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The steady trudge of artificial intelligence isn’t stopping anytime soon. From synthesizing human voice and speech to creating unique art, music, prose and poetry, generative AI is opening up new avenues for scholastic and artistic pursuits.
But what about its use for businesses? With generative AI being a vast knowledge trove, organizations stand to open up new value areas by leveraging it tactfully.
“There is no database, there is no search engine. Everything that ChatGPT generates is done from the information it was trained on,” said Ben Fauber (pictured), senior AI research scientist and distinguished technical staff at Dell Technologies Inc. “It’s like a giant matrix of information with lots of numbers in there. Those numbers mean something to the deep learning network that sits beneath ChatGPT. As it’s trained, those numbers are adjusted to better reflect the information it was provided. The goal of all these large language models, whether it be ChatGPT or other things, is to generate text.”
Fauber spoke with theCUBE industry analyst Dave Vellante at the ISC High Performance event, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed key value areas in generative AI for the enterprise landscape. (* Disclosure below.)
One key difference between today’s generative AI models and past iterations of AI is the sheer resources required by the former at every functioning stage. Behind the scenes, these large language models depend on thousands of interconnected graphical processing units to perform tasks, according to Fauber.
“Things like ChatGPT require hundreds if not thousands of GPUs behind the scenes to facilitate that type of instantaneous response across multiple users,” he explained. “At one point, I think it was said that there had been over a hundred thousand people who used it within the first few days, and then it was a million users within the first few weeks.”
All of this power has to translate, in some way, to the enterprise. To that end, the “quick-start capabilities” enabled by generative AI give businesses an edge in the areas of design, marketing and content strategy ideation — among other things, according to Fauber.
“One of the neat things on the image generation side is that there’s a lot of quick-start capabilities to these tools,” he said. “With a few lines of text, you can generate some speech, a song, an image or things of the sort. If you’re in the creative space where there’s low risk associated with trying out different mockups and not being entirely factually correct, it helps to start getting the creative juices flowing.”
The impact on the language side is even larger than that of images, as businesses tend to deal more in text and figures, according to Fauber. But, while these language models can be a clutch tool for business applications, users must always be conscious of the factual correctness of generated results.
“Peoples’ imaginations have been opened to how they can use these tools and where the opportunities reside,” he said. “I think it comes back to this notion that amazing advances are made not through people sitting back and thinking about what could be, but instead tinkering.”
Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of the ISC High Performance event:
(* Disclosure: Dell Technologies Inc. sponsored this segment of theCUBE. Neither Dell Technologies nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)
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