5,874 karma · joined September 25, 2008
Podcast : corecursive.com Work: pulumi.com
Email: adam at corecursive dot com
Non the less, excellent organization. I had a monthly donation that I let lapse and will reinstate.
Most of the real work is done by lawyers working pro bono for CCLA to fight charter issues.
Peter Watts has a very dark view of humanity.
I have this issue as well, of burning thru LED lights.
Say more about the process and / or drop some link pointers.
https://bellard.org/ts_zip/ https://corecursive.com/the-hutter-prize/
You need to reserve some inventory, charge a card, eventually email a customer and steps can go wrong. So you have queues, and retries and ways to back things out, undo changes.
To my understanding, Temporal's idea is to factor that part out, the queues and retries, and offsetting actions, so you write the logic and not the workflow orchestration.
https://vester.si/bodily-oddities/oddities/voluntary-eustach...
Whereas natural gas generators do not.
Hence the runs on gas turbines, while solar panels are plentiful. ( Although I'd guess the consistency of power is a bigger issue. )
Running existing coal is now supposedly more expensive then putting in new wind or solar ... all else being equal.
Sometimes when you're trying to write something, it really seems like the exact words matter a lot. Suggestions made to be more direct or use a more common word here or whatever seem to really impact the thought that you're trying to communicate.
Certainly we've all had times when trying to communicate clearly when the specific words seem very important.
Have you seen this leaderboard of sorts[1], and this proposal to change hutter prize[2]?
I think it's a really clever idea that you could measure an LLM's prediction abilities and language understanding by some sort of held-out compression metric because file sizes are very concrete. They are already beating shannon's numbers using a human prediction for compression, from what i can see.
Hutter Prize being where you are paid if you can compress wikipedia small enough. LLMs do very well at that, if, big if, you ignore the cost of initial weights.
A cool Claude Shannon story:
Shannon wanted to measure how much information is actually contained in ordinary
English text. His 1948 theory said such a number must exist, but he had no way to
calculate it, because the patterns in English reach across dozens of letters and no
equation or frequency table captures all of them at once.
So instead of calculating it, he ran an experiment on a person.
He took a passage from a novel that the subject had not read, and covered it with a
card so only the text already guessed was visible. He asked the subject to name
the first letter. If the guess was wrong, he asked again, and kept asking until the
subject named the correct letter. He wrote down how many guesses it had taken,
revealed the letter, and moved the card one position to the right. Then he repeated
the process for the next letter, and the next, through the whole passage.
What this produced was not a sequence of letters but a sequence of numbers — one
number per letter, recording how many guesses that letter required. Most of the
numbers were 1, because someone fluent in English, seeing the preceding text,
usually names the next letter correctly on the first attempt.
Shannon then argued that this sequence of numbers contains exactly as much
information as the original passage.
Sounds a lot like next token prediction to me.https://corecursive.com/the-hutter-prize/
I've never punched the air after fixing some bug that I didn't at some point earlier get extremely frustrated at its intractability.
The catching yourself and recentering is the thing.
I had to change my mind on AI detectors after playing around with it.
It would be interesting to hear how this detector compares. It also seems to be aiming for low fp rate.
It was super fun! You can shoot him an email from his website and he's definitely worth chatting with. He's on hacker news sometimes as well.
He has many wild stories! Steve Jobs melting his software by leaving the disk out in the sun. Being homeless. Working at the JPL. I think he had a hard childhood and went his own way.
But I'm reading Karp's authorized biography, The Philosopher in the Valley, and it does say names were chosen to be legible to military. Or something like that.