Cryptocurrency miners are beginning to lead the next stage of AI

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As artificial intelligence (AI) rapidly works its complex magic on one sector of the economy after another, there is an increasingly pressing need for compute resources to power all this machine intelligence.

Training a model like ChatGPT costs more than $5 million, and running the early ChatGPT demo, even before usage increased to its current level, costs OpenAI around $100,000 per day. And AI is more than just text generation; applying AI to practical problems across multiple industries requires similar large neural models trained on a diversity of data types — medical, financial, customer information, geospatial and so forth. Moving beyond the limitations of current neural net AI toward systems with higher levels of artificial general intelligence will almost surely be even more compute intensive.

It’s only natural that a small but increasing number of crypto miners are now looking at how to leverage their own compute infrastructures to help push forward the AI revolution.

Bitcoin (BTC) mining remains a lucrative business. Mining other cryptocurrencies can still make money as well, but it is a rapidly shifting landscape. Ether (ETH) miners, for instance, took a major hit late last year when the Ethereum network shifted from proof-of-work to proof-of-stake.

The economic and technical situation in the crypto space over the last two years has driven an increasing number of crypto mining organizations to explore the potential of leveraging their facilities for other purposes, such as high-performance computing and, in particular, AI.

The specific computing hardware needed for high-performance computing (HPC) or AI processing is often different from what’s optimal for crypto mining. But buying servers is generally not the most difficult part of setting up a mining farm. Getting the electrical power and cooling and security and other physical infrastructure in place is a major cost and effort, and all this remains roughly the same whether one is hosting RAM-light GPUs appropriate for ETH mining or RAM-heavy GPUS appropriate for AI model learning.

Mining firm Hut 8 has led the way, leveraging its formerly mining-dedicated compute facilities for machine learning and other HPC applications. Hive Blockchain has been doing the same thing for some time, filling its servers with processor cards that “can be used for cloud computing and AI applications, and rendering for engineering applications, in addition to scientific modelling of fluid dynamics.”

Perhaps most interesting is the potential for miners to shift their compute resources to AI in a way that remains fully within the blockchain space — by using them to run AI processes that are hosted in decentralized blockchain-based networks. This opportunity is provided by a number of AI projects associated with 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 done well in the first part of 2023, as the market has come to understand the potential for decentralized AI software.

It’s been clear since before Bitcoin’s white paper that the fusion of distributed computing, strong encryption and decentralized control has broad applications beyond the financial. This is why we have blockchain projects in areas spanning nearly all vertical markets — medicine, supply chain, gaming, robotics and so on. As each of these business domains becomes dominated by AI, decentralizing the software and hardware underlying AI will be a critical aspect of decentralizing the global economy. Repurposing of a portion of crypto mining hardware to running AI processing, some of which is wrapped in AI-oriented crypto networks, will increasingly form part of the story.

If a non-trivial portion of global AI processing ends up being done on crypto mining facilities, this could have implications beyond finance. Crypto mining rigs are based in diverse legal jurisdictions and 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 centrally control than an AI network centered in Big Tech-owned server farms (the current default for AI). Whether this is good or bad AI ethics-wise depends on your estimate of the character of Big Tech and big government.

Ben Goertzel is the CEO and founder of SingularityNET and chairman of the Artificial General Intelligence Society. He has worked as a research scientist at a number of organizations, most notably as the chief scientist at Hanson Robotics, where he co-developed Sophia. He served previously as a director of research at the Machine Intelligence Research Institute, as the chief scientist and chairman of AI software company Novamente and as chairman of the OpenCog Foundation. He graduated from Temple University with a Ph.D. in mathematics.

This article is for general information purposes and is not intended to be and should not be taken as legal or investment advice. The views, thoughts and opinions expressed here are the author’s alone and do not necessarily reflect or represent the views and opinions of Cointelegraph.