- Exoskeletons Must be Covered by Health Insurance (VICE) — A medical review board ruled that a health insurance provider in the United States is obligated to provide coverage and reimbursement for a $69,500 ReWalk robotic exoskeleton, in what could be a major turning point for people with spinal cord injuries. (via Robohub)
- New Models for the Company of the 21st Century (Simone Brunozzi) — large companies often get displaced by new entrants, failing to innovate and/or adapt to new technologies. Y-Combinator can be seen as a new type of company, where innovation is brought in as an entrepreneurial experiment, largely for seed-stage ideas; Google’s Alphabet, on the other hand, tries to stimulate innovation and risk by dividing a large company into smaller pieces and reassigning ownership and responsibilities to different CEOs.
- Zephyr — Linux Foundation’s IoT open source OS project. tbh, I don’t see people complaining about operating systems. Integrating all these devices (and having the sensors actually usefully capturing what you want) seems the bigger problem. We already have fragmentation (is it a Samsung home or a Nest home?), and as more Big Swinging Click companies enter the world of smarter things, this will only get worse before it gets better.
- A Hands-On Approach on Botnets for a Learning Purpose — these researchers are working on open source botnet software for researchers to bang on. (So you don’t need to attract the interest of actual botnet operators while you learn what you’re doing.)
FEATURED STORY
Open source lessons for synthetic biology
Open source biology is taking off, but will it ever provide enough income to build a business around? When we look at the history of open source software and the work of Tesla, Google, and Red Hat, it seems inevitable. Read more...
Four short links: 19 February 2016
Exoskeletons Insured, Companies Rethought, IoT OS Launched, and BotNets Open Sourced
Scott Hurff on designing at Tinder
The O’Reilly Design Podcast: Design at Tinder, Awkward UI, and the UI Stack.
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: Stitcher, TuneIn, iTunes, SoundCloud, RSS.
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.
Rachel Kalmar on data ecosystems
The O’Reilly Hardware Podcast: Collecting, sharing, and accessing data from sensors.
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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.
Discussion points:
- 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 hardware@oreilly.com).
Sanjit Biswas on industrial sensors
The O’Reilly Hardware Podcast: The business of building, marketing, and deploying sensors in tough environments.
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In this episode of the Hardware Podcast, David Cranor and I talk with Sanjit Biswas, founder and CEO of the industrial sensor company Samsara.
Discussion points:
- 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
Risto Miikkulainen on evolutionary computation and making robots think for themselves
The O'Reilly Radar Podcast: Evolutionary computation, its applications in deep learning, and how it's inspired by biology.
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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.
Metadata services can lead to performance and organizational improvements
The O’Reilly Data Show podcast: Joe Hellerstein on data wrangling, distributed systems, and metadata services.
Subscribe to the O’Reilly Data Show Podcast to explore the opportunities and techniques driving big data and data science: Stitcher, TuneIn, iTunes, SoundCloud, RSS.
In this episode of the O’Reilly Data Show, I spoke with one of the most popular speakers at Strata+Hadoop World: ?Joe Hellerstein, professor of Computer Science at UC Berkeley and co-founder/CSO of Trifacta. We talked about his past and current academic research (which spans HCI, databases, and systems), data wrangling, large-scale distributed systems, and his recent work on metadata services.
Data wrangling and preparation
The most interactive tasks that people do with data are essentially data wrangling. You’re changing the form of the data, you’re changing the content of the data, and at the same time you’re trying to evaluate the quality of the data and see if you’re making it the way you want it. … It’s really actually the most immersive interaction that people do with data and it’s very interesting.
