- Introduction to Keyboard Programming — what happens when you press a key. (hint: a lot)
- Oblique Strategies: Prompts for Programmers — Do it both ways. Very often doing it both ways is faster than analyzing which is best. Now you also have experimental data instead of just theoretical. Add a toggle if possible. This will let you choose later. Some mistakes are cheaper to make than to avoid.
- The Responsibility We Have as Software Engineers — Where’s our Hippocratic Oath, our “First, Do No Harm?” Remember that moment when Google went from “amazing wonderful thing we didn’t have before, which makes our lives so much better” to “another big scary company and holy shit it knows a lot about us!”? That’s coming for our industry and the software engineering profession in particular.
- Gallery of Concept Visualisation — plenty I hadn’t seen before.
Leadership has changed — and in a big way — since the Web started upending the status quo two decades ago. That’s why we’re launching our new Cultivate event — Cultivate is O'Reilly's conference committed to training the people who will lead successful teams, now and in the future. Read more...
A look at AR today and how we need to design it for tomorrow.
Attend O’Reilly’s Solid Conference, June 23–25, in San Francisco. Solid is our conference exploring how the collision of software and hardware is fueling the creation of a software-enhanced, networked physical world. Helen Papagiannis will speak at Solid on June 24.Unlike virtual reality (VR), augmented reality (AR) provides a gateway to a new dimension without the need to leave our physical world behind. We still see the real world around us in AR, whereas in VR, the real world is completely blocked out and replaced by a new world that immerses the user in a computer generated environment.
The most common definition of AR to date is a digital overlay on top of the real world, consisting of computer graphics, text, video, and audio, which is interactive in real time. This is experienced through a smartphone, tablet, computer, or AR eyewear equipped with software and a camera. Examples of AR today include the translation of signs or menus into the language of your choice, pointing at and identifying stars and planets in the night sky, and delving deeper into a museum exhibit with an interactive AR guide. AR presents the opportunity to better understand and experience our world in unprecedented ways.
AR is rapidly gaining momentum (and extreme amounts of funding) with great advances and opportunities in science, design, and business. It is not often that a whole new communications medium is introduced to the world. AR will have a profound effect on the way we live, work, and play. Now is the time to imagine, design, and build our virtual future.
Working with AR for a decade as a Ph.D. researcher, designer, and technology evangelist, I’ve watched AR evolve in regard to both technology (software and hardware) and experience design. An AR experience is commonly triggered by tracking something in the physical environment that activates the AR content. Images, GPS locations, and the human body and face are all things that can be tracked to initiate an AR experience, with more complex things like emotion and voice expanding this list. We are seeing a rise in AR hardware, with a particular emphasis on digital eyewear that includes gesture interaction from companies like Magic Leap and Microsoft with the recently announced HoloLens headset.
Designing AR for tomorrow
We are at a moment where we are also seeing a shift from AR as a layer on top of reality to a more immersive contextual experience that combines things like wearable computing, machine learning, and the Internet of Things (IoT). We are moving beyond an experience of holding up our smartphones and seeing three-dimensional animations like dinosaurs appear to examples of assistive technology that help the blind to see and navigate their surroundings. AR is life changing, and there is extreme potential here to design experiences that surpass gimmickry and have a positive effect on humanity.
MIT Media Lab founder Nicholas Negroponte said, “Computing is not about computers anymore. It is about living.” AR, too, is no longer about technology; it’s about defining how we want to live in the real world with this new technology and how we will design experiences that are meaningful and help advance humanity. There is an immediate need for storytellers and designers of all types to aid in defining AR’s trajectory. The technology exists, now it’s about authoring compelling content and applying meaningful experiences in this new medium.
