This eGuide provides an easy-to-understand overview of generative AI technology – what it is, where it came from, how it works, and what it can (and can’t) do. We’ll go over the considerations and responsibilities of any enterprise implementing generative AI.
The advent of generative artificial intelligence (AI) as a consumer product has sparked excitement in virtually every industry and brought a new level of awareness of machine learning’s capabilities to the public. Now that generative AI is no longer confined to research labs and has entered the public square, it has sprouted into dozens of new applications and at least as many products. Generative AI could change how we interface with computers forever, and specific use cases are popping up constantly as Silicon Valley’s collective imagination runs wild.
It’s inevitable, however, that when a technology has this much hype, product designers, investors, and economic prognosticators alike get a little carried away in their excitement. While this is understandable, it’s not all that helpful for businesses and individuals looking to determine what this tech means for them, in the real world.
In this eGuide, we’ll provide a levelheaded, easy-to-understand overview of generative AI technology – what it is, where it came from, how it works, and what it can (and can’t) do. We’ll go over the considerations and responsibilities of any enterprise implementing generative AI, including how to access it, the risks and costs involved, and critically, the tasks at which generative AI excels. We’ll compare generative AI’s strongest use cases to problems that are still better suited to other kinds of machine learning algorithms and outline why it’s important to pick the right tool for the job. Finally, we’ll break down niche use cases industry by industry, highlighting opportunities in each field.
Your download is sponsored by Altair Engineering.
