AI Games

Wired gives a preview of new AI games. One of them will automatically harmonize with notes you play. Another takes your line drawings and tries to guess what you were attempting to picture.

WIRED: AI Games

Alexa as an operating system

On the blog Stratechery, a recent post discussed Alexa, the new digital assistant from Amazon. It talked through the business model that Amazon seems to be employing in order to promote this new line of service.

Alexa can take many forms, but the primary means to access this tool is through a standalone product known as the Echo. The blog noted some key developments:

• The physical device (the Echo) was simply a conduit for Alexa, Amazon’s new personal assistant. And critically, Alexa was a cloud service, the development of which Amazon is uniquely suited to in terms of culture, organizational structure, and experience.
• The Echo created its own market: a voice-based personal assistant in the home. Crucially, the home was the one place in the entire world where smartphones were not necessarily the most convenient device, or touch the easiest input method: more often than not your smartphone is charging, and talking to a device doesn’t carry the social baggage it might elsewhere.
• There was an ecosystem to assemble: more and more “smart” products, from lightbulbs to switches, were coming on the market, but nearly every company trying to be the centerpiece of the connected home was relying on the smartphone.

Why is this important? Well, the article had earlier discussed the vital importance of the operating system as a key driver of digital value (think Microsoft Windows).

• All kinds of hardware manufacturers are lining up to build Alexa-enabled devices, and will inevitably compete with each other to improve quality and lower prices.
• Even more devices and appliances are plugging into Alexa’s easy-to-use and flexible framework, creating the conditions for a moat: appliances are a lot more expensive than software, and much longer lasting, which means everyone who buys something that works with Alexa is much less likely to switch

That leaves the business model, and this is perhaps Amazon’s biggest advantage of all: Google doesn’t really have one for voice, and Apple is for now paying an iPhone and Apple Watch strategy tax; should it build a Siri-device in the future it will likely include a healthy significant profit margin.

Amazon, meanwhile, doesn’t need to make a dime on Alexa, at least not directly: the vast majority of purchases are initiated at home; today that may mean creating a shopping list, but in the future it will mean ordering things for delivery, and for Prime customers the future is already here. Alexa just makes it that much easier, furthering Amazon’s goal of being the logistics provider — and tax collector — for basically everyone and everything.

Here is the link to the full article:  Stratechery: Amazon's operating system Alexa

Alphabet DeepMind and NHS

Concrete example of the use of Big Data in creating a new prediction model.

Google will be using NHS data to warn doctors of potential kidney issues.

http://www.theverge.com/2016/11/23/13726280/deepmind-nhs-data-streams-app-new-deal

10 Ways to improve your Google searches

From this article:
Brightside: 10 Ways to Search Google

1.  Either This or That:  Use the word "or" to help you search both at once and select the one that you want.
2.  Search using Synonyms:  Use the ~ to help search for additional related terms.
3.  Search within websites:  Add the url for the specific site to the search term.
4.  Wildcards:  Use the *. Allows for any combination including the relevant term.
5.  When lots of words are missing:  Use "AROUND + (n)" to help. Example: I wandered AROUND(4) cloud will turn up results like "I wandered around lonely as a cloud"
6.  Use a time frame:  Add specific dates to the search to help focus the results.
7.  Searching for a title or url:  Use the term "intitle:" or "inurl:" Example:  "intitle:husky"
8.  Finding similar websites:  Use the term "related:" Example:  "related:nike.com"
9.  Whole phrases:  Add quotation marks around a quote to get the exact quote in order in results.
10.  Unimportant search words:  Use the minus sign to eliminate the word.  Example:  "Interesting books -buy" for books that are interesting but that you don't want to buy.

The Apple approach to innovation

Vox has an article talking about the release yesterday of the Touch Bar for Apple MacBook Pro laptops. It's a significant advance. They explain why it succeeded for Apple despite the fact that this particular innovation had been tried before by other manufacturers but failed.

Apple controls its products tightly. This approach allows it to approach innovation very differently:

In contrast, Apple controls the entire “stack” for its products. It manufactures the hardware, writes a lot of the software, and even makes some of its own chips. This makes it hard to achieve a large market share, since it’s difficult for one company to serve a lot of different kinds of customers. But the example of the Touch Bar shows that the Apple approach still has some distinct advantages.

