By brennanhm on Skatehive
Demand for AI has been skyrocketing ever since ChatGPT debuted in late 2022. In fact, the demand has been so great that we are facing several challenges... In addition to boatloads of additional energy, AI also requires vast amounts of GPUs (Graphics Processing Units) to train AI models and make inference calls on them. Blockchain technology, and the underlying token incentives, can be harnessed to aggregate and coordinate these scattered resources. Training vs. Inference Training an AI model requires processing vast amounts of data over a span of weeks or months. Inference, on the other hand, is simply querying an existing model, like you would do through ChatGPT or Grok. The massive AI data centers (of xAI, Google, or Meta) that house hundreds of thousands of GPUs are typically used to generate the AI models. A decentralized network of GPUs is often more efficient at handling the inference requests, however, compared to the GPUs housed in these big tech data centers. And there are pl