that statement above about what they are ‘willing’ to do. Otherwise, we’re only and ever at the mercy of the companies and developers, no matter whether they blame it on some disembodied algorithm, call it machine learning or whatever.
It’s definitely artificial something.
Image via reset.org
While often associated with envy, green is also the color of certain kinds of motion sickness. But the opposite of envy is, I guess, pity? A kind of misery? All of these are summed up in the new survey of crappiest towns of Britain, of which London is newly reigning, um, queen?
London was catapulted to victory by multiple nominations for its dismal suburbs, murder miles, high house prices, City bankers and a transport system that abandons late-night revellers to the mercy of rickshaws, minicabs or night buses, “a must for all fans of vomit, paranoid schizophrenics and R&B played through tinny mobile-phone speakers”.
The city’s trump card was undoubtedly its most affluent parish, Mayfair: “Its inhabitants are virtually without exception the biggest shower of needy, self-important bumwipes in London, with a self-pity complex and misplaced sense of entitlement to match. The architecture is either dull west London stucco or a twattish approach at some kind of meaningful landmark building. Either way it’s rubbish. Most importantly the pubs are shit. And full of people who live in Mayfair.”
Who are we to argue? Don’t miss the slideshow that accompanies the article – England at its remarkably dreadfulest. Maybe it’s a sly campaign to get people not to go there. A lot to work with either way.
In another dimension:
For decades, three hours has been seen as the magic number, the journey time at which train travel becomes faster than flying on a centre-to-centre basis. But with stricter and more time-consuming airport security, plus frequent air traffic delays, that magic three hours is stretching. So much so, that Guillaume Pepy, CEO of SNCF (French national railways) has stated that this three hours has become four or perhaps five.
He cites Paris-Perpignan, where SNCF’s high-speed TGV takes five hours, yet where rail has captured 50% of the market.
It’s not only journey time that’s important. European high-speed trains typically achieve punctuality of 90-95% on time or within 15 minutes, whereas European airlines struggle to reach 63-68%. And with WiFi and power sockets for laptops, a train journey is often more productive.
The point in the first graph is one that anyone who flies understands all too well: as flying becomes slower, rail becomes faster.
Aren’t you glad that, as opposed to worrying about things like high speed rail service between, say, Charlotte and Chicago, your government keeps dicking around with whether rich people deserve permanent tax cuts, or even more importantly, ways to keep Muslim community centers out of Manhattan? Manhattan?
Makes you wonder about what qualifies as a pre-existing condition. Ah, freedom.
As seen on Atrios.