io.net State of the Network: why IO could be a generational opportunity
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Bullish call$IO−89%since this piece, moved against the callHow it played out ↓Breaks down io.net's $40M raise and long-term plan against rising AI compute costs and a roughly $2.5T cloud market by 2032. Argues it is the only decentralized GPU network with Ray-based geo-distributed clustering.
Key claims
io.net raised $40M, $30M Series A led by Hack VC
1M+ compute hours served across 138+ countries
Decentralized compute is under 1% of the market
𝐓𝐡𝐞 𝐒𝐭𝐚𝐭𝐞 𝐨𝐟 𝐭𝐡𝐞 𝐍𝐞𝐭𝐰𝐨𝐫𝐤
$IO 𝗿𝗮𝗶𝘀𝗲𝗱 𝗮 𝘁𝗼𝘁𝗮𝗹 𝗼𝗳 $𝟰𝟬𝗠 with a Series A round led by @hack_vc accounting for $30M.
Funding that will allow @ionet to break into a 𝘁𝗿𝗶𝗹𝗹𝗶𝗼𝗻 $$$ 𝗺𝗮𝗿𝗸𝗲𝘁 and rival players like @awscloud, currently dominating the market for high-performance compute, which fuels AI innovation globally.
In an open letter that dropped yesterday, @MTorygreen lives up to his role as the visionary leader of @ionet and lays out a clear long-term path for $IO to succeed on this ambitious mission.
𝑅𝑒𝑎𝑑𝑦 𝑓𝑜𝑟 𝑎𝑙𝑝ℎ𝑎 𝑎𝑛𝑜𝑛?
𝐖𝐡𝐲 $𝐈𝐎 𝐂𝐨𝐮𝐥𝐝 𝐁𝐞 𝐚 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐎𝐩𝐩𝐨𝐫𝐭𝐮𝐧𝐢𝐭𝐲. ⤵️
Before we dive into @ionet's long-term game plan, let me briefly set the stage for an understanding of why the concept of decentralized compute is so powerful.
➊ 𝗧𝗵𝗲 𝗥𝗶𝘀𝗲 𝗼𝗳 𝗔𝗜 𝗳𝘂𝗲𝗹𝘀 𝘁𝗵𝗲 𝗗𝗲𝗺𝗮𝗻𝗱 𝗳𝗼𝗿 𝗖𝗼𝗺𝗽𝘂𝘁𝗲
The rising demand for computing power, driven by an AI industry in hyper-growth propelled the demand for high-performance hardware such as GPUs to record heights.
Meanwhile, the fast advances on the sophistication and complexity of these models has also led to a massive increase in training costs for large language models (LLMs) and similar technologies.
That has caused significant cost escalations, driven by the need for vast hardware resources such as GPUs and advanced networking infrastructure.
@Meta’s infrastructure cost for example rose 33% year-over-year, amounting to $8.5 billion in Q2 2024.
A trend fueled by Meta's AI/ML initiatives (training LLaMA).
With these technologies maturing, the requirements for machine and deep learning are doubling every 3.4 months.
Model training costs are increasing by 3,400% per year right now.
Let me be slightly more specific here. ⤵️
Training @OpenAI’s GPT-4 cost approximately $78.4 million, up significantly from Google’s PaLM model, which cost $12.4 million just a year earlier.
A development that is not unique to @OpenAI though.
@Meta’s upcoming LLaMA 4 model is expected to require 10 times more computing power than its predecessor, once again increasing Meta's infrastructure cost significantly.
➋ 𝗧𝗵𝗲 𝗟𝗶𝗺𝗶𝘁𝗮𝘁𝗶𝗼𝗻𝘀 𝗼𝗳 𝗧𝗿𝗮𝗱𝗶𝘁𝗶𝗼𝗻𝗮𝗹 𝗖𝗼𝗺𝗽𝘂𝘁𝗲 𝗠𝗮𝗿𝗸𝗲𝘁𝘀
The race towards more and more powerful AI models requires enormous amounts of compute.
It will be another massive catalyst for the cloud computing market, which is expected to grow to roughly $2.5 Trillion in size by 2032.
However, cloud providers like AWS, @Azure or GCP struggle to meet this demand due to supply chain constraints, logistical challenges, and high capital expenses, resulting in delays, limited options, and higher costs.
This significantly hinders innovation and imposes barriers on AI/ML startups that, for example due to the cost of compute resources, are priced out of traditional GPU markets, hence lacking access to the computing power they need to train and run their models.
It also re-enforces the oligopolistic market structure, in which the big tech companies that already have all the funding, talent and data, also dominate compute resources, giving them more than an unfair advantage vs. smaller competitors.
@ionet will fix this and even the playing field.
➌ 𝗚𝗲𝗼-𝗗𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗲𝗱 𝗖𝗹𝘂𝘀𝘁𝗲𝗿𝗶𝗻𝗴 𝗼𝗻 $𝗜𝗢 𝗶𝘀 𝘁𝗵𝗲 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻
The need for a better solution is evident.
Decentralized networks like @ionet offer exactly that.
A revolutionary way of aggregating underutilized GPUs globally, providing massive computing power, scalability, and cost efficiency.
$IO reduces latency through distributed nodes, enhances censorship resistance, and lowers cost by tapping into idle hardware resources.
While decentralized computing currently accounts for less than 1% of the overall market, it definitely bears enormous growth potential.
If @ionet executes well, it definitely has a good chance to capture a significant share of this $2.5 trillion industry.
Offering a faster, cheaper, and more flexible alternative to traditional cloud providers to players otherwise under-served or fully priced out of the market.
➍ 𝗧𝗵𝗲 𝗟𝗼𝗻𝗴-𝗧𝗲𝗿𝗺 𝗣𝗮𝘁𝗵 𝘁𝗼 𝗦𝘂𝗰𝗰𝗲𝘀𝘀 𝗳𝗼𝗿 $𝗜𝗢
To achieve its ambitious goals, a clear execution path is essential.
In the $IO State of the Network, @MTorygreen outlines exactly that.
Let me give you a quick TL;DR. ⤵️
@ionet has already achieved great things.
Over 1M hours of compute served and nearly 2M on-chain transactions, processed on a network of tens of 1000s of cluster-ready GPUs across >138 countries.
Going forward, $IO will focus on the fundamentals. ⤵️
✪ 𝗘𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲-𝗚𝗿𝗮𝗱𝗲 𝗦𝗲𝗿𝘃𝗶𝗰𝗲: Match or exceed traditional cloud service standards at lower costs.
$𝘐𝘖 𝘸𝘪𝘭𝘭 𝘴𝘵𝘳𝘦𝘯𝘨𝘵𝘩𝘦𝘯 𝘪𝘵𝘴 𝘗𝘳𝘰𝘰𝘧 𝘰𝘧 𝘞𝘰𝘳𝘬 𝘴𝘺𝘴𝘵𝘦𝘮 𝘣𝘺 𝘢𝘥𝘥𝘳𝘦𝘴𝘴𝘪𝘯𝘨 𝘢𝘵𝘵𝘢𝘤𝘬 𝘷𝘦𝘤𝘵𝘰𝘳𝘴, 𝘢𝘥𝘥𝘪𝘯𝘨 𝘝𝘙𝘈𝘔 𝘤𝘩𝘦𝘤𝘬𝘴, 𝘦𝘯𝘩𝘢𝘯𝘤𝘪𝘯𝘨 𝘩𝘢𝘳𝘥𝘸𝘢𝘳𝘦 𝘷𝘦𝘳𝘪𝘧𝘪𝘤𝘢𝘵𝘪𝘰𝘯, 𝘢𝘯𝘥 𝘪𝘮𝘱𝘭𝘦𝘮𝘦𝘯𝘵𝘪𝘯𝘨 𝘴𝘵𝘳𝘪𝘤𝘵𝘦𝘳 𝘣𝘦𝘯𝘤𝘩𝘮𝘢𝘳𝘬𝘴. 𝘈 𝘯𝘦𝘸 𝘵𝘪𝘦𝘳𝘪𝘯𝘨 𝘴𝘺𝘴𝘵𝘦𝘮 𝘸𝘪𝘭𝘭 𝘳𝘦𝘲𝘶𝘪𝘳𝘦 𝘒𝘠𝘊/𝘒𝘠𝘉 𝘷𝘦𝘳𝘪𝘧𝘪𝘤𝘢𝘵𝘪𝘰𝘯 𝘢𝘯𝘥 𝘐𝘖 𝘤𝘰𝘪𝘯 𝘴𝘵𝘢𝘬𝘪𝘯𝘨 𝘵𝘰 𝘱𝘳𝘦𝘷𝘦𝘯𝘵 𝘴𝘱𝘰𝘰𝘧𝘪𝘯𝘨, 𝘸𝘩𝘪𝘭𝘦 𝘢 𝘴𝘵𝘢𝘬𝘪𝘯𝘨 𝘢𝘯𝘥 𝘴𝘭𝘢𝘴𝘩𝘪𝘯𝘨 𝘱𝘳𝘰𝘨𝘳𝘢𝘮 𝘸𝘪𝘭𝘭 𝘴𝘦𝘤𝘶𝘳𝘦 𝘵𝘩𝘦 𝘯𝘦𝘵𝘸𝘰𝘳𝘬. 𝘋𝘦𝘵𝘢𝘪𝘭𝘦𝘥 𝘴𝘺𝘴𝘵𝘦𝘮 𝘥𝘢𝘵𝘢 𝘸𝘪𝘭𝘭 𝘣𝘦 𝘴𝘩𝘢𝘳𝘦𝘥 𝘩𝘰𝘶𝘳𝘭𝘺, 𝘸𝘪𝘵𝘩 𝘳𝘦𝘸𝘢𝘳𝘥𝘴 𝘧𝘰𝘳 𝘪𝘥𝘦𝘯𝘵𝘪𝘧𝘺𝘪𝘯𝘨 𝘧𝘳𝘢𝘶𝘥. $𝘐𝘖 𝘸𝘪𝘭𝘭 𝘢𝘭𝘴𝘰 𝘤𝘰𝘭𝘭𝘢𝘣𝘰𝘳𝘢𝘵𝘦 𝘸𝘪𝘵𝘩 𝘵𝘩𝘪𝘳𝘥 𝘱𝘢𝘳𝘵𝘪𝘦𝘴 𝘵𝘰 𝘦𝘯𝘩𝘢𝘯𝘤𝘦 𝘷𝘦𝘳𝘪𝘧𝘪𝘤𝘢𝘵𝘪𝘰𝘯 𝘢𝘯𝘥 𝘴𝘺𝘴𝘵𝘦𝘮 𝘳𝘦𝘭𝘪𝘢𝘣𝘪𝘭𝘪𝘵𝘺.
✪ 𝗔𝗴𝗴𝗿𝗲𝘀𝘀𝗶𝘃𝗲 𝗥𝗲𝘃𝗲𝗻𝘂𝗲 𝗚𝗿𝗼𝘄𝘁𝗵: Leverage competitive advantages of decentralized computing to disrupt traditional providers.
$𝘐𝘖 𝘸𝘪𝘭𝘭 𝘦𝘹𝘱𝘢𝘯𝘥 𝘦𝘹𝘪𝘴𝘵𝘪𝘯𝘨 𝘤𝘶𝘴𝘵𝘰𝘮𝘦𝘳 𝘳𝘦𝘭𝘢𝘵𝘪𝘰𝘯𝘴𝘩𝘪𝘱𝘴, 𝘣𝘶𝘪𝘭𝘥𝘪𝘯𝘨 𝘰𝘯 56 𝘥𝘦𝘢𝘭𝘴, 𝘢𝘴 𝘮𝘢𝘯𝘺 𝘤𝘭𝘪𝘦𝘯𝘵𝘴 𝘱𝘭𝘢𝘯 𝘵𝘰 𝘪𝘯𝘤𝘳𝘦𝘢𝘴𝘦 𝘶𝘴𝘢𝘨𝘦, 𝘥𝘳𝘪𝘷𝘪𝘯𝘨 𝘎𝘔𝘝 𝘨𝘳𝘰𝘸𝘵𝘩. 𝘛𝘩𝘦 𝘴𝘢𝘭𝘦𝘴 𝘵𝘦𝘢𝘮 𝘸𝘪𝘭𝘭 𝘧𝘰𝘤𝘶𝘴 𝘰𝘯 𝘨𝘳𝘰𝘸𝘪𝘯𝘨 𝘵𝘩𝘦 𝘱𝘪𝘱𝘦𝘭𝘪𝘯𝘦 𝘰𝘧 𝘈𝘐/𝘔𝘓 𝘴𝘵𝘢𝘳𝘵𝘶𝘱𝘴 𝘪𝘯 𝘵𝘩𝘦 𝘜𝘚, 𝘌𝘜, 𝘢𝘯𝘥 𝘈𝘗𝘈𝘊. $𝘐𝘖 𝘢𝘭𝘴𝘰 𝘢𝘪𝘮𝘴 𝘵𝘰 𝘪𝘯𝘤𝘳𝘦𝘢𝘴𝘦 𝘪𝘵𝘴 𝘴𝘶𝘱𝘱𝘭𝘺 𝘰𝘧 𝘦𝘯𝘵𝘦𝘳𝘱𝘳𝘪𝘴𝘦-𝘨𝘳𝘢𝘥𝘦 𝘎𝘗𝘜𝘴 𝘢𝘤𝘳𝘰𝘴𝘴 𝘬𝘦𝘺 𝘳𝘦𝘨𝘪𝘰𝘯𝘴. 𝘉𝘺 𝘣𝘶𝘯𝘥𝘭𝘪𝘯𝘨 𝘤𝘰𝘮𝘱𝘶𝘵𝘦 𝘸𝘪𝘵𝘩 𝘴𝘵𝘰𝘳𝘢𝘨𝘦, 𝘵𝘩𝘦 𝘤𝘰𝘮𝘱𝘢𝘯𝘺 𝘸𝘪𝘭𝘭 𝘦𝘯𝘩𝘢𝘯𝘤𝘦 𝘎𝘔𝘝 𝘢𝘯𝘥 𝘤𝘶𝘴𝘵𝘰𝘮𝘦𝘳 𝘳𝘦𝘵𝘦𝘯𝘵𝘪𝘰𝘯. 𝘈𝘥𝘥𝘪𝘵𝘪𝘰𝘯𝘢𝘭𝘭𝘺, 𝘢 𝘤𝘩𝘢𝘯𝘯𝘦𝘭 𝘱𝘢𝘳𝘵𝘯𝘦𝘳 𝘱𝘳𝘰𝘨𝘳𝘢𝘮 𝘵𝘢𝘳𝘨𝘦𝘵𝘪𝘯𝘨 𝘈𝘐/𝘔𝘓 𝘢𝘯𝘥 𝘞𝘦𝘣3 𝘤𝘰𝘮𝘱𝘢𝘯𝘪𝘦𝘴 𝘸𝘪𝘭𝘭 𝘣𝘳𝘰𝘢𝘥𝘦𝘯 𝘥𝘪𝘴𝘵𝘳𝘪𝘣𝘶𝘵𝘪𝘰𝘯 𝘢𝘯𝘥 𝘧𝘶𝘦𝘭 𝘨𝘳𝘰𝘸𝘵𝘩 𝘵𝘩𝘳𝘰𝘶𝘨𝘩 𝘴𝘵𝘳𝘢𝘵𝘦𝘨𝘪𝘤 𝘢𝘭𝘭𝘪𝘢𝘯𝘤𝘦𝘴.
✪ 𝗖𝗼𝗺𝗺𝘂𝗻𝗶𝘁𝘆 𝗜𝗻𝘃𝗼𝗹𝘃𝗲𝗺𝗲𝗻𝘁: Actively collaborate with the community to foster innovation and agility.
$𝘐𝘖 𝘸𝘪𝘭𝘭 𝘪𝘮𝘱𝘭𝘦𝘮𝘦𝘯𝘵 𝘢 3-𝘮𝘰𝘯𝘵𝘩 𝘳𝘰𝘢𝘥𝘮𝘢𝘱 𝘸𝘪𝘵𝘩 𝘮𝘰𝘯𝘵𝘩𝘭𝘺 𝘮𝘪𝘭𝘦𝘴𝘵𝘰𝘯𝘦𝘴, 𝘱𝘳𝘰𝘷𝘪𝘥𝘦 𝘰𝘯𝘦-𝘮𝘰𝘯𝘵𝘩 𝘯𝘰𝘵𝘪𝘤𝘦 𝘧𝘰𝘳 𝘤𝘩𝘢𝘯𝘨𝘦𝘴, 𝘢𝘯𝘥 𝘩𝘰𝘭𝘥 𝘸𝘦𝘦𝘬𝘭𝘺 𝘈𝘔𝘈𝘴 𝘸𝘪𝘵𝘩 𝘴𝘦𝘯𝘪𝘰𝘳 𝘭𝘦𝘢𝘥𝘦𝘳𝘴𝘩𝘪𝘱. 𝘈 𝘱𝘶𝘣𝘭𝘪𝘤 𝘪𝘴𝘴𝘶𝘦 𝘵𝘳𝘢𝘤𝘬𝘦𝘳 𝘢𝘯𝘥 𝘥𝘦𝘥𝘪𝘤𝘢𝘵𝘦𝘥 𝘋𝘪𝘴𝘤𝘰𝘳𝘥 𝘤𝘩𝘢𝘯𝘯𝘦𝘭𝘴 𝘸𝘪𝘭𝘭 𝘮𝘢𝘯𝘢𝘨𝘦 𝘤𝘰𝘮𝘮𝘶𝘯𝘪𝘵𝘺 𝘧𝘦𝘦𝘥𝘣𝘢𝘤𝘬. 𝘙𝘦𝘸𝘢𝘳𝘥 𝘱𝘳𝘰𝘨𝘳𝘢𝘮𝘴 𝘸𝘪𝘭𝘭 𝘦𝘯𝘨𝘢𝘨𝘦 𝘢𝘯𝘥 𝘪𝘯𝘤𝘦𝘯𝘵𝘪𝘷𝘪𝘻𝘦 𝘢𝘤𝘵𝘪𝘷𝘦 𝘮𝘦𝘮𝘣𝘦𝘳𝘴. $𝘐𝘖 𝘱𝘭𝘢𝘯𝘴 𝘵𝘰 𝘤𝘰𝘯𝘵𝘪𝘯𝘶𝘦 𝘰𝘯 𝘪𝘵𝘴 𝘱𝘢𝘵𝘩 𝘵𝘰𝘸𝘢𝘳𝘥𝘴 𝘥𝘦𝘤𝘦𝘯𝘵𝘳𝘢𝘭𝘪𝘻𝘢𝘵𝘪𝘰𝘯 𝘷𝘪𝘢 𝘋𝘈𝘖𝘴 𝘢𝘯𝘥 𝘵𝘰𝘬𝘦𝘯-𝘣𝘢𝘴𝘦𝘥 𝘷𝘰𝘵𝘪𝘯𝘨 𝘵𝘰 𝘨𝘪𝘷𝘦 𝘵𝘩𝘦 𝘤𝘰𝘮𝘮𝘶𝘯𝘪𝘵𝘺 𝘧𝘶𝘭𝘭 𝘨𝘰𝘷𝘦𝘳𝘯𝘢𝘯𝘤𝘦 𝘤𝘰𝘯𝘵𝘳𝘰𝘭.
✪ 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗮 𝗪𝗼𝗿𝗹𝗱-𝗖𝗹𝗮𝘀𝘀 𝗧𝗲𝗮𝗺: Recruit the best talent in Cloud Computing, Web3 and AI.
