Alternate title: Defence minister gaining too much influence.
The upper echelons of Chinese politics must be insane. It almost seems suicidal. On the one hand, you need to amass huge amounts of social capital to rise up the pyramid. On the other, you constantly risk flying too close to the sun.
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Just a bit more jaw definition
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Bitttt more
▶️
Fuck
Kunde gij da nog ‘s herhalen?
‘Small businesses’
One of the points the article makes is that people boost such content despite knowing it’s fake because it confirms what they’re ’feeling’. Want to feel outrage? Here’s an image that will let you and others feel that. Truth? Irrelevant.
In short: it’s the ‘facts don’t care about your feelings’ crowd doing what they do best: recasting reality as a jumble of vague feelings.
Oooooohh
Pastes 300k tokens worth of scp and creepy pasta lore into the prompt
“Sweet dreams, Timmy”
Just a few more years until we’ve fully migrated to SAP’s WiFu system
Vivaldi is chrom_ium_. Been trying out the last month on macOS. Great browser, although it’s funny how for some settings you get taken to a different page that looks 100% like Chrome except with Vivaldi branding.
Vivaldi on iOS doesn’t feel as great though – less ‘native’. Certain gestures and animations just don’t quite fit.
Shoutout to Webkit-based Orion for both platforms. Slowly gravitating to that
I agree with you. I just wanted to share some nuance. The point I wanted to make is that it is in fact possible to incorporate LLMs in a fairly controlled way while calculating (estimates of) the risk of failure as well as the associated social and financial costs. I do it every day, but I’m no tech bro and dislike the ‘AI will fix everything’ types as much as everyone here.
Just fyi, that’s not entirely true. If we’re just focusing on LLMs, structured and guided generation exists. Combine that with an eval set (= unit tests), you can at least track how well you’re doing. For sure, prompt engineering misses the feeling of being in control. You’ll also never be able to claim 100% coverage (although even with unit tests that’s not something you can claim, as there are always blind spots). What you gain over traditional coding, however, is that you can tackle problems that might otherwise take an infinite number of years to express in code. For example, how would you define the rules for detecting whether an image shows a bird?
It’s just a tool like any other. Overuse is currently detestably rife. But its value is there.
Source: ML engineer who secretly hates a lot about ML but is also in awe at the developments of the last few years.
Huh… Come to think of it…
Transfiguration always seemed like such a specific subject compared to the others. Although, then again, there’s room for divination as well.
Also: