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ANDRÉ CRAMER

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May 2017

Great piece – but sad it’s Walt Mossberg’s last ever column: The Disappearing Computer (Walt Mossberg)

As I write this, the personal tech world is bursting with possibility, but few new blockbuster, game-changing products are hitting the mainstream. So a strange kind of lull has set in.

The multi-touch smartphone, launched 10 years ago with Apple’s first iPhone, has conquered the world, and it’s not done getting better. It has, in fact, become the new personal computer. But it’s a maturing product that I doubt has huge improvements ahead of it. Tablets rose like a rocket, but have struggled to find an essential place in many people’s’ lives. Desktops and laptops have become table stakes, part of the furniture.

The big software revolutions, like cloud computing, search engines, and social networks, are also still growing and improving, but have become largely established…

Source: Mossberg: The Disappearing Computer – The Verge

This is impressive progress made possible by Machine Learning: Google’s speech recognition technology now has a 4.9% word error rate (Emil Protalinski)

Google CEO Sundar Pichai today announced that the company’s speech recognition technology has now achieved a 4.9 percent word error rate. Put another way, Google transcribes every 20th word incorrectly. That’s a big improvement from the 23 percent the company saw in 2013 and the 8 percent it shared two years ago at I/O 2015.

The tidbit was revealed at Google’s I/O 2017 developer conference, where a big emphasis is on artificial intelligence. Deep learning, a type of AI, is used to achieve accurate image recognition and speech recognition. The method involves ingesting lots of data to train systems called neural networks, and then feeding new data to those systems in an attempt to make predictions…

 

Source: Google’s speech recognition technology now has a 4.9% word error rate | VentureBeat | Dev | by Emil Protalinski

Great Read on the Future of Manufacturing: How Microfactories Can Bring Iterative Manufacturing to the Masses (Andrew O’Keefe, Jason Dorrier)

Humans manufacture a mind-numbing amount of stuff each year—ever wonder how we do it? In the past 100 or more years, it’s been all about economies of scale. This means you should make a lot of a thing because the more you make, the more your fixed expenses get spread out. This reduces the cost of each unit, from light bulbs to iPhones. Here’s the problem. It’s expensive to do a big manufacturing run. So, how do you know what to make in the first place? Often, it’s an educated guess based on prototypes and limited feedback, but you don’t really know until you try to sell a product—and by then, you’re fully committed, succeed or fail. Jay Rogers of Local Motors wants to upend common wisdom. Manufacturers should run through tons of potentially good ideas and then…

via How Microfactories Can Bring Iterative Manufacturing to the Masses

Google’s AI Invents Sounds Humans Have Never Heard Before (Cade Metz)

Jesse Engel is playing an instrument that’s somewhere between a clavichord and a Hammond organ—18th-century classical crossed with 20th-century rhythm and blues. Then he drags a marker across his laptop screen. Suddenly, the instrument is somewhere else between a clavichord and a Hammond. Before, it was, say, 15 percent clavichord. Now it’s closer to 75 percent. Then he drags the marker back and forth as quickly as he can, careening though all the sounds between these two very different instruments. “This is not like playing the two at the same time,” says one of Engel’s colleagues, Cinjon Resnick, from across the room. And that’s worth saying. The machine and its software aren’t layering the sounds of a clavichord atop those of a Hammond. They’re producing entirely new sounds using the mathematical characteristics of the notes that emerge…

via Google’s AI Invents Sounds Humans Have Never Heard Before | WIRED

Great Read: Here’s The Unofficial Silicon Valley Explainer On Artificial Intelligence (Daniel Terdiman)

I’m willing to bet you didn’t know that artificial intelligence can help sort cucumbers. It can, and in fact it does. And while AI has gotten massive amounts of attention recently due to its role in making cars autonomous, doing facial recognition, and automatically translating languages, there’s one man in Silicon Valley who really wants everyone developing any kind of technology-based tool to know that AI has something to offer them as well. Last year, Frank Chen, a partner at the A-list venture capital firm Andreessen Horowitz (a16z), published a primer on artificial intelligence. The 45-minute video took viewers through a history of the technology, from its “birthday” in the summer of 1956 through its years in the wilderness of technology and straight through current-day Silicon Valley, where it is dominating conversations at most of the largest tech companies there.

In fact, if the mobile cloud was computing’s previous major era, the next will be the era of AI…

via Here’s The Unofficial Silicon Valley Explainer On Artificial Intelligence

Time well-spent listening: The Digital Industrial Revolution (TED Radio Hour @NPR)

Guy Raz: “I ask myself this question a lot which is: Is this the future we want? Have we gotten to a place where the train has left the station, where we don’t really have much of a choice about where the future is heading?”

Erik Brynjolfsson: “Well let me try to cheer you up a little bit. Let’s just step back and look at the fundamentals. What are you and I are talking about? We re talking about a world with vastly more wealth, vastly more power to solve all sorts of problems. Vastly less need for us to work. Most routine tasks could be eliminiated. Shame on us, shame on us, if we mess that up and turn that into a bad thing. Wouldn’t that be the worst irony in the world where we take more wealth and less work and say ‘Oh, what a terrible thing?’ I think we can essentially eliminate poverty from planet earth, we can cure most deseases. And the global millennium goals, we are on track to beat them and eliminate severe poverty. There are a lot of positive trends. I think the world in 25 years could be a much better version of the world we have today. But the role of humans would still be fundamentally at the center of that.”

Source: The Digital Industrial Revolution : TED Radio Hour : NPR

Interesting Development regarding Bay Area & Seattle: Silicon Valley North – How America’s two tech hubs are converging (The Economist)

Would your region care to be the next Silicon Valley? In most of the world’s technology hubs, local leaders scramble to say “yes”. But ask the question in and around Seattle, the other big tech cluster on America’s west coast, and more often than not the answer is “no”—followed by explanations of why the city and its surrounds are different from the San Francisco Bay Area. The truth may be more complex: in recent years the Seattle area has become a complement to the valley. Some even argue that the two regions, though 800 miles (1,300km) apart, are becoming one…

 

Source: Silicon Valley North: How America’s two tech hubs are converging | The Economist

Synthetic Sensors Is a Sensor That Could Soon Make Homes Scary-Smart (Liz Stinson)

If you want to set up a connected home, you’ve got two options. You can buy a bunch of smart gadgets that may or may not communicate with other smart gadgets. Or you can retrofit all of your appliances with sensor tags, creating a slapdash network. The first is expensive. The second is a hassle. Before long, though, you might have a third choice: One simple device that plugs into an electrical outlet and connects everything in the room. That’s the idea behind Synthetic Sensors, a Carnegie Mellon University project that promises to make creating a smart, context-aware home a snap. The tiny device, unveiled this week at the big ACM CHI computer interaction conference, can capture all of the the environmental data needed to transform a wide variety of ordinary household objects into smart devices…

Source: Synthetic Sensors Is a Sensor That Could Soon Make Homes Scary-Smart | WIRED

The U.S., Canada and Mexico are buying more job-killing robots than ever before (April Glaser, Rani Molla)

Robots are getting cheaper and smaller and, as a result, sales have grown significantly over the past year, particularly in North America, as more companies move manufacturing operations closer to U.S. markets. North American manufacturing companies bought a total of 9,773 industrial robots, valued at approximately $516 million, in the first quarter of 2017. That means 32 percent more robots were bought this year than at the same time in 2016 — it’s the strongest first quarter on record for robots ordered by North American companies, according to the Robotic Industries Association…

via The U.S., Canada and Mexico are buying more job-killing robots than ever before – Recode

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