$𝘐𝘖’𝘴 𝘴𝘶𝘤𝘤𝘦𝘴𝘴 𝘪𝘴 𝘥𝘳𝘪𝘷𝘦𝘯 𝘣𝘺 𝘢 𝘵𝘢𝘭𝘦𝘯𝘵𝘦𝘥 𝘵𝘦𝘢𝘮, 𝘣𝘶𝘵 𝘵𝘰 𝘤𝘰𝘮𝘱𝘦𝘵𝘦 𝘸𝘪𝘵𝘩 𝘉𝘪𝘨 𝘊𝘭𝘰𝘶𝘥, 𝘸𝘦 𝘮𝘶𝘴𝘵 𝘤𝘰𝘯𝘵𝘪𝘯𝘶𝘦 𝘦𝘹𝘱𝘢𝘯𝘥𝘪𝘯𝘨 𝘸𝘩𝘪𝘭𝘦 𝘶𝘱𝘩𝘰𝘭𝘥𝘪𝘯𝘨 𝘩𝘪𝘨𝘩 𝘴𝘵𝘢𝘯𝘥𝘢𝘳𝘥𝘴. 𝘞𝘦 𝘸𝘪𝘭𝘭 𝘮𝘢𝘪𝘯𝘵𝘢𝘪𝘯 𝘢 𝘤𝘶𝘭𝘵𝘶𝘳𝘦 𝘰𝘧 𝘢𝘤𝘤𝘰𝘶𝘯𝘵𝘢𝘣𝘪𝘭𝘪𝘵𝘺 𝘸𝘪𝘵𝘩 𝘤𝘭𝘦𝘢𝘳 𝘒𝘗𝘐𝘴, 𝘳𝘦𝘤𝘳𝘶𝘪𝘵 𝘰𝘯𝘭𝘺 𝘵𝘩𝘦 𝘣𝘦𝘴𝘵 𝘵𝘢𝘭𝘦𝘯𝘵, 𝘢𝘯𝘥 𝘵𝘢𝘳𝘨𝘦𝘵 𝘵𝘰𝘱 𝘱𝘳𝘰𝘧𝘦𝘴𝘴𝘪𝘰𝘯𝘢𝘭𝘴 𝘧𝘳𝘰𝘮 𝘤𝘰𝘮𝘱𝘦𝘵𝘪𝘵𝘰𝘳𝘴 𝘭𝘪𝘬𝘦 𝘈𝘞𝘚 𝘢𝘯𝘥 𝘈𝘻𝘶𝘳𝘦. 𝘛𝘩𝘦𝘴𝘦 𝘪𝘯𝘥𝘪𝘷𝘪𝘥𝘶𝘢𝘭𝘴 𝘸𝘪𝘭𝘭 𝘣𝘦 𝘦𝘮𝘱𝘰𝘸𝘦𝘳𝘦𝘥 𝘵𝘰 𝘣𝘶𝘪𝘭𝘥 𝘢 𝘴𝘤𝘢𝘭𝘢𝘣𝘭𝘦, 𝘰𝘱𝘦𝘯 𝘴𝘺𝘴𝘵𝘦𝘮, 𝘤𝘳𝘶𝘤𝘪𝘢𝘭 𝘧𝘰𝘳 𝘰𝘶𝘳 𝘭𝘰𝘯𝘨-𝘵𝘦𝘳𝘮 𝘴𝘶𝘤𝘤𝘦𝘴𝘴.
To dive into the details of the $IO long-term strategy, have a look here:
𝚑𝚝𝚝𝚙𝚜://𝚒𝚘.𝚗𝚎𝚝/𝚂𝚝𝚊𝚝𝚎𝙾𝚏𝚃𝚑𝚎𝙽𝚎𝚝𝚠𝚘𝚛𝚔
➎ 𝗙𝗶𝗻𝗮𝗹 𝗧𝗵𝗼𝘂𝗴𝗵𝘁𝘀
Personally, I believe $IO has a unique position and is likely the only distributed solution in the market today that can compete with traditional cloud computing providers.
It is the largest decentralized GPU network for on-demand compute in the world.
It is the only decentralized GPU network that supports a Ray-based solution for geo-distributed clustering of compute resources.
@ionet hence serves as an aggregation layer that taps into other decentralized networks, centralized data centers, and even consumer-grade hardware.
That enables $IO to serve compute to a multi-trillion AI industry in hyper-growth at scale and at an affordable price.
The superior economics of decentralized networks, coupled with the rising demand for cheaper compute, provides the ideal catalyst for mass public adoption.
𝑇ℎ𝑖𝑠 𝑖𝑠 𝑛𝑜𝑡 𝑓𝑖𝑛𝑎𝑛𝑐𝑖𝑎𝑙 𝑎𝑑𝑣𝑖𝑐𝑒, 𝑏𝑢𝑡 𝐷𝑌𝑂𝑅 𝑎𝑛𝑜𝑛. 🧠 ✨
