Archive for the ‘Software, Technology, and Wow I Didn't Know That’ Category

… “123456”.  And that’s a problem, according to Security Keeper, Inc.  For years, tech firms have been trying to limit the damage hackers can do by cracking conventional passwords.  They’ve tried two-factor authentication for Gmail, iris scanning, fingerprint ID… and yet phishing and scamming schemes not only persist, they become larger, more audacious, more widespread and more costly.

Our firm has witnessed more than one of our ERP clients compromised by ransomware in the last year.  And while weak passwords aren’t necessarily the only way in to networks, they don’t help.  A product manager at Yahoo! once put it succinctly: “Our vision is to kill passwords completely.”  This was noted in a recent article on computer security in Bloomberg Businessweek (June 2017).  “In the future we’ll look back on this time and laugh that we were required to create a 10-character code” with mixed case, numbers and symbols, according to Yahoo’s Dylan Casey, VP of Product Management.  And the day can’t come soon enough for most of us.

To move in that direction, new ideas are emerging.  Yahoo lets email users unlock their accounts solely through a push notice sent to their smartphones, no password required.  Others are following similar “smartphone-as-skeleton-key” approaches, or are expanding the use of biometrics as unique identifiers, in lieu of passwords.  Samsung is about to allow Galaxy S8 owners authorize mobile payments (in the U.K. for now) utilizing the phone’s iris scanner.  Microsoft and Lloyds Banking are experimenting with allowing users access to online accounts using a webcam photo of their face.

Microsoft also offers fingerprint authentication via smartphone, with plans soon for desktops and laptops.  According to Alex Simons of Microsoft, “You’ll be able to take your phone, walk up to your Windows 10 PC and just user your thumbprint to log in.”  Barclay’s bank is experimenting with identify verification over the phone using vocal records.

While none of these security measures is perfect (you can fool the S8’s facial recognition for example by holding up a photo of the right person’s face), still… they’re big steps in the right direction.  As in all things tech, it’s only a matter of time.

Michela Menting, a security researcher at ABI Research still believes it will be tough to get those last holdouts from using their 123456 though “until we have embedded devices in ourselves that can act as that password.”  Scary thought.  Welcome to the future.

But we’ll close with this factoid from USA Today: 37% of Americans keep a piece of paper with all of their passwords somewhere they deem safe.  (Want to bet it’s more than that?)


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Recently the editors of Computerworld laid out a nice overview of all the new features in Microsoft’s Excel 2016 – a cheat sheet of sorts in giving readers a quick summary of What’s New for 2016.

These new features are available to users of both the standalone Excel version and the one incorporated into their newer Office 365 suite subscription.  We’ll provide the link to the full article at the end of this post, so you can review it yourself.  Meanwhile, a quick summary:

  • The Tell Me feature makes Excel simpler to use by letting you tell Excel what you want to do – say, create a Pivot Table – and get instant direction with shortcuts on doing what you requested, so you can start building that table right away.
  • Smart Lookup lets you do research online in the background while you’re working on your sheet. It uses Bing to do a web search on words at places like Wikipedia, and lets you “define” words or further “explore” as well.
  • New chart types:
    • Histograms – for statistical analysis
    • Waterfalls – for showing running financial totals, say from gross revs to net income
    • Hierarchical Treemaps – to help find patterns in data
    • Sunbursts – for showing graphical relationships between categories and their sub (and sub-sub-) categories
    • Pareto (80/20) – a “sorted histogram” that shows both bars and lines to better display cumulative totals of percentages (you could see, say, primary machine “downtime reasons” at a glance)
    • Box & Whisper – for deeper drilldowns than a histogram to see frequencies within data sets.
  • Improved Collaboration for users of the online version (only). A better way to share spreadsheets and see who has made what changes and when.  You can do some “simpler sharing” with the desktop version, with some limitations, to allow changes by more than one user at a time.
  • Quick Analysis is a new feature that lets you quickly highlight select cells and then click a little lightning bolt icon to perform instant analysis (for Greater Than purposes, numerical averages, or a chart on the fly).
  • Forecast Sheet lets you build forecasts based on historical data if you are working with time-based historical data in your worksheets.
  • Get & Define (formerly Power Query) is a BI tool that lets you import, combine and shape data from a variety of local and cloud sources.
  • 3D Maps allow you to plot geographic and other information on a map. You’ll need of course suitable data and to prepare it for 3D Maps.

