What does AI mean to you? : Amr Ellabban speaks to Jon Krohn
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Why should humans stay in the loop when using ChatGPT?
Chat GPT makes mistakes. It will lie very confidently. So you need to have a human at least work with the results and confirm that they're accurate before you want to be publishing them publicly or making big business decisions based on Chat GPT comments. So I don't recommend that you take the human out of the loop, as it were. However What ChatGPT is great for, just like all preceding automation technologies, going back centuries to mechanized farming or you know robots appearing in factories, machines take away s piece by piece the most repetitive, boring parts of work that you don't really want to be doing anyway as a human.
Welcome to Orbit, the HG podcast series where we speak to leaders and innovators from across the software and tech ecosystem to discuss the key trends that change how we all do business. My name is Amrilaban. I'm the head of data and analytics at HG, and I'm thrilled to be joined today by John Cron, the co-founder and chief data scientist at nebula.io, author of Deep Learning Illustrated, a best-selling introduction to AI, and host of the Super Data Science Podcast, the most listened-to data science podcast in the world. We're speaking today, tucked away in a little side room at HG's 2023 digital forum here in In London where John will be giving the opening keynote tomorrow morning. John, thank you so much for joining us.
Yeah, my great pleasure, Amher. Thank you for inviting me. We've known each other for an absurdly long time.
Sixteen years we were saying.
Sixteen years, yeah. And I'd like to think we don't look that old, but thankfully people are just mostly listening to this. So they don't have to decide for themselves. So we were doing PhDs at the same time and both of us uh basically doing AI research or data science research before those were widely used terms to describe what we were doing. Although maybe your stuff, machine vision stuff, I guess people I could have been calling that AI.
They weren't even at the time, right? I didn't hear the term data scientist until I'd been working in the field for a few years post PhD. So it's uh we were we were doing it before it was cool.
Yeah. If doing PhDs in the sciences is cool. And yeah, so absolutely uh have always loved analyzing data, looking at data, building models with data, trying to make predictions with them. Uh during my PhD was doing it in genomics and brain imaging. And then afterwards worked a bit in finance myself. So was uh uh doing high frequency trading at a hedge fund using uh algorithm driven uh strategies, subsecond kind of trading strategies. And I then uh yeah, worked briefly in marketing, automating digital advertising. Very common data science application. The most common data science application. We'll be hearing
about
it tomorrow at the forum. Yeah, I bet. And then found my l my a love for tech startups. So for the last nine years have been working in tech startups, two of them.
Who are the hosts and what are their professional backgrounds?
So one called Untapped was acquired in twenty twenty. And now I have the joy of being the co founder of the startup nebula, and I'm working with the founder of the previous company. as and our third co founder is the CEO of the holding company that bought the previous company that I was working at. So Really close group of founders. Uh we get to have intellectual property continuity and have been able to get to market relatively quickly uh into private beta with uh with our first product just in the last few months. That's very cool. Yeah. What does the product do? So it is for finding people with natural language. So there are lots of tools out there for finding talent that you'd like to hire or Sales leads, all of them are keyword based.
But we use natural language processing algorithms, which are AI, I guess. Everything it seems to be AI. Whatever AI is, NLP seems to be squarely in the middle of it, especially with recent applications that we've seen. And I know that we're gonna be talking about that later on the show. But basically with our platform, you can use these really high powered, really nuanced natural language processing algorithms that understand
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Chapters
8 chapters
1
Why should humans stay in the loop when using ChatGPT?
0:00–3:03
2
Who are the hosts and what are their professional backgrounds?
3:03–6:04
3
How does Nebula use natural‑language processing to improve talent and sales prospect search?
6:04–10:10
4
What are the core sub‑fields of AI beyond the buzzword hype?
10:10–13:29
5
How did AlexNet revolutionize machine learning in 2012?
13:29–17:27
6
Can we trust AI for high‑stakes decisions in healthcare, finance, and security?
17:27–20:32
7
What is the human bias against machine mistakes and how does it affect AI adoption?
20:32–24:51
8
What breakthroughs are expected in AI over the next decade and beyond?
24:51–27:34
Speakers
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