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Tech Transforms podcast: A reporter’s take on AI, data privacy, ChatGPT, and TikTok

Dynatrace

In a special two-episode podcast, Krishan shares his thoughts on artificial intelligence (AI), specifically around two wildly popular, yet extremely contentious apps: ChatGPT and TikTok. As a result, he has access to a variety of insights and opinions on new and emerging technologies.

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Generative AI in the Enterprise

O'Reilly

Even with cloud-based foundation models like GPT-4, which eliminate the need to develop your own model or provide your own infrastructure, fine-tuning a model for any particular use case is still a major undertaking. (We’ll say more about this later.) We’ve never seen adoption proceed so quickly.

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Bringing the Magic of Amazon AI and Alexa to Apps on AWS.

All Things Distributed

Today, I want to focus on helping app developers who have chosen to develop their apps on AWS and have in the past developed some of the seminal apps of our times on AWS, such as Netflix, AirBnB, or Pinterest or created internet connected devices powered by AWS such as Alexa and Dropcam. Summing it all up.

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I Actually Chatted with ChatGPT

O'Reilly

Overly-agreeable artificial tone : Lastly, it’s still ChatGPT under the hood, so all the regular limitations of ChatGPT apply here. Most notably, ChatGPT is tuned to be overly-friendly and overly-agreeable (sounding like a customer service agent) so it will simply go along with whatever you assert.

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Real-Real-World Programming with ChatGPT

O'Reilly

And since ChatGPT is trained on text from the internet, if that text doesn’t contain high-quality information about a topic, then ChatGPT won’t work well for it either. I wanted to verify this for myself, so I went back to “old-school” searching the web, reading docs, and looking for example code online.