Post by account_disabled on Dec 26, 2023 22:53:04 GMT -5
Massive investments in computing infrastructure only partially explain why A.I. Most of the big breakthroughs in the field have come from a select group of big tech companies, including Amazon, Google, and Microsoft. What sets tech giants apart from many other businesses seeking to gain an advantage from artificial intelligence is the vast amounts of data they collect as platform operators. Amazon alone processes millions of transactions on its platform every month. All this big data is a rich strategic resource that can be used to develop and train complex machine learning algorithms, but for most enterprises, it is a resource that is out of reach and better-performing artificial intelligence and machine learning models, but many companies must work with smaller data sets. For smaller companies and those in traditional industries like healthcare, manufacturing, or construction, a lack of data is the biggest barrier to venturing into artificial intelligence.
The digital divide between big data and small data organizations is a serious problem due to self-reinforcing data network effects. More data leads to better AI tools, which helps attract more to generate more data. customers, etc. AI competitive advantage, while small and medium-sized organizations struggle to keep up. Get the latest news on AI and data leadership with monthly insights into how AI is impacting Job Function Email List your organization and what it means for your company and customers. What is your email? Sign Up Privacy Policy The idea of multiple small-scale companies pooling their data in a central, commonly controlled repository has been around for some time, but concerns about data privacy may have stymied such a move.
Federated machine learning is a recent innovation that overcomes this problem through privacy-preserving collaborative artificial intelligence using decentralized data. could be a game changer, addressing the digital divide between companies with and without big data and enabling a larger portion of the economy to reap the benefits of artificial intelligence. Not only does this technology sound promising in theory, it's already being successfully implemented in industry, which we'll detail below. But first, we'll explain how it works. Small Data and Federated Machine.
The digital divide between big data and small data organizations is a serious problem due to self-reinforcing data network effects. More data leads to better AI tools, which helps attract more to generate more data. customers, etc. AI competitive advantage, while small and medium-sized organizations struggle to keep up. Get the latest news on AI and data leadership with monthly insights into how AI is impacting Job Function Email List your organization and what it means for your company and customers. What is your email? Sign Up Privacy Policy The idea of multiple small-scale companies pooling their data in a central, commonly controlled repository has been around for some time, but concerns about data privacy may have stymied such a move.
Federated machine learning is a recent innovation that overcomes this problem through privacy-preserving collaborative artificial intelligence using decentralized data. could be a game changer, addressing the digital divide between companies with and without big data and enabling a larger portion of the economy to reap the benefits of artificial intelligence. Not only does this technology sound promising in theory, it's already being successfully implemented in industry, which we'll detail below. But first, we'll explain how it works. Small Data and Federated Machine.