It’s critical that we are asking these big questions now, at a time when AR is still largely undefined. I’m excited to be able to initiate and have these conversations across disciplines. I hope you’ll join me at O’Reilly’s Solid Conference 2015 in San Francisco June 23-25, where I’ll talk about the new opportunities this technological shift represents, highlighting and expanding on significant moments, inventions, and concepts. I’ll also be speaking at the annual Augmented World Expo 2015 in Silicon Valley June 8-10, where this year’s theme is “Superpowers to the People.”
Keeping it human-centered
For me, it’s about maintaining our humanness in a sea of limitless options within this new medium. We must think critically about how we will place human experience at the center. It’s not about being lost in our devices; it’s about technology receding into the background so that we can engage in human moments.
An article in Forbes by John Hagel and John Seely Brown looked at how IoT can help to enhance human relationships. Hagel and Brown described a scenario (that can be powered with current technology) of “data-augmented human assistance,” where a primary care physician wearing digital eyewear interacts with a patient to listen attentively and maintain eye contact while accessing and documenting relevant data. With the process of data capture and information transfer offloaded into the background, such devices can be applied to improve human relationships. “Practitioners can use technology to get technology out of the way — to move data and information flows to the side and enable better human interaction,” wrote Hagel and Brown, noting how such examples highlight a paradox that is inherent in the IoT: “although technology aims to weave data streams without human intervention, its deeper value comes from connecting people.”
This new wave of AR that combines IoT, big data, and wearable computing also has an incredible opportunity to connect people and create meaningful experiences, whether it’s across distances or being face to face with someone. The future of these new experiences is for us to imagine and build. Reality will be augmented in never-before-seen ways. What do you want it to look like and what role will you play in defining it?
The O'Reilly Radar Podcast: Cait O'Riordan on Shazam's predictive analytics, and Francine Bennett on using data for evil.
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 Radar Podcast, I chat with Cait O’Riordan, VP of product, music and platforms at Shazam. She talks about the current state of predictive analytics and how Shazam is able to predict the success of a song, often in the first few hours after its release. We also talk about the Internet of Things and how products like the Apple Watch affect Shazam’s product life cycles as well as the behaviors of their users.
Predicting the next pop hit
Shazam has more than 100 million monthly active users, and its users Shazam more than 20 million times per day. This, of course, generates a ton of data that Shazam uses in myriad ways, not the least of which is to predict the success of a song. O’Riordan explained how they approach their user data and how they’re able to accurately predict pop hits (and misses):
What’s interesting from a data perspective is when someone takes their phone out of their pocket, unlocks it, finds the Shazam app, and hits the big blue button, they’re not just saying, “I want to know the name of this song.” They’re saying, “I like this song sufficiently to do that.” There’s an amount of effort there that implies some level of liking. That’s really interesting, because you combine that really interesting intention on the part of the user plus the massive data set, you can cut that in lots and lots of different ways. We use it for lots of different things.
At the most basic level, we’re looking at what songs are going to be popular. We can predict, with a relative amount of accuracy, what will hit the Top 100 Billboard Chart 33 days out, roughly. We can look at that in lots of different territories as well. We can also look and see, in the first few hours of a track, whether a big track is going to go on to be successful. We can look at which particular part of the track is encouraging people to Shazam and what makes a popular hit. We know that, for example, for a big pop hit, you’ve got about 10 seconds to convince somebody to find the Shazam app and press that button. There are lots of different ways that we can look at that data, going right into the details of a particular song, zooming out worldwide, or looking in different territories just due to that big worldwide and very engaged audience.
How the IoT could help organizations create a better employee experience.
Contributing Author: Claire Niech
Attend O’Reilly’s Solid Conference, June 23–25, in San Francisco. Solid is our conference exploring how the collision of software and hardware is fueling the creation of a software-enhanced, networked physical world.
At 5:37 a.m., Nina’s alarm softly begins to buzz and glow. It has calculated her recovery time based on her previous day’s workout and monitored her sleep tracker to identify the best point in her REM cycle to wake her up. After rising, she grabs a healthy breakfast and her PrepPad or Drop connected kitchen scale records the fat, protein, calories, and carbohydrates in her meal.
