Cryptocurrency miners are leading the next level of AI
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As artificial intelligence (AI) rapidly unleashes its complex magic on one economic sector after another, there is an increasingly pressing need for the computing resources to power all this machine intelligence.
A model like ChatGPT costs more than $5 million to train, and running the early ChatGPT demo costs OpenAI about $100,000 a day even before usage has ramped up to current levels. And AI is more than just text generation; Applying AI to practical problems across multiple industries requires similarly sized neural models trained on a variety of data types — medical, financial, customer information, geospatial, and so on. Overcoming the limitations of current AI with neural networks towards systems with higher levels of artificial general intelligence will almost certainly be even more computationally intensive.
It’s only natural that a small but increasing number of crypto miners are now considering how to use their own computing infrastructures to fuel the AI revolution.
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Bitcoin (BTC) mining remains a lucrative business. Mining other cryptocurrencies can still make money, but it’s a rapidly changing landscape. Ether (ETH) miners, for example, suffered a major blow late last year when the Ethereum network switched from proof-of-work to proof-of-stake.
The economic and technical situation in the crypto space over the past two years has prompted a growing number of crypto mining organizations to explore the potential of using their facilities for other purposes, such as mining. g. high-performance computing and in particular AI.
The specific computing hardware required for high performance computing (HPC) or AI processing is often different than what is optimal for crypto mining. But buying servers is generally not the hardest part of building a mining farm. Providing power and cooling, as well as security and other physical infrastructure, comes at a high cost and hassle, and all of this stays about the same whether you’re hosting RAM-light GPUs suitable for ETH mining or RAM -heavy GPUS suitable for learning AI models.
Mining company Hut 8 has led the way, leveraging its formerly mining computing facilities for machine learning and other HPC applications. Hive Blockchain has been doing the same thing for a while, populating its servers with processor cards that “can be used in addition to scientific fluid dynamics modeling for cloud computing and AI applications and rendering for engineering applications.”
Mining company Hut 8 stock price, February 2022 to February 2023. Source: TradingView
Perhaps most interesting is the potential for miners to offload their computing resources to AI in a way that stays entirely in the blockchain space — by using it to run AI processes hosted on decentralized blockchain-based networks. This possibility is provided by a number of AI projects connected to their own altcoins such as Fetch.ai (FET), Ocean (OCEAN), Matrix AI Network (MAN), Cortex (CTXC) and my own project, SingularityNET (AGIX ). and its various ecosystem projects such as NuNet (NTX) and the new ledgerless blockchain HyperCycle. AI-related altcoins have performed well in the first half of 2023 as the market understands the potential for decentralized AI software.
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Even before Bitcoin’s white paper, it was clear that the merging of distributed computing, strong encryption, and decentralized control had far-reaching applications beyond finance. Because of this, we have blockchain projects in areas covering almost every vertical market – medical, supply chain, gaming, robotics, and so on. As each of these business areas is dominated by AI, the decentralization of the software and hardware underlying AI will be a crucial aspect of the decentralization of the global economy. The repurposing of some crypto mining hardware to perform AI processing, some embedded in AI-centric crypto networks, will increasingly be part of the story.
If a non-trivial chunk of global AI processing is performed in crypto mining rigs, it could have ramifications beyond finance. Crypto mining rigs are located in different jurisdictions and are owned by a variety of different parties. A globally distributed AI network spread across crypto mining rigs would be dramatically more difficult for governments or other parties to control centrally than an AI network centered on Big Tech server farms (the current standard for AI). Whether this is good or bad in terms of AI ethics depends on your assessment of the character of big tech and big government.
Ben Goertzel is CEO and Founder of SingularityNET and Chair of the Artificial General Intelligence Society. He has worked as a research scientist at a number of organizations, most notably as chief scientist at Hanson Robotics, where he helped develop Sophia. Previously, he was research director at the Machine Intelligence Research Institute, senior scientist and chairman of the AI software company Novamente, and chairman of the OpenCog Foundation. He graduated from Temple University with a Ph.D. in mathematics.
This article is for general informational purposes and should not be construed as legal or investment advice. The views, thoughts, and opinions expressed herein are solely those of the author and do not necessarily reflect or represent the views and opinions of Cointelegraph.
