Pausing to think about scikit-learn & OpenAI o1

"So at Assembly, we're building industry-leading speech AI models for various tasks like speech to text, streaming speech to text, speech understanding, to help developers easily convert voice data into super accurate text."

"There's so much voice data being created on the internet now—Podcasts, videos, phone calls, voice messages, audio books, virtual meetings. We can now transform and understand all of this voice and audio data in ways that were not even possible a year, 18 months ago."

"We bundle all those things into a super simple API with really great docs that developers can just sign up for free to start, use the API, build into their apps."

"You know, I think that gets lost with all the hype on AI and particularly Gen AI these days. There's still so much data science going on. I would suggest that just core everyday data science is still by far bigger in terms of being present in the number of organizations."

"Fly gives you a lot of flexibility on multiple fronts... one of my favorite partners is Tigris... such a good thing to know when it comes to object storage... it's incredibly easy to use and set up."

"They have in their prompts that they train the model on, which is like now give the answer to the user, right? Whatever that special token is, which, you know, we don't have a ton of information about."

"One of them is that it still has a cutoff date on knowledge, which is tied back to October of 2023. So, you know, it's almost a year since it has access to that knowledge."

"And unlike some of the other models before it, which had Internet access to go out and kind of make up for that and get some more current information to throw into the model that was trained up until the cutoff date, this one does not have the ability to browse the Internet."

"And I find myself certainly feeling very comfortable and gravitating, but I would actually conclude by saying in my own experience working at some large companies, you know, large corporations and having a lot of friends and colleagues that I talked to at other big companies, they may use proprietary models to some degree, but nobody's betting their business."

What is "Pausing to think about scikit-learn & OpenAI o1" about?

In this episode, the hosts discuss key developments in AI, focusing on scikit-learn's recent seed funding and OpenAI's introduction of the 'o1' model, which pauses to think during complex tasks. They explore the implications of these technologies for data science, emphasizing the importance of both generative AI and foundational data science processes. Dylan Fox, CEO of Assembly AI, shares insights on using voice data and the growing demand for AI models that support audio processing. The hosts highlight the trend toward hybrid AI systems and the need for transparency in AI model marketing. Additionally, they address the trust issues surrounding proprietary versus open-source models in critical applications.

What are the key takeaways from "Pausing to think about scikit-learn & OpenAI o1"?

Assembly AI is at the forefront of developing advanced speech AI models to convert voice data into actionable insights. There is a significant trend in leveraging voice data across industries, highlighting the demand for custom tools to extract insights. The importance of combining traditional and modern AI processes is critical for effective voice and audio processing.

Which podcast is this episode from?

"Pausing to think about scikit-learn & OpenAI o1" is an episode from Practical AI: Machine Learning, Data Science, LLM.