The O’Reilly Design Podcast: Design at Tinder, Awkward UI, and the UI Stack.
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In this week’s Design Podcast episode, I sit down with Scott Hurff, product manager and lead designer at Tinder, Inc. Hurff is the author of Designing Products People Love. In this episode, we talk about how Tinder approaches design, avoiding awkward UI, and why customer research is the most important skill for future designers.
Here are a few highlights from our conversation:
Questions of structure
At Tinder, the product team is about five people, six people. What’s interesting is that we’re trying to grow really quickly. There’s a give and take on how we divide up product design responsibilities and product management responsibilities. There is a lot of engineering talent here, and they need a lot of product to work on. It’s a matter of, how do we structure ourselves so we can give them thought-through, packaged-up, ready-to-go ideas and concepts while still hammering out the details in time.
Design as a full-contact sport
Design is such a part of the Tinder experience. It may not seem like that’s the case because it’s such a simple app, but that’s only because everything goes through this distillation process. You have to really fight for real estate and your idea. Design’s really a full-contact sport here. You have to bring in all the big guns to make your case. Sometimes these can be really long debates, but they’re good; they’re healthy. They get the ideas out on the table, and a lot of times, design really has to be put through its bases to prove itself.
The O’Reilly Hardware Podcast: Collecting, sharing, and accessing data from sensors.
In this new episode of the Hardware Podcast, David Cranor and I talk with data scientist Rachel Kalmar, formerly with Misfit Wearables and the founder and organizer of the Sensored Meetup in San Francisco. She shares insights from her work at the intersection of data, hardware, and health care.
- The need for a “data ecosystem” approach: it’s important to understand the entire stack from acquisition through storage and analysis, and where security and privacy become concerns.
- Analysis and insight as the real value in data: consumers get very little from raw data.
- Authentication for smart devices—and an experiment (let us know if your lights went out during this podcast by e-mailing firstname.lastname@example.org).
The O’Reilly Hardware Podcast: The business of building, marketing, and deploying sensors in tough environments.
In this episode of the Hardware Podcast, David Cranor and I talk with Sanjit Biswas, founder and CEO of the industrial sensor company Samsara.
- The challenges of making modern systems work with ancient industrial control systems already in the field
- The process of designing temperature sensors for heavy-duty deployments, including environmental constraints, firmware, testing, and necessary certifications
- Price sensitivity in the industrial sensor market; Samsara is one of several interesting startups that make it practical for mid-size businesses that haven’t been previously automated to add sensors
The O'Reilly Radar Podcast: Evolutionary computation, its applications in deep learning, and how it's inspired by biology.
In this week’s episode, David Beyer, principal at Amplify Partners, co-founder of Chart.io, and part of the founding team at Patients Know Best, chats with Risto Miikkulainen, professor of computer science and neuroscience at the University of Texas at Austin. They chat about evolutionary computation, its applications in deep learning, and how it’s inspired by biology.
Finding optimal solutions
We talk about evolutionary computation as a way of solving problems, discovering solutions that are optimal or as good as possible. In these complex domains like, maybe, simulated multi-legged robots that are walking in challenging conditions—a slippery slope or a field with obstacles—there are probably many different solutions that will work. If you run the evolution multiple times, you probably will discover some different solutions. There are many paths of constructing that same solution. You have a population and you have some solution components discovered here and there, so there are many different ways for evolution to run and discover roughly the same kind of a walk, where you may be using three legs to move forward and one to push you up the slope if it’s a slippery slope.
You do (relatively) reliably discover the same solutions, but also, if you run it multiple times, you will discover others. This is also a new direction or recent direction in evolutionary computation—that the standard formulation is that you are running a single run of evolution and you try to, in the end, get the optimum. Everything in the population supports finding that optimum.
The O’Reilly Design Podcast: Moving from GUI to VUIs.
Subscribe to the O’Reilly Design Podcast, our podcast exploring how experience design—and experience designers—are shaping business, the Internet of Things, and other domains.
In this week’s Design Podcast episode, I sit down with Tanya Kraljic, UX manager and principal designer at Nuance Communications. Kraljic recently spoke at OReilly’s inaugural Design Conference (you can find the complete video compilation of the event here). In this episode, we talk about the challenges of moving from graphical to voice interfaces, the voice tools ecosystem, and where she finds inspiration.
Here are a few highlights from our conversation:
We’re seeing a renewed emphasis on design at Nuance—actually, much like in the technology industry as a whole. We’ve always had great engineers who are building this very complex, very cutting-edge technology. Now, we’re augmenting that with a human-centered approach to product strategy and development, which I think we’re already seeing as accelerating innovation in our own company and, hopefully, it will also help create better and more usable solutions as voice becomes available in all these different technologies.