While generative AI such as ChatGPT gets all the buzz, AI in other, typically more targeted forms, has been used for years to solve business and research challenges.
CCC invited various speakers to share their experiences with ChatGPT and other AI tools and to express their concerns and questions about this rapidly changing technology.
Data quality is an expression of a data’s usefulness and value. We often describe the things we build as knowledge systems, or a system that takes data as its input and, through a series of data process steps, extracts as much of the ‘actionable information’ in the data as is possible.
In Thomas Kuhn’s work, paradigms are characterized by “universally recognized scientific achievements that for a time provide model problems and solutions to a community of practitioners.”
The U.S. Copyright Office announced a new artificial intelligence initiative that will “examine the copyright law and policy issues raised by AI, including the scope of copyright in works generated using AI tools and the use of copyrighted materials in AI training.”
While training AI usually involves large data sets, significant AI innovation occurs today by virtue of tech companies (and others) using large datasets licensed by entities such as Getty, STM publishers, and news outlets, among others.
While there are many benefits to embracing the advancements in AI, some may argue that the technology is not ready to supplant the value of the human touch—at least not in every case.
We’re breaking down the different types of personalization used by search engines so we can recognize the benefits of applying these tools to data searches in the business environment.