The O’Reilly Solid Podcast: A discussion about critical issues for hardware startups.
Subscribe to the O’Reilly Solid Podcast for insight and analysis about the Internet of Things and the worlds of hardware, software, and manufacturing.
Hardware is getting more accessible, which makes hardware startups more appealing. A small team can develop a viable prototype for a simple product on a few hundred thousand dollars, and even tricky problems like autonomous cars are within the reach of startups.
Incubators and accelerators like Highway1, Lemnos, and HAX have played an important role in making hardware accessible; they help their portfolio companies work through the tricky engineering, manufacturing, and marketing problems that software startups don’t have to deal with.
In our new episode of the Solid Podcast, David Cranor and I have a wide-ranging discussion with Ben Einstein, co-founder and managing director of Bolt, one of the leading hardware startup accelerators.
Einstein, who spoke at Solid 2015 in California, talks about the importance of hardware marketing and customer development, including branding, crowdfunding, and virality (which is “much more possible with hardware now than it was 10 years ago,” he says). Read more…
The O'Reilly Radar Podcast: Suzanne Pellican on the ups and downs of Intuit's journey to become a design-driven organization.
Subscribe to the O’Reilly Radar Podcast to track the technologies and people that will shape our world in the years to come.
In this week’s episode, O’Reilly’s Mary Treseler chats with Suzanne Pellican, VP and executive creative director at Intuit, about three core principles of design thinking and about Intuit’s journey to become a design-driven organization.
Pellican also will be speaking at our upcoming O’Reilly Design Conference about creating a culture based on design thinking, experimentation, and risk taking. You can find out more at the event website.
Here are a few highlights from their chat:
Design thinking is the practice of problem solving, and to me, that is based on those three core principles that I spoke about: deep customer empathy, going broad to go narrow, and rapidly experimenting with your customer. That’s the actual skill set and the tools and the mindset that you have.
Design thinking is absolutely experiential, and I think the first mistake that we made when we started rolling this out eight years ago was, if you’re going to change the way people work day to day, that’s going to take a long time. You can’t just ask people to do it and expect them to change. You have to give them ample opportunities to practice so that they can then understand it and make it their own.
The O'Reilly Data Show Podcast: Mike Cafarella on the early days of Hadoop/HBase and progress in structured data extraction.
Subscribe to the O’Reilly Data Show Podcast to explore the opportunities and techniques driving big data and data science.
February 2016 marks the 10th anniversary of Hadoop — at a point in time when many IT organizations actively use Hadoop, and/or one of the open source, big data projects that originated after, and in some cases, depend on it.
During the latest episode of the O’Reilly Data Show Podcast, I had an extended conversation with Mike Cafarella, assistant professor of computer science at the University of Michigan. Along with Strata + Hadoop World program chair Doug Cutting, Cafarella is the co-founder of both Hadoop and Nutch. In addition, Cafarella was the first contributor to HBase.
We talked about the origins of Nutch, Hadoop (HDFS, MapReduce), HBase, and his decision to pursue an academic career and step away from these projects. Cafarella’s pioneering contributions to open source search and distributed systems fits neatly with his work in information extraction. We discussed a new startup he recently co-founded, ClearCutAnalytics, to commercialize a highly regarded academic project for structured data extraction (full disclosure: I’m an advisor to ClearCutAnalytics). As I noted in a previous post, information extraction (from a variety of data types and sources) is an exciting area that will lead to the discovery of new features (i.e., variables) that may end up improving many existing machine learning systems. Read more…
Digital content, the Internet, and data science have changed the music industry.
Download our new free report “Music Science: How Data and Digital Content are Changing Music,” by Alistair Croll, to learn more about music, data, and music science.
Today’s music industry is the product of three things: digital content, the Internet, and data science. This trifecta has altered how we find, consume, and share music. How we got here makes for an interesting history lesson, and a cautionary tale for incumbents that wait too long to embrace data.
When music labels first began releasing music on compact disc in the early 1980s, it was a windfall for them. Publishers raked in the money as music fans upgraded their entire collections to the new format. However, those companies failed to see the threat to which they were exposing themselves.
Until that point, piracy hadn’t been a concern because copies just weren’t as good as the originals. To make a mixtape using an audio cassette recorder, a fan had to hunch over the radio for hours, finger poised atop the record button — and then copy the tracks stolen from the airwaves onto a new cassette for that special someone. So, the labels didn’t think to build protection into the CD music format. Some companies, such as Sony, controlled both the devices and the music labels, giving them a false belief that they could limit the spread of content in that format.
One reason piracy seemed so far-fetched was that nobody thought of computers as music devices. Apple Computer even promised Apple Records that it would never enter the music industry — and when it finally did, it launched a protracted legal battle that even led coders in Cupertino to label one of the Mac sound effects “Sosumi” (pronounced “so sue me”) as a shot across Apple Records’ legal bow. Read more…
Implementing software quality standards guarantees measurable results.
Listen to the podcast Better code is cheaper to learn how the Software Improvement Group (SIG) is paving the way for software quality and maintainability.
Software quality is an often-overlooked development parameter, making way for those items that resonate outside of the engineering team – a faster schedule and an on-budget project. Joost Visser, Head of Research at Software Improvement Group (SIG) sat down with me to explain how a focus on quality helps to achieve the fastest possible schedules and lowest possible cost of development and maintenance.
The O’Reilly Design Podcast: Tristan Harris on design ethics and leaving things better than you find them.
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.
Harris talks about Design for Time Well Spent, the Doubt Club, and why it’s important to leave things better than you find them.
Here are a few highlights from our chat:
I think one aspect of why designers need to design responsibly is this new scale, this new proportion of influence and impact — because one choice about whether something takes five seconds of someone’s life versus one second of someone’s life gets multiplied by a billion people.
Even when the intention is very good and very positive, it devolves into what I’ve called the ‘race to the bottom of the brain stem’ to seduce people’s psychological instincts. The best way to get time from people, the best way to seduce or get their attention, is to use people’s psychological biases in a way that gets them to come back or stay.
Part of being ethical means being deeply thoughtful, comprehensive — not just optimistic about the one goal that you have, but to see where that goal might break down.