It’s hard to imagine anyone other than Apple successfully pulling off an ambitious innovation like the Touch Bar because it requires simultaneous investments on both the hardware and software sides of the business.

Apple’s ability to make dramatic changes to its platforms has been an important source of strength for the company. And it’s a big reason that two of Apple’s chief competitors — Google and Microsoft — have increasingly aped Apple’s business model in recent years.

Here is more on why Apple can lead far more successfully than its competitors despite having much less market share:

A feature like Touch Bar or Adaptive Keyboard is only going to succeed if it becomes a platform-wide standard. And on a decentralized platform like Windows, that creates a chicken-and-egg problem: Applications developers are only going to put in the effort to support it if it’s available on a lot of laptops. But laptop makers are only going to offer it if there’s a lot of application support.

This is a particularly severe problem in the Windows PC world precisely because the PC market is so competitive. The hardware for the Touch Bar is apparently expensive — Apple is charging $300 extra for the cheapest MacBook Pro with a Touch Bar compared with the entry-level MacBook Pro without it.

So if a PC maker added a Touch Bar to its laptops, it would be taking a big risk of getting undercut by competitors that skipped the Touch Bar and charged significantly less. This is probably one reason Lenovo’s adaptive keyboard was so much less impressive than the Touch Bar — the Chinese company couldn’t spend a lot on the feature and risk being priced out of the market.

Apple can guarantee that a significant percentage of their products will contain the new innovation. This allows the software makers to design products with the confidence that there will be a ready market for their work once the new innovation is finally released.

This model has been so successful for Apple that Microsoft and Google are now openly copying it. They have both ventured into producing their own hardware (Surface, Chromebooks, and the Pixel). All of this will likely lead to even more innovation in the years to come.

Here is a link to the original article:  http://www.vox.com/new-money/2016/10/27/13441068/touch-bar-apple-google

Building a perfect team

Throughout our career, we'll be asked to work on teams. They will come in various shapes and sizes. We'll probably be asked to work with people of different skills with different personalities. 

Google is interested in trying to build the perfect team. They opened "Project Aristotle" to study how they might achieve major improvements in their teams. This article in the NY Times discusses what they found.

Early on in the article, you are asked to decide which team you would rather join:

Team A is composed of people who are all exceptionally smart and successful. When you watch a video of this group working, you see professionals who wait until a topic arises in which they are expert, and then they speak at length, explaining what the group ought to do. When someone makes a side comment, the speaker stops, reminds everyone of the agenda and pushes the meeting back on track. This team is efficient. There is no idle chitchat or long debates. The meeting ends as scheduled and disbands so everyone can get back to their desks.

Team B is different. It’s evenly divided between successful executives and middle managers with few professional accomplishments. Teammates jump in and out of discussions. People interject and complete one another’s thoughts. When a team member abruptly changes the topic, the rest of the group follows him off the agenda. At the end of the meeting, the meeting doesn’t actually end: Everyone sits around to gossip and talk about their lives.

Which group would you rather join?

Researchers studied this issue by analyzing hundreds of teams to see if they could figure out what would work and what would not. Because of the wide differences between the makeup of the teams, they couldn't draw direct parallels. Instead, they found common themes. If a team succeeded in some tasks, they generally built on that success and succeeded at most of them. Conversely, if they ran into problems, they generally struggled at everything.

As the researchers studied the groups, however, they noticed two behaviors that all the good teams generally shared. First, on the good teams, members spoke in roughly the same proportion, a phenomenon the researchers referred to as ‘‘equality in distribution of conversational turn-taking.’’ On some teams, everyone spoke during each task; on others, leadership shifted among teammates from assignment to assignment. But in each case, by the end of the day, everyone had spoken roughly the same amount. ‘‘As long as everyone got a chance to talk, the team did well,’’ Woolley said. ‘‘But if only one person or a small group spoke all the time, the collective intelligence declined.’’

Second, the good teams all had high ‘‘average social sensitivity’’ — a fancy way of saying they were skilled at intuiting how others felt based on their tone of voice, their expressions and other nonverbal cues. One of the easiest ways to gauge social sensitivity is to show someone photos of people’s eyes and ask him or her to describe what the people are thinking or feeling — an exam known as the Reading the Mind in the Eyes test. People on the more successful teams in Woolley’s experiment scored above average on the Reading the Mind in the Eyes test. They seemed to know when someone was feeling upset or left out. People on the ineffective teams, in contrast, scored below average. They seemed, as a group, to have less sensitivity toward their colleagues.

Based on these findings, it seems as if Team B would go on to have more success. There were other findings, too:

What Project Aristotle has taught people within Google is that no one wants to put on a ‘‘work face’’ when they get to the office. No one wants to leave part of their personality and inner life at home. But to be fully present at work, to feel ‘‘psychologically safe,’’ we must know that we can be free enough, sometimes, to share the things that scare us without fear of recriminations. We must be able to talk about what is messy or sad, to have hard conversations with colleagues who are driving us crazy. We can’t be focused just on efficiency. Rather, when we start the morning by collaborating with a team of engineers and then send emails to our marketing colleagues and then jump on a conference call, we want to know that those people really hear us. We want to know that work is more than just labor.

....

The paradox, of course, is that Google’s intense data collection and number crunching have led it to the same conclusions that good managers have always known. In the best teams, members listen to one another and show sensitivity to feelings and needs.

The fact that these insights aren’t wholly original doesn’t mean Google’s contributions aren’t valuable. In fact, in some ways, the ‘‘employee performance optimization’’ movement has given us a method for talking about our insecurities, fears and aspirations in more constructive ways. It also has given us the tools to quickly teach lessons that once took managers decades to absorb. Google, in other words, in its race to build the perfect team, has perhaps unintentionally demonstrated the usefulness of imperfection and done what Silicon Valley does best: figure out how to create psychological safety faster, better and in more productive ways.

‘‘Just having data that proves to people that these things are worth paying attention to sometimes is the most important step in getting them to actually pay attention,’’ Rozovsky told me. ‘‘Don’t underestimate the power of giving people a common platform and operating language.’’

Project Aristotle is a reminder that when companies try to optimize everything, it’s sometimes easy to forget that success is often built on experiences — like emotional interactions and complicated conversations and discussions of who we want to be and how our teammates make us feel — that can’t really be optimized. Rozovsky herself was reminded of this midway through her work with the Project Aristotle team. ‘‘We were in a meeting where I made a mistake,’’ Rozovsky told me. She sent out a note afterward explaining how she was going to remedy the problem. ‘‘I got an email back from a team member that said, ‘Ouch,’ ’’ she recalled. ‘‘It was like a punch to the gut. I was already upset about making this mistake, and this note totally played on my insecurities.’’

After all of the study, Google didn't seem to learn anything more than "common sense" might have told them. That said, it was likely still worth the effort to underscore just how important some of the "soft skills" could be--even to the hard sciences and technology!

Here is the link to the full article:  http://www.nytimes.com/2016/02/28/magazine/what-google-learned-from-its-quest-to-build-the-perfect-team.html 

4G? No, 5G!!

Mobile applications require bandwidth. Generally speaking, speed is a necessity. As the internet becomes more pervasive and we ask our smartphones and devices to perform ever more sophisticated tasks, the demand for greater capacity grows. The planned "Internet of Things" will add billions of new connections. Google's dream of self-driving cars will need near instantaneous responses that can only occur with vastly improved infrastructure--especially in wireless communication.

The current state-of-the-art is 4G LTE. Top speeds can hit about 15 megabits per second. When available, it allows the user to download a high definition movie in about eight minutes. There are lab tests underway on the next generation of access called 5G. At top speeds in excess of 10 gigabits per second, that same movie will download in about five seconds!

Today, this technology is confined to the lab and highly controlled tests. It could be many years before you start to see this in full production. Major companies like Verizon, AT&T, and Cisco are working on plans to invest billions of dollars in the quest for ways to differentiate themselves.

Here are some articles that give more background on the subject.

General overview:  http://www.nytimes.com/2016/02/22/technology/what-5g-will-mean-for-you.html?ref=technology

Cisco, Ericsson, and Intel:  Cisco, Ericsson and Intel to work on 5G networks - Business Insider

CNET review of Verizon's plans:  Inside Verizon's vision of smokin' 5G speeds - CNET  

A search engine for your memories

There is a wide gap between the things I can remember and the things that I can't. Last summer, I got together with high school friends for an impromptu reunion and they started reminiscing about our experience from decades ago. I laughed and smiled, but I couldn't remember what they were talking about. No doubt, it was somewhere in the hidden recesses of my mind, but I had long ago lost the road markers that would lead me there.

When I was a little boy, I used to laugh at my mother all the time. She was constantly mixing up the names of my friends. Unfortunately, it seems that I find myself doing that now and the thought is a bit unsettling.

This article discusses one way to deal with this.

“Human memory is not the same as computer memory,” said James Kozloski, an inventor at IBM who focuses on computational and applied neuroscience. “We don’t have pointers. We don’t have addresses where we can just look up the data we need.”

Kozloski wants to change that. He recently filed a patent for technology that, in the simplest terms, will help finish your sentences for you. Like autocomplete for your voice, the system is a model of human memory that could be embedded in a device and offer prompts when necessary. It would use a combination of surveillance, machine learning, and Bayesian inference—a kind of predictive modeling—to recognize when a person has forgotten something, then provide the missing information.

“The idea is quite simple,” Kozloski told me. “You monitor an individual's context, whether it’s what they’re saying or what they’re doing ... and you predict what comes next.”

Kozloski has a specific use case in mind:

If you can get past the creepiness factor, a cognitive interface like the one Kozloski envisions could theoretically be useful for anyone, but he sees specific applications for people as they get older—and especially for those who suffer from diseases like Alzheimer’s. “The loss of ability to access memory in the moment is the beginning of the breakdown of normal cognitive function: the ability of individuals to interact with others, take care of themselves, clothe themselves, cook meals,” he said.

.....

Imagine for example, if your cognitive assistant knew that when you dial a certain person’s phone number—your niece, let's say—it should also remind you of the name of her husband. The system might also know that, because of the time of day when you’re calling, the husband is more likely to pick up the phone. Or that, by checking a calendar, it happens to be his birthday.

“All of that context becomes the basis for inference as to what name should be spoken when they pick up the phone,” Kozloski said.

That information—Paige’s husband’s name is Teddy. And it’s his birthday!— could come through an earpiece or mobile device. Or it could be part of a larger—and, frankly, more Hal 9000-esque—home integration. “It could be just the speakers in your house that are primed and ready to advise, literally waiting in the wings to assist,” Kozloski said.

To me, the idea is at once brilliant and creepy. Who knows what actually lurks in our minds and would you really want perfect recall of all your memories? There may be some things best left forgotten. Of course, maybe it could also bring back some of those brilliant ideas that I had in dreams that just as quickly vanished when I woke up....

I suppose it would be nice to have something that would never mix up (or forget) someone's name!

Here is the link to the full article:  The Cognitive Assistant That's Like Google for Your Brain - The Atlantic

As seen on TV

Original post:  Oct 1, 2015

Star Trek first aired in the 1960s. It presented a futuristic view of life in the 23rd century. Humans are exploring the galaxy in starships. In the show, computers are almost alive. The interface is not a keyboard. It's speech!

The latest version of the iPhone now has a new, improved Siri. You can actually address your virtual assistant from a distance of about five feet. This review from the NY Times, explains the evolution:

As David Pierce wrote recently in Wired, voice recognition and artificial intelligence are getting so good so quickly that it isn’t really a stretch to imagine that talking to computers will soon become one of the signature ways we interact with them. The new Siri is paving the way to what you might call “ambient computing” — a future in which robotic assistants are always on hand to answer questions, take notes, take orders or otherwise function as auxiliary brains to whom you might offload many of your chores.

Picture the “Star Trek” computer, but instead of powering a starship, it’s turning off the basement lights, finding you a good movie on Netflix and, after listening in on a fight between you and your spouse, reminding you to buy flowers the next day. It will be slightly creepy and completely helpful — and it’s coming faster than you think.

All of these improvements are changing the way that we interface with our digital assistants:

The ubiquity of voice-controlled assistants changes the way we interact with them. When Siri and other voice systems were new, they seemed gimmicky. Nobody quite knew what to do with them, and interactions veered toward the awkward. But the more assistants there are, and the more you use them, the more natural they feel — and that means the more you’ll use them, feeding the cycle.

Ironically, the Star Trek computer is not just fantasy. It is actually becoming a design goal!

In fact, for years now, Google’s top search engineers have been describing the “Star Trek” computer as their vision of the future of search.

“The ‘Star Trek’ computer is not just a metaphor that we use to explain to others what we’re building,” Amit Singhal, the head of Google’s search team, once told me. “It is the ideal that we’re aiming to build — the ideal version done realistically.”

Here is the link to the full article:  http://www.nytimes.com/2015/09/24/technology/personaltech/iphone-6s-hands-free-siri-is-an-omen-of-the-future.html?_r=0

Have you talked to your computer lately?

Original post:  Sep 3, 2015

Many new smartphones come equipped with a digital assistant. My wife is constantly talking to Siri. I don't have an Android, but I believe there is something similar with Cortana. I am sure there are others on the horizon. Each new improvement makes it easier for us to locate information that once required laborious searches through labyrinths of card catalogs and dusty shelves.

This article in Wired talks about how computers might actually be changing the way we describe the world about us: 

How Computers Are Changing the Way We Explain the World | WIRED

The example they give is in language translation. The first attempts at programming computers to perform this complex task involved a simple substitution. They would replace nouns with nouns and verbs with verbs (and so on). In the 1980's, a team working on an early version of IBM's Watson (the famous computer that defeated humans at Jeopardy!) came up with a new approach. They decided to use a statistical model:

They did this in a clever way. They got hold of a copy of the transcripts of the Canadian parliament from a collection known as Hansard. By Canadian law, Hansard is available in both English and French. They then used a computer to compare corresponding English and French text and spot relationships.

For instance, the computer might notice that sentences containing the French word bonjour tend to contain the English wordhello in about the same position in the sentence. The computer didn’t know anything about either word—it started without a conventional grammar or dictionary. But it didn’t need those. Instead, it could use pure brute force to spot the correspondence between bonjour and hello.

By making such comparisons, the program built up a statistical model of how French and English sentences correspond. That model matched words and phrases in French to words and phrases in English. More precisely, the computer used Hansard to estimate the probability that an English word or phrase will be in a sentence, given that a particular French word or phrase is in the corresponding translation. It also used Hansard to estimate probabilities for the way words and phrases are shuffled around within translated sentences.

Using this statistical model, the computer could take a new French sentence—one it had never seen before—and figure out the most likely corresponding English sentence. And that would be the program’s translation.

Their model proved successful. Google Translate uses this very method to perform its magic!

Language is not the only area where computers are pioneering:

Related stories are playing out across science, not just in linguistics. In mathematics, for example, it is becoming more and more common for problems to be settled using computer-generated proofs. An early example occurred in 1976, when Kenneth Appel and Wolfgang Haken proved the four-color theorem, the conjecture that every map can be colored using four colors in such a way that no two adjacent regions have the same color. Their computer proof was greeted with controversy. It was too long for a human being to check, much less understand in detail. Some mathematicians objected that the theorem couldn’t be considered truly proved until there was a proof that human beings could understand.

As computers grow more and more powerful, it will be fascinating to watch how they literally begin to change the way we experience the world around us. I am sure that healthcare will be no different than the world at large!

Innovation has to extend beyond the product itself

Original post:  Feb 3, 2015

It's extremely hard to create new markets out of thin air. While we correctly heap all kinds of praise on the chosen few that succeed in bringing amazing new inventions into our lives, we also ignore the thousands of new products that never quite find their footing. Many of those lesser lights were excellent ideas on their own. For whatever reason, they may not have captured the imagination of enough customers to sustain themselves in the marketplace.

We often think of the giant technology companies as if they are invincible. They toss around their mighty power and we simply react. But even the largest and most successful companies sometimes have a difficult time sustaining innovation.

One example of that is Google. While they dominate search and have other really great products like Google Analytics, Maps, and Documents, they do not enjoy complete success at all of their inititives. They were unable to make Google Health work properly. Google Wave had promise but never caught fire. Even Google Glass, once so highly prized that there was a lottery for the right to pay $1500 to acquire one, has now been downgraded to a much lower profile. This article explains some of the reasons why:

On Thursday, Google announced that it would stop selling its much ridiculed Google Glass smart glasses, and that the product would no longer be developed in Google X, the company’s research division.

