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We all get a few chuckles when autocorrect gets something wrong, but there's a lot of time-saving and face-saving value with autocorrect. But do we trust autocorrect? Yeah. We do, even with its errors. Maybe you can use ChatGPT to improve your productivity. Ask it to a cool question and maybe get a decent answer. That's fine. After all, it's just between you and ChatGPT. But, what if you're a software company and you're leveraging these technologies? You could be putting generative AI output in front of your users.
On this episode of the Georgian Impact Podcast, it is time to talk about GenAI and trust. Angeline Yasodhara, an Applied Research Scientist at Georgian, is here to discuss the new world of GenAI.
You'll Hear About:
Who is Angelina Yasodhara?
Angeline Yasodhara is an Applied Research Scientist at Georgian, where she collaborates with companies to help accelerate their AI products. With expertise in the ethical and security implications of LLMs, she provides valuable insights into the advantages and challenges of closed vs. open-source LLMs.
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We all get a few chuckles when autocorrect gets something wrong, but there's a lot of time-saving and face-saving value with autocorrect. But do we trust autocorrect? Yeah. We do, even with its errors. Maybe you can use ChatGPT to improve your productivity. Ask it to a cool question and maybe get a decent answer. That's fine. After all, it's just between you and ChatGPT. But, what if you're a software company and you're leveraging these technologies? You could be putting generative AI output in front of your users.
On this episode of the Georgian Impact Podcast, it is time to talk about GenAI and trust. Angeline Yasodhara, an Applied Research Scientist at Georgian, is here to discuss the new world of GenAI.
You'll Hear About:
Who is Angelina Yasodhara?
Angeline Yasodhara is an Applied Research Scientist at Georgian, where she collaborates with companies to help accelerate their AI products. With expertise in the ethical and security implications of LLMs, she provides valuable insights into the advantages and challenges of closed vs. open-source LLMs.