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One of the biggest hurdles was the sheer cost of doing AI research and development. Training large language models (LLMs), for instance, requires massive computational power, specialized hardware, and huge datasets. Only the biggest companies could afford these resources. On top of that, there was a significant knowledge gap. AI research is incredibly complex, and it requires experts with advanced degrees and specialized skills. This created a bottleneck, as the talent pool was limited and concentrated within a few elite institutions and companies. Finally, the closed-source nature of many AI projects made it difficult for others to build upon existing work. When models and code are kept secret, it prevents collaboration, slows down innovation, and creates a fragmented ecosystem. So, basically, Big Tech's monopoly was built on money, expertise, and secrecy. It was a tough nut to crack, but open source is proving to be up to the challenge.
