Elise Carmichael is the CTO of Lakeside Software, where she oversees the design and delivery of its digital employee experience platform. Read Elise Carmichael's full executive profile here.
As the CTO of a software company, I, like many of my peers, have found myself engrossed by generative large language models ever since OpenAI's release of the GPT-3 model in 2020.
Yes, I went down the same rabbit hole as everyone else. While playing with any shiny, new object in the tech world, though, we owe it to our collective contributions to innovation to ask,"What can I do with this?"of executives revealed,"71 percent plan to implement their first generative AI solution within two years" . There hasn’t been this much buzz since the digital transformations and huge cloud migrations of a decade ago.
Why is this step so crucial? At present, large language models rely primarily on information from the internet . Much of that new data will be created by large language models. Bots feeding bots feeding bots feels like a bad cycle. Because these models are only as good as their data, they inherently have biases and cases of misinformation.
You don’t have to go all in at once, nor should you. A pilot use case or two is essential. And remember, although ChatGPT is impressive, it may not be the best fit in all scenarios.
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