The debate about the performance of graphics processing has been ongoing for a while now. However, the real key to success in the future lies in mastering where data is located. As global data creation continues to explode, companies that fail to adapt to the next level of innovation will be left behind. According to recent estimates, global data creation is expected to reach 200 Zettabytes by the end of 2025, which is more than all previous human output combined.
This massive increase in data creation has significant implications for the field of artificial intelligence (AI). Research teams have recently developed the first publicly published language model with trillion parameters, which requires enormous amounts of data to train. However, without adequate storage pipelines, even the fastest processors can become idle due to frustration. The central cloud memory has become a significant bottleneck, with exit fees increasing costs by up to 80% and slowing down data transmissions.
Decentralized memory networks offer a solution to this problem by sharpening data across independent nodes and providing cryptographic evidence of replication. This approach not only reduces costs but also increases the speed of data transmission. Moreover, regulations such as the EU’s AI Act, which came into effect on August 2, require model providers to document all training data, making decentralized networks a more attractive option.
The need for transparent examination paths that fulfill impending disclosure mandates is crucial, especially when it comes to merchant data. Decentralized storage networks can provide a more secure and compliant solution, making them an essential component of the AI ecosystem. The latest MLPerF memory V2.0 benchmarks demonstrate the burden of centralized silos, with even a super cluster of 100,000 GPU taking 4.4 seconds to perform mathematical operations while waiting for hard drives.
In conclusion, the future of AI depends on the development of decentralized storage networks that can handle the increasing volumes of data. Companies that fail to prioritize storage and decentralization will be left behind, and those that do will be the ones to trigger AI’s next breakthrough. As Kai Wawrzinek, co-founder of Impossible Cloud and Impossible Cloud Network, notes, “The storage is no longer a background benefit. It is the only substrate on which the AI of tomorrow can run legally and physically.” For more information, visit https://crypto.news/storage-not-silicon-will-trigger-ais-next-breakthrough/
