Fueling the AI Revolution

AI could add $2.6–4.4 trillion in annual economic benefits. Organizations’ data and its underlying foundations are the determining factors to what’s possible with generative AI... “72% of leading organizations note that managing data is already one of the top challenges preventing them from scaling AI use cases.”

Andrew Ng: “Data is food for AI.... If 80 percent of our work is data preparation, then ensuring data quality is the most critical task for a machine learning team.” Ng says that with the right data, carefully prepared, companies need orders of magnitude less to create AI systems as performant as those built by consumer internet giants that have billions of examples.

“The indexed web, holding approximately 500 trillion unique tokens, is projected to grow by a mere 50% by 2030—insufficient to support AI's exponential capabilities.”

“While public datasets remain a constraint, large technology companies have a significant advantage: access to private, proprietary datasets. Meta, for example, reportedly has access to 100 times more data than what is publicly available online. If such data can be leveraged in a compliant and ethical manner, it may allow companies like Meta to scale AI models more efficiently than their competitors.”