Dr. Ben Goertzel suggests that it will be challenging for governments to exert control over a globally distributed AI network that relies on mining rigs. This type of network operates on a decentralized infrastructure, which makes it resistant to external control or regulation. In such a system, AI algorithms are distributed across a network of interconnected devices, which are powered by mining rigs. The decentralized nature of this network means that it is not controlled by a single entity or government, making it difficult to impose regulations or restrictions. This type of technology is still in its early stages, and the full extent of its capabilities and implications is not yet fully understood.
With artificial intelligence (AI) rapidly advancing in various sectors of the economy, there is a growing demand for computing resources to support the increasing complexity of these machine learning algorithms. As AI applications become more sophisticated, they require more computing power to process vast amounts of data and deliver accurate results. This demand has led to the development of new hardware and software technologies, such as graphics processing units (GPUs), application-specific integrated circuits (ASICs), and cloud-based computing services. The need for computing resources is likely to continue growing as AI continues to advance, and researchers and developers work to unlock new applications and use cases for this technology.
The cost of training a large-scale AI model like ChatGPT is significant, with estimates suggesting it can cost upwards of $5 million. Even running a basic demo of ChatGPT, prior to its widespread use, costs OpenAI roughly $100,000 per day. However, AI encompasses far more than just text generation. Many practical applications of AI across various industries require large neural models trained on diverse data types such as medical, financial, customer information, and geospatial data. To move beyond the current limitations of neural net AI and achieve higher levels of artificial general intelligence, even more, significant compute resources will likely be necessary. As such, the demand for computing power to support AI development and deployment is expected to continue to grow significantly in the coming years.
As the demand for computing resources to power AI continues to increase, a growing number of cryptocurrency miners are exploring the possibility of using their own computing infrastructures to support the AI revolution. Although Bitcoin mining remains a profitable business, the shifting landscape of mining other cryptocurrencies, such as Ether, has prompted mining organizations to consider alternative applications for their facilities. While the hardware requirements for high-performance computing and AI processing may differ from those of crypto mining, the cost and effort involved in setting up the physical infrastructure for hosting such equipment remain relatively consistent. As a result, miners are increasingly looking to leverage their existing facilities for other purposes, including AI.
Hut 8, a mining company, has taken the lead in repurposing its computing facilities that were previously dedicated to mining for other high-performance computing (HPC) applications, such as machine learning. Hive Blockchain has also been pursuing a similar strategy by using processor cards that can be utilized for cloud computing, AI applications, rendering for engineering applications, and scientific modeling of fluid dynamics.
It’s worth noting that using mining rigs for AI processing in decentralized blockchain-based networks is still a relatively new and experimental concept, and it remains to be seen how effective it will be in practice. While there is potential for miners to shift their resources to AI within the blockchain space, it’s important to remember that the technology is still developing and may require significant investment in research and development. Additionally, the regulatory landscape for AI and cryptocurrencies is still evolving, and there may be legal and compliance risks associated with using mining rigs for AI processing in this way. Nonetheless, the potential for decentralized AI software is an exciting development and could lead to new opportunities for both the crypto and AI industries.
Indeed, the potential for decentralization and democratization of AI through blockchain technology is a fascinating and rapidly developing area. By leveraging the power of distributed computing and decentralized control, blockchain-based AI networks have the potential to unlock a new era of innovation and collaboration in AI, while also addressing some of the challenges associated with centralized control of AI by a few large tech companies. As more and more businesses and industries turn to AI to gain a competitive advantage, the need for decentralized AI networks that can be accessed and utilized by a wide range of stakeholders will only continue to grow. The repurposing of crypto mining hardware for AI processing and the use of AI-oriented crypto networks may be one of the ways in which this vision is realized.
It is true that a globally distributed AI network spread across crypto mining rigs would be more difficult for governments or other parties to centrally control than an AI network centered in Big Tech-owned server farms. However, it is important to note that the decentralized nature of such a network could also raise concerns around transparency and accountability. Additionally, relying on crypto mining facilities for AI processing could lead to issues around resource allocation and stability, as the availability of compute resources could fluctuate depending on factors such as market conditions and energy costs. Ultimately, the ethics of such a network depend on a variety of factors, including the motivations of the parties involved and the potential risks and benefits to society as a whole.
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