In a blog post on the Google Plus social network, Google said Glass was graduating from X. It will still be available to “certified partners” and for commercial trials in places like hospitals and factories. But the Explorer program, in which software developers and gadget nerds could buy a test version of the product, is over.

The article continues by pointing out that only two years ago, Glass was the star at Google's developers conference. It showcased some of the incredible future possibilities of the platform. Yet all of that promise also held some of the same reasons why it hasn't been successful:

Today, Glass is more like a case study in the perils of developing hardware whose purpose isn’t clear. Unlike, say, the iPhone — which cleverly combined products people already understood and used — consumers weren’t quite sure what to make of Glass. That creeped some people out.

The device was pre-emptively banned by bars and large parts of Las Vegas. Legislators in West Virginia tried to make it illegal to use the gadget while driving.

“There’s no vision for why people actually need this device,” Mr. Gownder said. “That’s a problem. When you don’t have that, people fill that in with their own assumptions, and right now the assumption is that this is a device for recording people.”

That last issue probably doomed the product. The article closes:

“From the privacy perspective, we are of course pleased to see Google drop this product,” Marc Rotenberg, president of the Electronic Privacy Information Center, wrote in an email. “And it is a very big deal when Google backs down, particularly after its big push.”

He continued: “But it is also speaks to a larger issue in tech design about privacy. Eyeglass-mounted web display and phone for those who wanted it? Not really a problem. Surveillance and recording of those around the user? Yeah, that’s a problem.”

Here is the link to the full article:  http://bits.blogs.nytimes.com/2015/01/18/a-retreat-for-google-glass-and-a-case-study-in-the-perils-of-making-hardware/?_…

The missing link

Original post:  Jan 8, 2015

A few years ago when the iPhone was just starting out, there used to be a marketing tag line that went "there's an app for that." Now that there are literally hundreds of thousands of different apps, there really does seem to be an application for just about anything that you can imagine. Unfortunately, there doesn't seem to be an easy way to link these various apps together.

One of the reasons search engines have been so successful is that they take the chaos that is the world wide web and help to simplify and organize it into digestible chunks. You don't have to be an expert about every topic under the sun. By crawling the web, sites like Google and Bing do the heavy lifting for you to return relevant search results. There is no such entity linking apps together. At this point, there are all kinds of data and information inputs in all of these apps, but nothing linking them together.

This article from the New York Times discusses this gap:  http://www.nytimes.com/2015/01/06/technology/tech-companies-look-to-break-down-walls-between-apps.html?_r=0

Here is an introduction to the issue:

Navigating the Internet used to mean painstakingly typing the exact address you wanted into your computer. The web browser and the search engine simplified that, giving us the Internet we take for granted today.

Now, across Silicon Valley, companies from tiny start-ups to titans like Google and Facebook are trying to bring the same simplicity to smartphones by teaching apps to talk to one another.

Unlike web pages, mobile apps do not have links. They do not have web addresses. They live in worlds by themselves, largely cut off from one another and the broader Internet. And so it is much harder to share the information found on them.

It is not just a matter of consumer convenience. For Google and Facebook, and any company that has built its business on the web, it is a matter of controlling the next entryway to the Internet — the mobile device.

The major companies are hard at work on the problem:

Take Google, which makes money helping people search the web. When people search in apps, it is mostly left out. And while the company has a fast-growing business selling apps through devices that use its Android operating system, that pales in comparison to its business selling search advertising.

Google’s solution is App Indexing technology, a way to catalog app pages, letting Google’s search engine retrieve information from mobile applications as well as from web pages.

Still, there are major challenges:

With so many companies and investors working on deep linking, the competition has become a problem. That is because the easiest way to get apps to link as if they were part of the web is to get app developers to adopt one standard that would work across devices and operating systems.

“Once we’re all using the same plumbing, everyone can go and build businesses and interesting experiences on top of that,” said Eddie O’Neil, a Facebook product manager working on the company’s program, App Links.

The app problem traces its origins to 2008, when Apple introduced the App Store for iPhones. Unlike websites, apps were set up to be separate little boxes whose technology prohibited them from interacting with one another. At the time, the idea of a phone full of apps was new enough that most people were not very worried about whether those apps could link to each other. But today, apps have begun to eclipse the web. Americans spend about half of their time online using mobile apps, according to comScore, a digital media analytics company.

