From: mk_thisisit
The development and advancement of artificial intelligence heavily rely on significant computing power, which is essential for training sophisticated AI models and fostering research [00:49:37].
Current Landscape of Computing Power in AI
To create new artificial intelligence tools, models must be trained on vast amounts of data, requiring substantial computational resources [00:49:38]. The sheer scale of computing needed is enormous [00:50:00]. For instance, Meta aims to possess 600,000 equivalents of H1 cards by the end of the year [00:50:14]. In contrast, Poland’s strongest current cluster has only 100 such cards [00:50:27]. Other countries, including Switzerland, France, and Great Britain, are announcing programs for tens of thousands of these computational units [00:50:35].
The current high demand for computing power is partly attributed to the early stage of artificial intelligence development, where optimal learning algorithms are not yet fully achieved [00:52:53]. To enable artificial intelligence to learn at a level comparable to a single human brain, hundreds of millions of zlotys are needed for computing centers [00:53:10].
Expanding Computing Capabilities in Poland
There is a strategic plan to significantly increase Poland’s computing power, aiming for a hundredfold increase [00:50:46]. This expansion would serve multiple purposes:
- Academic Research It would provide academic institutions with the capacity to conduct world-level research, fostering competent specialists [00:50:56].
- Entrepreneurial Support The increased computing power would be available for entrepreneurs, forming a support program that is both substantive and computational [00:51:03]. This shared resource would be more efficient than individual companies acquiring their own equipment [00:51:15].
Acquiring the necessary hardware, such as Nvidia H1 cards, involves waiting periods due to high demand, but this is considered a minor issue given the longer timeline for building and organizing a cluster [00:51:49]. While Nvidia is the most popular supplier, other solutions like TPUs and Amazon’s accelerators will also be considered to ensure optimal computing power [00:52:22].
Future Implications
The integration and regulation of data, along with its use, are becoming significant topics for countries and groups of countries [00:54:19]. The way private companies operate will heavily influence the requirements set by nations, as this represents a fundamental shift in the world’s operational network [00:54:35]. The long-term goal is to make artificial intelligence widely accessible, reducing differences across all areas of life and allowing humanity to coexist and integrate with the technology [01:00:39].
The need for high computing power today is a consequence of the current stage of artificial intelligence development [00:52:53]. In the future, as learning algorithms become more optimal, the reliance on massive computing power for certain tasks might change, potentially accelerating artificial intelligence development even further without as much national investment [00:53:41].