Why DePIN is the shortest way to bridge Web2 to Web3? ​ "AI presents a $200T market that nearly 2x cur. global GDP." mentioned on @0xCheeezzyyyy thread. ​ DePIN solves the problem of distributing resources accross blockchain. ​ Don't underestimate the power of decentralization, it's like the ants - small but strong enough to carry up to 50 times their weight. ​ ▸ @ionet - pioneering in Decentralizing GPUs ​ Owning GPUs require strong financial base. ​ Before the buzzword "AI," GPUs had already been sought after to serve crypto mining, especially for BTC or ETH. ​ Why GPUs? To non-tech users, GPUs are capable of parallel processing, which is ideal for solving cryptographic equations. ​ In the midst of the mining craze (during 2017), GPU prices skyrocketed. ​ For example, a popular GPU - Nvidia's GTX 1070 Ti - saw its prices surge by 100% due to high demand from Bitcoin rigs. And now, mining is super hard. However, GPUs have an ultimate mission to do: AI. ​ Till 2022 and early 2023, when ChatGPT and especially Generative AI were introduced, AI has officially stepped into golden era. ​ ➜ This, once again, pushed the GPU prices up dramatically. ​ Moreover, as mentioned in my very last post, hardware (GPUs) accounts for the largest proportion when training an AI model. ​ For example, GPT-3 requires thousands of NVIDIA V100s, costing $10k each. ​ At this cost, most SMEs cannot afford to build. ​ 👉 To sum up, putting all these GPUs on the cloud is needed to lower GPU costs - which is exactly what @ionet is offering. ▸ Decentralized GPUs provider comparison: ​ According to a report from Fortune Insights, GPUaaS (GPU as a service) market value is estimated at $4.31b in 2024. ​ And this figure is forecasted to reach nearly $50b in 2032. ​ Thus, this niche seems to be a delicious piece of cake if providers can optimize their GPU fixed costs. ​ Here's a board of recent players in the field: ​ Set market cap and FDV aside, let's talk about the scale of each player. ​ + @AethirCloud and @ionet have the highest amount of GPU capacity. ​ + @ionet and @akashnet_ are able to tap into the retail market. ​ + Counting the number of high-quality GPUs (like H100s): large scale belongs to @ionet and @AethirCloud. ​ In fact, IOnet and Aethir have been collaborating for a while to easily scale up and cover a wide range of market share. ▸ @ionet - the perfect solution for AI-built ​ Talking about all the services of IOnet, you can walk through my previous posts. ​ In this post, let's cover the overlap zone between them: ​ + IO Cloud: where builders rent GPUs + IO Worker: where owners register their GPUs for rental + IO Staking: where GPU owners stake to commit to their offerings ​ ➜ Thus, IOnet stands in the middle, opens up a GPU marketplace to charge rental fees and pays the owners (in terms of $IO). Moreover, since Co-staking feature was launched, $IO holders can join staking w/o owning a piece of GPU. ​ + IO Intelligence: an AI hub tapping into retail market, including ready-to-use AI models, APIs, and built-in agents. ​ 👉 Conclusion: @ionet team has been taking a huge step forward to meet the market need for GPU as a Service. Decentralizing GPUs is a must. ​ I have to admit that IOnet has already built a sustainable growth model that is too solid to fail.