It will be fascinating to watch as our mobile world morphs and changes over the coming years.

How do I know that you're you?

Original post:  Dec 8, 2014

It seems like we are getting closer to eliminating one irritant in our daily lives. When was the last time you had to enter a captcha?

These types of screens ask you to enter a set of characters that are deliberately obscured to make it difficult for automated "bots" to read using optical character recognition. It's supposed to separate out the humans who you typically want from the spammers and evildoers who you don't. As with any plan, there are now some sophisticated programs that can use crowdsourcing and other techniques to get past the captcha. Meanwhile, the rest of us suffer through the puzzles every time we have to reset a password.

Google has come up with a new technique. It's quite simple. All you will have to do is click on a checkmark. Most of the time, that will be it. Based on the track of your mouse, it can make an educated guess that is 60-80% accurate about whether or not there is a real person making the click or an automated program.

Here's an excerpt from the Wired article on this exciting development:

“For most users, this dramatically simplifies the experience,” says Vinay Shet, the product manager for Google’s Captcha team. “They basically get a free pass. You can solve the catptcha without having to solve it.”

Instead of depending upon the traditional distorted word test, Google’s “reCaptcha” examines cues every user unwittingly provides: IP addresses and cookies provide evidence that the user is the same friendly human Google remembers from elsewhere on the Web. And Shet says even the tiny movements a user’s mouse makes as it hovers and approaches a checkbox can help reveal an automated bot.

“All of this gives us a model of how a human behaves,” says Shet. “It’s a whole bag of cues that make this hard to spoof for a bot.” He adds that Google also will use other variables that it is keeping secret—revealing them, he says, would help botmasters improve their software and undermine Google’s filters.

Unfortunately, this is only for desktop users (for now). Smartphone and tablet users might have a different challenge:

For smartphone and tablet users, Google hasn’t simplified its captcha to a single click. Instead, it will show users a collection of images and ask them to make distinctions that might be tough for bots. For instance, it might display a picture of a cat and ask the user to tap the images that match it among eight photos of other cats, dogs, gerbils and leaves.

One last quote:

But Google’s Shet points out that when its captchas appear on other sites, Google will only be able to track the user’s movements over the captcha widget, not the whole page. And he argues that captchas are, by their very nature, good for privacy: They provide a way to show you’re a good user, rather than an evil bot, without logging in to a service or coughing up identifying details. “You don’t have to verify your identity,” Shet says, “to verify your humanity.”

Here is the link to the full article:  Google Can Now Tell You're Not a Robot With Just One Click | WIRED

No, you first

Original post:  Oct 6, 2014

In many of the fields that I work in, collaboration is a necessity. Some of these projects, like the UDI Program, are internal. Others, like GHX or GS1, are external. In each of these cases, there is the challenge of trying to get personnel or organizations with vested interests in the status quo to take actions which may run counter to their short-term interests. Even if it is in pursuit of a shared long-term goal, it can often be difficult to get anyone to look past the standard question of "what's in it for me?".

In today's USA Today, the Money section has a lengthy article on Apple Pay.

Apple is in that same quandry with Apple Pay. This ambitious proposal attempts to allow for the use of mobile devices to authorize payment at the point of sale. There have been previous attempts to do just this before in other industries. There are many places in Europe that allow users to use their cellphones to make payments. Google Wallet was another attempt that has not yet succeeded in any meaningful way.

In this case, Apple may have a chance to succeed where others have not. They have established a large network of retail outlets that are willing to accept their network and authorize the payments. This is a very costly effort, since the retailers will either have to retrofit or purchase special terminals that will work with the Apple devices that now use the Near Field Communications (NFC) protocol. It will also force interested users to upgrade to the latest iPhone 6 or 6 plus in order to take advantage of these efforts.

One potential advantage Apple may have in this effort is the recent focus on card security. Major breaches at Target, TJ Maxx, and Home Depot are accelerating a push towards more secure forms of commerce like the chip and pin credit cards.

Competitors are already starting to worry about this new threat. This may mean that this attempt finally makes this method of payment viable. Here is a link to an article discussing how PayPal is trying to adapt:

Apple Pay is such a big deal that eBay already has had to change strategy – Quartz