🚀 High Risk/Reward AI Platform
Our next pick is democratizing AI, enabling startups and developers to undertake projects that were previously beyond their reach due to the high cost of computational resources.
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The field of Artificial Intelligence (AI) is experiencing unprecedented growth.
Based on ARK’s research, AI is poised to scale to $30 trillion by 2037, becoming the first foundational technology to dwarf the internet:
However, modern AI models, especially deep learning models like GPT, have become significantly more complex.
These models involve millions, if not billions, of parameters that require immense computational power to train and deploy effectively.
The Role of GPUs in AI
Unlike Central Processing Units (CPUs), which are optimized for sequential processing, GPUs are designed to handle parallel processing tasks. This architecture makes GPUs particularly well-suited for the matrix operations and large-scale computations central to training AI models.
GPUs have become a vital component of AI development due to their capacity to perform parallel processing. This feature is critical for efficiently training sophisticated AI models, which necessitates managing massive volumes of data and executing millions of computations. GPUs can expedite these operations, lowering training time from weeks to days or hours.
The accessibility of powerful GPUs is the key to lower the barrier to entry for AI startups, enabling them to develop and deploy sophisticated AI models without needing access to supercomputers.
Our next pick is democratizing AI, enabling startups and developers to undertake projects that were previously beyond their reach due to the high cost of computational resources.
Now let’s tell you which project we are talking about and share the full investment case with you: