GPU Economics

“You’re getting high quality, really high quality bare metal servers for next to nothing. I hope these prices will stay the way they are, but I think right off the bat we’re looking for like two to three x lower than the market… this is bare metal, so there’s nothing in the middle — you’re just getting raw performance that is not possible on the cloud today.” — Greg Osuri, 00:17:04

“You’re getting high quality, really high quality bare metal servers for next to nothing. I hope these prices will stay the way they are, but I think right off the bat we’re looking for like two to three x lower than the market… this is bare metal, so there’s nothing in the middle — you’re just getting raw performance that is not possible on the cloud today.” — Greg Osuri, 00:17:43

“Today to run an AI company on the cloud, it’s literally paying 20% of your margins to Amazon… you have this enormous amount of capacity… your utilization rates are significantly low in your data center, north of 85 or so in our conservative estimates — you have underutilized capacity.” — Greg Osuri, 00:08:29

“The most attractive area for us to focus is machine learning… because that segment is currently suffering with the immense cost problem… [an Andreessen Horowitz] report recently… stated essentially 20 [percent] of margins tend to go to the cloud. It’s extremely hard being a growth stage AI company that’s trying to survive in this increasingly prohibitive layer called cloud.” — Greg Osuri, 00:05:43

“The most attractive area for us to focus is machine learning… because that segment is currently suffering with the immense cost problem… [an Andreessen Horowitz] report recently… stated essentially 20 [percent] of margins tend to go to the cloud. It’s extremely hard being a growth stage AI company that’s trying to survive in this increasingly prohibitive layer called cloud.” — Greg Osuri, 00:05:43

“The model that we envisioned for an AI company to function is more of a peer-to-peer cloud… they have a server from the offices that has GPU clusters… they only use these clusters maybe two or three hours a day while they’re training these models… they can install Akash and offer this unused capacity and earn credits in exchange… and they can use these credits for when they want to use peak capacity. That’s really when you see providers becoming users and users becoming providers.” — Greg Osuri, 00:05:43

“The model that we envisioned for an AI company to function is more of a peer-to-peer cloud… they have a server from the offices that has GPU clusters… they only use these clusters maybe two or three hours a day while they’re training these models… they can install Akash and offer this unused capacity and earn credits in exchange… and they can use these credits for when they want to use peak capacity. That’s really when you see providers becoming users and users becoming providers.” — Greg Osuri, 00:05:43

“There’s an article by [Andreessen] Horowitz that stated about 20% of margins for a lot of AI companies go to paying the cloud bills, and… it’s rampant, it’s very very expensive.” — Greg Osuri, 01:17:44

“Especially as we see a lot of these proof-of-work coins start to switch to proof-of-stake… you’re gonna have a lot of GPUs on the market that… can do something better, and so I’m hoping to see that Akash will be there and ready to fill in those boots and take in all that capacity.” — Sunny Aggarwal, 01:21:20

“They can install Akash and earn compute credits in AKT tokens in their downtime, and when they want to peak they can use this AKT tokens to actually use for compute. So you essentially create a very amazing mechanism where the provider becomes a tenant and vice versa. It’s a self-serving ecosystem of a peer-to-peer cloud… that’s only possible on Akash.” — Greg Osuri, 01:19:10

“20% of revenues for these machine learning companies is going to the cloud… We’d love for these companies to install Akash and earn the tokens when they’re not using [their servers], and when they want to peak they can use these tokens to actually get compute. This is the use case where the provider becomes a tenant and vice versa, creating a truly peer-to-peer cloud.” — Greg Osuri, 00:46:37

“We’re working on futures as well — it’s still early design — I think opening up, creating a futures market for compute will add efficiency. Futures generally add efficiency to pricing.” — Greg Osuri, 01:05:57

“They could actually install Akash in their clusters and sell the underutilized… capacity back into the network like a power grid model, and earn tokens for that unused capacity, and when they want to use at peak… they can use these tokens… so in this case the provider itself becomes a payer, and that’s really an ideal peer-to-peer GPU cloud that we really want to target.” — Greg Osuri, 00:38:14