For athletes like Nina, this kind of technology-enabled tracking is now standard. When Nina hits the gym for her daily routine, she warms up on a treadmill equipped with sensors to help gauge when she is striking at her optimal force. As she practices technique and form, a ‘smart’ surface records the location and duration of each move. Her training regimen is personalized based on this data; ‘instead of working off a generalized idea of what an athlete needs to be successful, [data analysis] has identified the specific abilities that a player requires to excel in a given sport.’ (From Faster, Higher, Stronger, by Mark McClusky)
Professional athletes today increasingly rely on Internet-connected devices and sensors to boost performance. Yet, the potential of such devices — commonly called the “Internet of Things” — extends beyond sports and fitness; as “weekend warriors” begin to bring these technologies mainstream, it is not hard to imagine that similar devices may soon also help us better understand other complex personal pursuits, such as creativity and productivity at work. As Laszlo Bock, who runs Google’s People Operations, notes: “We all have our opinions and case studies, but there is precious little scientific certainty around how to build great work environments, cultivate high-performing teams, maximize productivity, or enhance happiness.”
Today, many organizations tackle these questions with an industrial-organizational approach, diagnosing the issues most relevant to their workforce using tools such as annual surveys and benchmarking. But today’s approach seldom offers insight on “what works” — ways to track, teach, or reinforce new behaviors, or to see if specific initiatives are achieving the desired effect. Solutions to complex challenges like productivity or satisfaction often vary by organization, and demand better, real-time measurement and testing to enable experimentation.
By weaving together our physical and digital environments, sensors could help organizations analyze how factors like mood, focus, social engagement, or movement contribute to the employee experience — and even help replicate or enhance this experience. Consider how this new technology could impact how companies do work, assess outcomes, and enable employees to thrive. Read more…
The O'Reilly Data Show Podcast: Gary Kazantsev on how big data and data science are making a difference in finance.
Having started my career in industry, working on problems in finance, I’ve always appreciated how challenging it is to build consistently profitable systems in this extremely competitive domain. When I served as quant at a hedge fund in the late 1990s and early 2000s, I worked primarily with price data (time-series). I quickly found that it was difficult to find and sustain profitable trading strategies that leveraged data sources that everyone else in the industry examined exhaustively. In the early-to-mid 2000s the hedge fund industry began incorporating many more data sources, and today you’re likely to find many finance industry professionals at big data and data science events like Strata + Hadoop World.
During the latest episode of the O’Reilly Data Show Podcast, I had a great conversation with one of the leading data scientists in finance: Gary Kazantsev runs the R&D Machine Learning group at Bloomberg LP. As a former quant, I wanted to know the types of problems Kazantsev and his group work on, and the tools and techniques they’ve found useful. We also talked about data science, data engineering, and recruiting data professionals for Wall Street. Read more…
The O'Reilly Solid Podcast: Andy Cavatorta and Jamie Zigelbaum on art that combines physical and digital.
One of the theses behind our Solid Conference is that the stacks — the ranges of knowledge that technologists need to understand — are expanding so that the formerly separate disciplines of hardware and software are merging. Specific expertise is still critical, but the future lies in systems that integrate physical and virtual, and developing those effectively requires the ability to understand both sides at some basic level.
Installation art is a great place to look for those seamless integrations, and we’re excited to feature a couple of interesting installations at Solid. Our latest episode of the Solid Podcast takes us to Flatbush Avenue in Brooklyn, home to a collective of designers and engineers called Dark Matter Manufacturing, where David Cranor and I spoke with Andy Cavatorta and Jamie Zigelbaum. Cavatorta and Zigelbaum both create installations; Cavatorta works with sound and robotics, and Zigelbaum’s projects explore communication and interaction.
Cavatorta’s Dervishes installation will appear at O’Reilly Solid, June 23-25. He will also speak on “Music, machines, and meaning: What art teaches us about robotics and networks.” Read more…