Zach Hanson is an expert in artificial intelligence and machine learning product management, with experience developing AI solutions for Fortune 500 companies including IBM, Brightcove, Capital One, and Wells Fargo. He holds degrees from the College of Charleston and Johns Hopkins University. In today's episode, We discussed power of AI, Zach discusses how it aids in tasks like content parsing, summarizing, and producing video trailers. He also explores the interconnection of different AI models, and the rise of content generation through freeform speech. We discusses how AI technologies, like ChatGPT and GitHub co-pilot, can streamline creative content creation and refine stories or code. Finally, for those looking to enter the AI product management or creation space, Zach advises building something to understand core product fundamentals and getting comfortable with data. Tune in to hear Zach Hanson's insights and experiences in building Inworld AI and how you can apply these lessons to your own product.

Find the full transcript at: https://www.aiproductcreators.com/

Where to find Zach Hanson:

• LinkedIn: https://www.linkedin.com/in/zachary-hanson-a1a761a3/ 

Where to find Dhaval:

• LinkedIn: https://www.linkedin.com/in/dhavalbhatt 



Transcript:-

Dhaval:
Hey, Zach, tell us what you've been up to.

Zach:
So everybody, I'm Zach Hanson. Dhaval it's great to see you again. You and I used to work together in a, past life in the AI field but What I've been up to lately is pushing for AI innovation within video, specifically at Brightcove, which is a great company, and working around how we actually build out and better experiences for our customers in the video space.

Dhaval:
Oh, wow. That's like the most cutting edge space in AI right now. The video and AI generated videos and all of that as we speak in April of 2023. What specifically is Brightcove's mission? And, yeah, if you could share a little bit about the, what is the product, what pain is it solving, and what are your customers, who are your customers? And then a little bit about where you are in the product space, like in the journey. Like, are you a startup? Are you, have you already found the product market fit? Are you enterprise? So yeah, any of that? So, a lot of questions, but just trying to understand the product story.

Zach:
So it is interesting, right? So we're a very unique company. So Brightcove's goal, to answer your first question, has become the most trusted company in streaming. So that's our goal, right? That's the big headline. That's what we're pushing and we kind of run the line of being a media company and an enterprise company. So from a competitive landscape perspective just to frame where we're at, would be the Vimeos of the world, Kaltura and some other companies that are providing OTT services to brands around the world. And Brightcove has actually been in the game for over 15 years. So to answer another piece of your question is we're a publicly traded company. We've been around for over 15 years and we've been providing these services for live streaming, for video on demand OTT for years, and it's pretty amazing. So we're one of the biggest little companies you might not have heard of. But with that comes a lot of responsibility around data because we actually ingest around one to two petabytes of video data every month. So we have an absolutely enormous catalog and data warehouse of videos, audio, all sorts of content that is being leveraged by our customers. Now, to answer one of the other questions rolled in there about our customers and some of the ones we can talk about, we help deliver video, great quality video with our encoders for the Olympics the year ago. Wow. Yeah, we've done that. We work with south by Southwest. So folks, if you've watched conference video from there, that's Brightcove under the hood masterclass for instance. So we have a huge list of really amazing clients who are doing All sorts of different things with video. And that's what we're trying to enable. Now, the other piece of your question, where are we at in the product journey? Are we a startup? Are we a mature company? And I would say from the delivery of video, we're very much a mature company. But when we start to think about machine learning and leveraging Models that are out there building our own models, we're really much more in that startup phase where we're trying to find the appropriate product market fit for the different types of models we might build or leverage the really immense amount of data we have to train models and do some really cool things.

Dhaval: 
Wow. Thank you. Thank you so much for answering all those questions. I threw a barrage of questions at you. Wanna dive in a little bit on your last answer here on the topic of being new to AI ml. And what I wanna understand, Zach, is what is the customer trying to do when they want to use the AI ML capabilities for Brightcove? What is the thing that's going on in their head when they are like trying to use your specifically AI ML features?

Zach:
So this is where it's also like an interesting story because there's a lot of stuff that we're focused on from a machine learning perspective, kind of under the hood, things that our customers might not know is being powered by machine learning. So some of that has to do with encoding and how we get the video to the actual end user in a very efficient manner or in an efficient manner. As far as doing CDN optimization and making sure that the ultimate end user, which is our customer's customer, whoever's watching video. Has a great experience and that's where the bulk of our effort's been. But when you think about pain points, as we think about becoming more of a media company, when we think about enabling producers of content to be able to do some really cool things there's really this kind of crawl, walk, run approach. One is when somebody uploads content to our catalog or their catalog through Brightcove, there are sorts of metadata that should be tagged in those videos. Oftentimes people are having to do that manually time stamping stuff or putting this as a certain piece of a sub catalog within their overall experience. So we're trying to do some automation through their of automating tag management to suggest to our customers tags they might need in order to ease the burden of some of the metadata management, but then you go up the chain to content itself, the video, and we start to think about object recognition and video. We start to think about segmenting video. So you can easily cut and pull out specific elements of a video. For instance, if you were watching a soccer match or football match I grew up in the United States, so I'm a little bit more used to American football and I've become a bit more of a fan of the universal football in the years, in the past few years. But you might have an hour and a half long game and only have two goals or none. So the ability to be able to search through a video and find that really intense moment where somebody actually scores a goal, be able to rip that out really quickly and repurpose that content for marketing is very powerful. And there's a lot of startups actually playing in that space and then you have the bigger players like ourselves, Brightcove. Then you also trying to play around with segmentation of video. So it really runs the whole gamut where we've been focused mostly on backend support, leveraging ml. All the way to that kind of front facing customer content production type of use case.

Dhaval: 
Yeah, I, that's amazing. You have, I can think of so many use cases. I was at a photo shoot video shoot event this weekend where I was hosting it, and we have like terabytes of video content that we created and now I want to create recap videos for that event. And I can imagine being able to feed something like that to your platform. Is that, am I getting it right? Would that be a potential use case? Is that how you It is parts out valuable clips.

Zach:
Exactly. And that is part of a potential use case that we're exploring. But this is where it goes back to being in that kind of pseudo startup space. Like with all the data we have. With the great customers that we have, there's a lot of opportunity there and we're still in that feeling out phase of saying, what are those pain points to your other question. And like the use case you just gave, that might be something at the top of mind for a lot of our customers. And that's where we're just starting to put the feelers out and understand how we might be able to build some of these things out and make sure we have the right product market fit before rolling something out to our broader customer base.

Dhaval:
Yeah, that's very interesting. Just like thinking for like content creators like myself. That event is an example of a use case. This podcast is an example of a use case, parsing out insights from this video, insights, and then publishing them. And then for courses that I create on product management and artificial intelligence, it's the same thing. I can imagine being able to give you a whole course and create a trailer for that. So there are a million use cases that you can be going after. Are you thin