“We have amazing opportunities with Ethereum network… coming off proof of work and going to proof of stake — that opens up a whole range of GPUs on the market, so that’s significantly helpful for AI workloads.” — Greg Osuri, 00:14:49

“As we were deploying this Kubernetes in data centers across the walls, what we discovered was 85% or so of compute capacity that sits in these data centers remains unused. The reason being most data centers are planned for peak capacity to handle peak loads.” — Greg Osuri, 00:04:59

“We’ll be launching the world’s first GPU marketplace. So that’s going to be very exciting because there’s an enormous amount of GPUs that are getting essentially unlocked with Ethereum and a lot of these networks going to proof of stake… currently GPUs are extremely expensive on Amazon.” — Greg Osuri, 00:28:26

“When Ethereum moves to a proof of stake… all that hardware becomes useless. And it’s really good hardware… there is no marketplace, there’s no sort of like liquidity mechanism… So the solution is to install Akash and have users run TensorFlow applications or any of these machine learning applications and take advantage of this chip compute.” — Greg Osuri, 00:29:14

“Эфир переходит на Proof of Stake, а значит, огромная инфраструктура графических адаптеров, которая поддерживает эфир, станет никому не нужной. Это предоставляет огромную возможность для рынка ИИ, искусственного интеллекта. Мы строим инфраструктуру, ориентированную именно на этот рынок.” (“Ethereum is moving to Proof of Stake, which means the enormous GPU infrastructure supporting Ethereum will no longer be needed by anyone. This presents a huge opportunity for the AI market. We are building infrastructure aimed precisely at that market.”)” — Greg Osuri, 00:15:47

“Есть довольно много неиспользуемых графических адаптеров по всему миру, и эта цифра будет продолжать расти, потому что многие из этих сетей сейчас переходят от Proof-of-Work на Proof-of-Stake… Когда произойдет переход, мы хотим быть готовы к работе с рынком графических процессоров. Мы считаем, что сможем купить их за полцены, а для рынка искусственного интеллекта это очень важно.” (“There are quite a lot of unused GPUs around the world, and that number will keep growing because many of these networks are moving from Proof-of-Work to Proof-of-Stake… When the transition happens, we want to be ready to work with the GPU market. We believe we’ll be able to buy them at half price, and for the artificial intelligence market that is very important.”)” — Greg Osuri, 00:30:52

“Ethereum network moving off proof of work and moving on to proof of stake implies that this entire GPU infrastructure Ethereum miners have built is going to become obsolete, and we want to tap into that… and enable a multi-tenancy GPU marketplace… I think it’s going to be huge for us.” — Greg Osuri, 00:38:02

“Today on the cloud, if you are a machine learning company using Amazon, 20% of your margins go to Amazon, and you and I, even though we don’t run machine learning workloads, are actually paying an invisible Amazon tax.” — Greg Osuri, 00:38:02

“We leverage essentially 85 or so [percent] underutilized cloud capacity in about 8.4 million data centers to enable anyone with a computer to buy and sell cloud compute in a safe and frictionless market… the tenant… experiences anywhere from 8x to 10x lower cost than what you would pay Amazon.” — Greg Osuri, 00:00:43

“Later this year we’re coming up with GPU marketplace — it’ll be the world’s first open marketplace for GPU compute, and it’s a big deal because the GPU segment is suffering right now… 20 percent of their margins go to Amazon, and we have enormous capacity, enormous GPU demand, where some of the customers are spending about a million to two million dollars a month on GPU right now — they want to come to Akash.” — Greg Osuri, 00:17:02

“A16z wrote an article recently that basically said 20% of margins for AI companies goes to Amazon. So it is so big that it is actually hurting their viability to exist as a business. It’s no longer a secondary cost, it is a primary cost, sometimes much more than payroll… I’m particularly excited about AI workloads.” — Greg Osuri, 00:09:55

“Another interesting event that is going to happen over the next couple of years is Ethereum moving off proof of work and coming to proof of stake — [that] unlocks enormous amount of computing… there’s enormous amount of GPUs that are being unlocked and we want to offer that to a customer base that’s really suffering quite a bit right now.” — Greg Osuri, 00:28:29