@hack_vc @ionet @awscloud Linking the original post by @MTorygreen here ⤵️
x.com/MTorygreen/status/1831039118794711124
4 images on X
How the call played out · since 05 Sep 2024
Prices as of 23 Oct 2026This piece takes a view on $IO, so that move is read against the call.
Bullish on IO as a generational opportunity, the decentralized GPU network positioned to rival centralized cloud for AI compute.
−89%
Moved against the call · over 2.1 years
- At publication
- $1.50
- Now
- $0.158
- vs BTC
- −93%
- After 1 month
- +18%
- After 3 months
- +125%
- After 1 year
- −66%
- High since
- +182% 14 Dec 2024
- Low since
- −94% 06 Apr 2026
Since then
Zero has written 28 more pieces on io.net and $IO since this one.
- io.net IDE tokenomics: #1 revenue DePIN at 5.3x MC/ARRBullish call on $IO
- DeAI as crypto's endgame: compute, agents and autonomous economiesOn io.net
- Why decentralized compute solves the startup GPU cost squeezeOn io.net
- Big compute is cracking: summary of the DeAI case against centralized cloudOn io.net
Daily closes in USD from DefiLlama and Yahoo Finance. Only a bullish or bearish call in a thesis or market take is tracked; explainers, lists, maps and mentions are neutral context. Not financial advice.