A bit related: AI companies distilled the whole Web into LLMs to make computers smart, why humans can't do the same to make the best possible new Wikipedia with some copyrighted bits to make kids supersmart?
Why kids are worse than AI companies and have to bum around?)
> Imagine taking the whole Web, removing spam, duplicates, bad explanations
Uh huh. Now imagine the collective amount of work this would require above and beyond the already overwhelmed number of volunteer staff at Wikipedia. Curation is ALWAYS the bugbear of these kinds of ambitious projects.
Interactivity aside, it sounds like you want the Encyclopedia Brittanica.
What made it so incredible for its time was the staggeringly impressive roster of authors behind the articles. In older editions, you could find the entry on magic written by Harry Houdini, the physics section definitively penned by Einstein himself, etc.
"So, yep, I really wasn't even using my VPN that much recently - it's the same one I used for months.
And even bigger problem, of course, is - why just looking at my problem where a user with almost 1000 followers and a community that actively chats and spends a lot of time on X (usually, it's good for ad supported platforms).
So why even quite active paid users can't be checked in at least a day (I think it should be minutes but alas), why 5-7 days! ;-)"
Sadly it is almost inevitable we'll have another Bredolab-size botnet (30 mln computers, 1% of all) by cybercriminals but this time it'll be an AI botnet.
As soon as AI components will be useful, they'll be in botnets. And with such a size, you have more compute than OpenAI and can train a frontier misaligned model or modify an open source one:
The solution is to not just have 10% of compute in clouds like we have now but at least 50% in SOTA clouds, to have more compute than botnets. Have AI model App Store, probably NVIDIA will become like Apple:
Will have at least the most minimal checks on what runs on their hardware
We'll have to do it but better to do it early not late
It can be a unicorn startup that NVIDIA will want to buy (motivating gamers to put GPUs in clouds is easy, same with others really, you can share $30-1500/month with them by renting GPUs from your cloud to corporations and others)
There is Salad but they don't secure the hardware and software, so can't really have corporate clients. Amazon AWS, Azure, others, show that it's a real business. Unicorn-sized just in the USA (even bigger if global) if you'll do the math
>And with such a size, you have more compute than OpenAI and can train a frontier misaligned model or modify an open source one
That doesn't seem like a reasonable conclusion based on Open AI and leading lab expenditures. They need training data too, would one group actually be able to amass all of this? If you hijack 30 million random computers that's not as nearly as useful as 300K B200 GPUS for model training. Am I missing something?
The densest UI is a direct democratic simulated multiverse: imagine a long exposure photo as a 3D scene, in which you can walk or fly.
“Point and scroll the mouse wheel” to focus on a particular moment of time, make it crisp, or “scroll back” to see billions of years of time as a hazy long exposure scene.
Example: 14 bln years of our planet look like a hazy ocean (our planet was a water-world most of the time), with the Sun arcs static in the bright sky.
A radical proposal to do what AI companies did but for humans that just may work.
The author has another proposal that he claims can be a trivial to make viral YT horror indie game “Into the AI Brain” that will democratize AI interpretability
