810 karma · joined January 23, 2020
I have seem several people use AI to write apps to automate a process and along they way finally ask the question 'do we even need this process?'.
Regrettably this does not happen everywhere.
The core concept is that tokens/watt is tokens/watt ( for a given model of course ). A computer at home is actually less efficient overall because most of the time it is not doing tokens but still using a small footprint of power.
The revenue pressure is an interesting problem , but I suspect the actual demand math will be much more complicated.
I find local models interesting for sure, and run several on my own personal DGX cluster. I am however most certainly not power efficient!
This is such an odd and illogical conclusion. If a smaller model can be sufficient (which is not something I would have said), that smaller model can be ran in a datacenter. The idea that a small model running at home is 'sipping' while that same small model in a datacenter is 'slurping' is absurd. The datacenter will have much greater overall efficiency in both power usage and total cost to implement. Of course if you compare a small home model to a DC frontier model the power usage is different, but so is the output.
Indeed what made George special was that he was a broad 'engineer' first, and a specialist later. Everything was an engineering problem that could be solved. Perhaps most of all he believed in the students, hiring as many as he could get approved.
I found a 'bug' in the debugger on the NP1s that gave me a root escalation, and when he found out he said I should come work for him and that was that! About a year in we scrapped another older system and he had a spare disk that we put in the EE NP1 (en.ecn.purdue.edu) and mounted it as '/hogs' because I was always hogging disk space with stuff I downloaded. Funny enough I still have an exabyte tape backup of that drive.
Great times for sure. RIP.
On the plus side, someone will sometimes say while talking to me - oh your are that Subaru guy, or that youtube guy, or whatever and that is fun connection.
The other game this reminds me of is a game for the TI99/4a called Tunnels of Doom. It was a cartridge game that also had a floppy or cassette data load. It had a dynamic dungeon creation so every time you played the game you got a new unique experience. That would be an equally challenging one to reverse engineer due to the oddity of the GROM/GPL architecture in the TI99/4a.
One of the most interesting observations about AI is the timescale at which the favorite model and favorite task changes. Before November I found Sonnet to be interesting, but not moving that much of the needle. Once Opus came out it was clear the needle was not only moving, but moving fast.
The devices that reported BFI information were also stationary, and there were no extra devices transmitting information that would be conflicting.
A single camera would be much more effective.
I'm using mostly fiber just because the servers are connected to Cisco 9305 with 72 100g ports.
It has not lost its value yet, but the future will shift that value. All of the past experience you have is an asset for you to move with that shift. The problem will not be you losing value, it will be you not following where the value goes.
It might be a bit more difficult to love where the shift goes, but that is no different than loving being a artist which often shares a bed with loving being poor. What will make you happier?
Yet.
It could also be BAs being lazy and not jumping ahead of the train that is coming towards them. It feels like in this race the engineer who is willing to learn business will still have an advantage over the business person who learns tech. At least for a little while.