Not really, the politicians with a Trumpian style (Johnson and Truss) came after brexit and got there because of the polarisation caused by brexit (and had the example of Trump himself). There was definitely a lot of lying and false claims that were used by the leave campaign in order to get brexit and it shared some similarities with Trump, but it wasnt politics in the the style of being completely divorced from reality and overwhelming incompetance that defines Trump.
10% to 80% seems like too wide a range for your range of “how many are on the largest instance” 10% means only 1 in ten users are on the largest instance and 9/10 are spread out on the rest, If anything that seems overly fragmented. On the other end 80% means 4/5 users are on the largest instance and 1/5 are shared between all other instances which is incredibly concentrated.
I’d sugest narrowing the range to 20% to 66%, 1 in 5 on the largest instance is still plenty dispersed to ensure that there is competition/variety and 2 in 3 users on the largest instance is already well into monopoly territory.
As per the article:
It uses high frequency radio waves to disrupt or damage critical electronic components inside drones, causing them to crash or malfunction.
Its not jamming the comms, its inducing currents inside the electronics of the drone to fry them.
Even if it were true (which I’m pretty sure it isnt) so what? The whole benefit of free software is people can fork it and make their own version if they dont like where it is headded.
Empty sequences being false goes back a lot further than perl, it was already a thing in the first lisp (in fact the empty list was the cannonical false).
We also didnt understand how the internet would change the world, still went ahead with it. We didnt understand how computers would change the world, still went ahead with it, we didnt understand how the steam engine would change the world… etc etc.
No one can know how a new invention will change things, but you are not going to be able to crush human’s innate creativity and drive to try new things. Sometimes those things are going to be a net negative and that’s bad, but the alternative is to insist nothing new is tried and thats A bad and B not possible.
People being economically displaced from innovation increasing productivity is good provided it happens at a reasonable pace and there is a sufficient social safety net to get those people back on their feet. Unfortunately those safety nets dont exist everywhere and have been under attack (in the west) for the past 40 years.
Translations apps would be the main one for LLM tech, LLMs largely came out of google’s research into machine translation.
So where does it end? Slugs, mites, krill, bacteria, viruses? How do you draw a line that says free will this side of the line, just mechanics and random chance this side of the line?
I just dont find it a particularly useful concept.
Ok, but then you run into why does billions of vairables create free will in a human but not a computer? Does it create free will in a pig? A slug? A bacterium?
In a Ted Talk in April, Li further explained the field of research her startup will work on advancing, which involves algorithms capable of realistically extrapolating images and text into three-dimensional environments and acting on those predictions, using a concept known as “spatial intelligence.” This could bolster work in various fields such as robotics, augmented reality, virtual reality, and computer vision. If these capabilities continue to advance in the ambitious ways Li plans, it has the potential to transform industries like healthcare and manufacturing.
I mean that sounds a lot more interesting than 99% of the LLM work going on at the moment, and given that she lead the team that cracked the computer vision problem of recognising objects she has pedigree.
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