“If you think about Ethereum network moving off proof of work and moving on to proof of stake implies that this entire GPU infrastructure Ethereum miners have built is going to become obsolete, and we want to tap into that… and enable a multi-tenancy GPU marketplace… I think it’s going to be huge for us.” — Greg Osuri, 00:33:26

“Today on the cloud, if you are a machine learning company using Amazon, 20% of your margins go to Amazon, and you and I, even though we don’t run machine learning workloads, are actually paying an invisible Amazon tax.” — Greg Osuri, 00:32:42

“When it comes to Akash, the cost advantage of using Akash versus a centralized cloud is one-third… sometimes it is one-fourth, like when compared to Google. And the reason for that is because open marketplaces generally tend to optimize for the forces of demand-supply for pricing, versus an individual setting the price.” — Greg Osuri, 00:08:32

“It turns out 85 to 90 [percent] of data centers in the world are not used or underutilized… the result is the cost advantage you get on Akash is about one-third than Amazon. So if you’re paying a dollar on Amazon, you pay 30 cents in Akash — that’s just a pure free market at its best.” — Greg Osuri, 00:05:00

“That should be out in another six months or so if everything goes right — and turns out making a multi-tenancy marketplace for GPUs is not the easiest thing… if you can run TensorFlow on Akash — you can right now, but with GPUs — I think that’s going to be a holy grail.” — Greg Osuri, 00:15:31

“A big feature that’s upcoming is GPUs. For us, GPUs are one of the most exciting things for me, because today the biggest cost for AI is GPUs. Andreessen Horowitz even wrote an amazing article recently looking at their portfolio companies… this GPU cost, which is about 20% of margins — so 20% of the money, either investment or revenue, these AI companies make goes to Amazon, which is a lot.” — Greg Osuri, 00:13:25

“Supermini will become a reality when Akash enables GPU, which is in the next few months essentially.” — Greg Osuri, 00:48:24

“While we were deploying, we discovered that most capacity in these data centers — somewhere north of 85 percent of capacity — remains unused for various reasons, and that’s when the idea for a marketplace came about.” — Greg Osuri, 00:02:15

“Right now Akash supports CPUs only, but in about six months’ time you’ll start supporting GPUs — the work is underway. What that means is a lower cost GPU-based compute. As you know, GPU is very, very expensive on the cloud, so any cost reduction I think is a big, big win for the data science community.” — Greg Osuri, 00:03:36

“Machine learning is so expensive that if you look at any S1 filings from web 2 companies like Snowflake or whatnot, there’s a strong indication that 50 percent or so of margins actually go to pay Amazon bills.” — Greg Osuri, 00:29:07

“The important part of this model is that developers set the price, versus the traditional model where providers set the price… today Akash costs anywhere from half to one-fifth what you would pay on Amazon.” — Greg Osuri, 00:16:16

“We’re going to have machine learning in another six months hopefully… Ethereum is coming off proof of work to proof of stake, and that’s going to unleash a humongous amount of GPU systems that were primarily used for mining… having machine learning run on these GPU instances at 20% lower cost is going to be a huge win, and we have enterprise customers lined up.” — Greg Osuri, 00:29:49

“Akash right now offers a price point that’s one-third to one-fifth lower than Amazon. So when you see that sort of arbitrage opportunity… the best way to realize that opportunity is to mine. So we’ve seen quite a bit of miners… and we’re seeing quite a bit of Chia miners… so far it’s been more supply than demand, surprisingly.” — Greg Osuri, 00:15:32

“There’s a whole rework happening on economics now for Akash. We’re looking at enabling more DeFi primitives into the dCloud, in the sense we want to do futures for compute — a futures market for compute is something that doesn’t exist today and it can be great to do it in an open way.” — Greg Osuri, 00:32:36

“A big source of GPUs in the next six months is going to be from Ethereum miners. As you know, Ethereum is moving off proof of work to proof of stake — that unlocks [an] enormous amount of GPU capability in the market that has really nowhere to go, and Akash being a prime cloud partner would be an amazing use for us to use these GPUs and offer that at a discount that’s significant from what’s being offered in the market right now.” — Greg Osuri, 00:26:23