AI market sizing and the DePIN GPU case: io.net and Aethir
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Cites the AI market at $184B in 2024 heading to $826B by 2030 (Statista) and UBS's $420B 2027 revenue forecast, then argues io.net and Aethir can win GPU demand. Aethir commits 1,000 H100s to io.net, which has about 28,000 cluster-ready GPUs.
Key claims
AI market over $184B in 2024, projected over $826B by 2030
UBS: AI revenues 15x from $28B (2022) to $420B (2027E)
Goldman: about $1T of AI infra spend over the next few years
The artificial intelligence market surpassed 184 billion USD in 2024, a significant increase of nearly 50 billion from 2023.
This rapid growth is expected to continue, with the market projected to exceed 826 billion USD by 2030 according to @StatistaCharts.
@UBS expects AI industry revenues to grow 15x from $28B in 2022 to $420B in 2027E, or a CAGR of 72% in a report published earlier this year.
However, @UBS also notes that we are just entering the early stages of the AI growth cycle and that the forecast of $420B in revenues in 2027 is conservative at 0.3 - 0.4% of global GDP, given the significant cost savings & new business opportunities AI enables.
Meanwhile, @UBS remains confident in robust end demand for AI, driven by increased visibility in the infrastructure segment and expanding demand for AI applications and models throughout industries.
AI infrastructure primarily involves costs associated with training and running AI models and apps. This includes expenditures on computing resources such as graphics processing units (GPUs) and other chips, as well as spending on hardware like networking equipment and edge AI devices.
@GoldmanSachs recently estimated that around $1 trillion will be spent over the next few years on data centers, semiconductors, grid upgrades, and other parts of this AI infrastructure.
@GoldmanSachs also critically notes though that the hype around generative AI has relatively little to show for so far, especially considering the amount of money flowing into the space.
What AI overall definitely is though, is an opportunity for Web3 projects to find adoption in an emerging hyper-growth industry that has relevance outside of our crypto bubble.
Teams like @ionet or @aethir have identified this opportunity. 🤖✨
While @aethir is a leading GPU-as-a-Service provider in the Web3 space, @ionet acts as a GPU aggregator that plugs into consumer devices, data centers and service providers like @aethir.
In a recently expanded partnership, @aethir committed to providing a total of 1'000 @nvidia H100 GPUs to @ionet.
Overall, @ionet's global DePIN currently has around 28'000 cluster-ready GPUs that they aim to serve to AI/ML startups and other companies in need of affordable GPU resources.
Aside an edge on pricing that @ionet is going for, the decentralized nature and vast size of the network allows for highly customizable cluster solutions that can handle heavy workloads.
While the technology is nascent and the reliability of the service offering has to improve, the opportunity here is real.
There are also hurdles to overcome with regards to a certain scepticism that persists towards Web3 companies. If these can successfully be overcome and as the technology matures, @ionet and @aethir could grow into giants within the cloud computing space dominated today by large players like @awscloud, @azure or @googlecloud.
The PMF seems evident with both @ionet and @aethir already generating millions of $$$ in revenues and both $IO and $ATH sitting at billion dollar FDVs.
🧠 NFA but DYOR anon.
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