Local Compute

“If you go beyond data centers, just look at the compute that we have unused in our homes. I have a PlayStation and Xbox right behind me that’s just sitting there — I probably use it once or twice a year — but just sitting there with powerful GPUs. And the computers, your Macs have M1 chips, which are very powerful GPUs that are not used… there’s a lot of underutilized resources that are spread globally that is using enormous amounts of energy that needs to be fixed.” — Greg Osuri, 00:30:58

“So we have a ton of GPUs that just are waiting and sitting… [Will there be room for the average home miner in the near future?] Absolutely. So now our entire focus is demand, not supply… Supply is enormous, and crypto is really good at getting supply, and we can turn [on] spigots very soon.” — Greg Osuri, 00:42:18

“Just look at the compute that we have unused in our homes. I have a PlayStation and Xbox right behind me that’s just sitting there — I probably use it once or twice a year — but just sitting there with powerful GPUs. And the computers — your Macs have M1 chips, which are very powerful GPUs, that are not used in the night… but you’re paying cooling for it. So there’s a lot of underutilized resources that are spread globally that is using enormous amounts of energy that needs to be fixed.” — Greg Osuri, 00:00:00

“When you have a future where you have computers [that] essentially are mobile — you can think about a robot or a self-driving vehicle — the compute is at the edge, and in order for edge compute to function you need to solve the communication cost problem… the only way to achieve that is the massive distribution of compute all across, with the incentive model for these providers.” — Greg Osuri, 01:10:12

“Akash has been working on GPUs for a very long time — if you remember Supermini… Supermini was supposed to be a supercomputer for the home, so you can have your own compute. So we’ve been exploring GPUs for over four years.” — Greg Osuri, 00:54:18

“With GPUs going to come more and more in my home, I think we’re going to see home supercomputers that are going to be local… because they need latency. They’re going to be analyzing, sensing and inference data, and training the data for your home operations in your home — they’re not going to go to the cloud.” — Greg Osuri, 00:39:01

“Consider a scenario where you have a supercomputer in your house and your neighbor has one and you need more power — you don’t want to go to the cloud, you can go ask your neighbor and use Akash to trade… It becomes like battery packs for GPUs at some point: just use it when you have, or sell it back to the grid… or get back from the grid when you need it.” — Greg Osuri, 00:39:45

“It was not a miner, it was a GPU — a very incredible machine with GPUs to train AI… we thought the way to achieve this is to actually make a device. Unfortunately COVID hit and we were unable to do anything hardware… so we essentially scrapped the project.” — Greg Osuri, 00:20:51

“In 2018 we wrote a paper called Akash Network, the decentralized supercloud… a key ideology in that is AI machine learning is getting expensive, cloud is getting very very expensive… and we did deep thesis on why AI needs a supercloud, and then we started working on enabling GPUs.” — Greg Osuri, 00:19:26

“Anyone with the GPU can provide compute [on] Akash, but chances of your GPU getting selected depends on the application… please, if you have an extra A100 lying around, please put that on Akash.” — Greg Osuri, 00:40:22

“Most advanced models like GPT-4, 3.5… work well on high-end GPUs, but as they mature, as they get older, they get optimized to work on a distributed set of GPUs like 3090s, 4090s and whatnot — the lower-end GPUs, like gaming machines. So people that prefer these mature models over advanced models can use the lower-end GPUs.” — Greg Osuri, 00:41:49

“Most advanced models like GPT-4… work well on high-end GPUs. But as they mature, as they get older, they get optimized to work on a distributed set of GPUs like 3090s, 4090s, and whatnot, the lower-end GPUs, right? Like gaming machines.” — Greg Osuri, 00:41:37

“I envision a world where every home will have a supercomputer… no doubt about it. As AI gets more penetration, we’re going to realize there are privacy implications for AI.” — Greg Osuri, 00:43:16

“Why not that compute comes from your home? Just like today you’re able to produce energy from your renewables at your home and contribute back to the grid, why don’t we have a similar mode of compute contribution from your home to the compute grid? That is going to be a reality, and I have no doubt in my mind — if we bet that AI is going to take over our lives.” — Greg Osuri, 00:45:24

“I want to believe in a world that we are going to have sovereignty on the AIs. The only way to get sovereignty is control the chip; the only way to control the chip is to have it in your house… if you have your chips, you’re protected by the laws of your land.” — Greg Osuri, 00:46:50

“Can your home gaming PC be used for training? Yes, one day — not yet… We’re seeing gaming PCs actually getting a lot more used, and the rate at which they’re getting used is on uptrend. So that indicates that yes, in a not very distant future these gaming PCs will be a lot more usable.” — Greg Osuri, 00:18:07

“If you think about the global distribution of compute power, it’s everywhere. The best compute power is hyper-underutilized: gaming consoles — like my PlayStation and Xbox, I use them once a year during Christmas and most of the time I’m not using them, and they have very powerful GPUs sitting idle — to my desktops, to desktops at professional work environments, to data centers.” — Greg Osuri, 00:13:08

“There’s a whole movement right now happening with, instead of going to the GPU, bringing the GPU to you… a decentralized network can go places where a centralized cannot… Akash can go to a PlayStation, Akash can go to a refrigerator, Akash can go to anywhere a GPU exists and essentially bring that GPU to you using GPU-over-IP techniques.” — Greg Osuri, 00:24:56

“Now we are working on a way where you can leave the data where it is and bring the compute using IP or the internet… aggregate GPU supply or CPU supply… and give a federated GPU device on the device that has data… that’s perfect for scenarios where you have a Tesla or a PlayStation where you do not have full compute capabilities in terms of the device that holds the GPU, but we can extract the GPU and bring the GPU to the data.” — Greg Osuri, 00:46:48

“Ultimate goal is to get beyond the cloud parity, go into the home. There’s so much unused capacity in the home, where you have my PlayStation, my PS2, my Xbox which I use maybe once a year — you’re sitting on this massive compute capacity, GPUs — but Tesla, that’s not running in the night, is sitting and charging… it has an onboard data center, has about 200 GPUs.” — Greg Osuri, 00:59:51