Odd Lots · Thursday, July 9, 2026
Tushara Fernando of Man Group explained how AI allows discretionary portfolio managers to access and synthesize diverse data types, including earnings reports, broker research, alternative data, and podcasts. AI agents can distill this information into meaningful insights, enabling PMs to asynchronously review synthesized data, such as a podcast identifying GPU scarcity and data center limitations impacting AI model training.
“So if you think about traditionally how PM like that would work. They want to look across broad set of names and they want to get access to as much data as possible for those names. So they want to look at earnings reports, they want to look at broker research, they want to look at alternative data. They want to look at podcasts. But there's only so much time in the day. There's a few hours in the day, and there's fifty names. How are they going to cover them all? How do they get to the really important insight? And what AI has allowed us to do is allowed us to access all of those different types of data, lots of different modalities, podcasts, alternative data, things like broker research reports, and synthesize them into what's actually meaningful so that a PM can asynchronously get that inside.”
“So what you could see there was a couple of things like one that there's GPU scarce see and the other thing is that it's likely that we're going to need better networking between these large data sensors in the future. And that was something that came on a podcast from a head of engineering. This isn't someone who PM would usually interact with. They don't go to the investicles, that're not somebody they often have access to. But through AI, the PM was able to have an AI agent transcribe that podcast that synthesized that data so that they could get better insight into that investment idea.”