As a bonus, Computerworld provides a nifty 2016 Ribbon Reference Guide and 2016 listing of Keyboard Shortcuts at their site as well.  You’ll find it all here: http://www.computerworld.com/article/3193992/desktop-apps/excel-2016-cheat-sheet.html?cid=cw_nlt_computerworld_microsoft_2017-05-16


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In our prior post, we pointed out that China is on the verge of becoming the world leader in the production, sale and implementation of robots, with a stated goal of producing at least half the nation’s own robots for manufacturing by 2025.  The takeaway from that view, outlined recently in Bloomberg BusinessWeek might be that the world has much to fear from the ascendance of this wave of Chinese bots.

But a recent counterpoint to such a robot apocalypse offered by Greg Ip of the Wall Street Journal suggests that in fact, robots aren’t destroying enough jobs, fast enough.

In short, Ip points out that by enabling society to produce more with the same workers, automation like robots becomes a major driver of rising standards of living – in effect, a productivity boost.  While some say that “this time is different” because the technological change is so profound they fear that millions of workers will be out of work or at best consigned to more menial tasks… Ip says the evidence shows we’re moving in exactly the opposite direction.

He notes that while the U.S. “has many problems, job creation isn’t one of them.”  Job creation has averaged 185,000 per month this year and unemployment is down to a ten year low.  Wage gains are even up, slightly.  Ip says that “if automation were rapidly displacing workers the productivity of the remaining workers ought to be growing rapidly.”  Instead, worker output per hour has been dismal in most sectors, including manufacturing.

When slow-growing occupations are compared to fast-growing ones in data going back to 1850 (a proxy for job creation and destruction driven by ‘technology’), they find that churn relative to total employment today is the lowest on record.

Ip’s point is that the past was, in fact, much more ‘convulsive’ than today’s job churn.  American consumption he notes is gravitating toward goods and services whose production is not easily automated.  Societies increasingly are devoting “a growing share of their income to consumption in sectors where productivity [is] stagnant.”  The idea is that robots can replace fewer things that go into GDP than we think.

As examples he cites medical breakthroughs in new, more expensive treatments rather than cheaper existing treatments, and that child-care work has soared because parents won’t leave kids in the care of a robot.  Over the past decade, “low productivity sectors” including education, health care, social assistance, leisure and hospitality have added nearly 7 million jobs, whereas information and finance, where value added per worker is 5 to 10 times higher, have cut or barely added jobs.

His conclusion: We need a change in priorities.  Instead of worrying about robots destroying jobs, we need to use them more, especially in low-productivity sectors.  While robots may one day replace truck drivers, “it’s more urgent to make existing drivers, now in short supply, more efficient,” and to be more concerned about reducing the labor, and thus the cost of energy, rather than worry about jobs added in areas like solar power.  The alternative, notes Ip, “is a tightening labor market that forces companies to pay ever higher wages that must be passed on as inflation.  And that, he notes, “is a more imminent threat than an army of androids.”


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Industrial automation continues to progress, and nowhere is that happening at a faster clip now than in China.

Robots are making rapid headway in many plants around the world.  Currently South Korea leads in adoption with some 531 robots per 10,000 workers in 2015, followed by Germany at 301, and the U.S. at 176.  At 49 per 10,000, China lags, but is determined to catch up and surpass other nations.  For the first time, in 2013 more robots were sold in China than anywhere else in the world.  Last year, 90,000 robots were installed in China, fully one-third of the world’s total – all in an accelerating effort to counter higher labor costs.

The same fervor that made China a leader in solar panels and high speed rail is now embraced by its planners in the adoption of robots in factories.  And everyone should be concerned.

China has an aging workforce and increasing labor costs, and industrial automation there is crucial.  But as John Roemisch, a VP at robot manufacturer Fanuc America Corp. says, “There’s nothing keeping them from coming after our market.”  As the CEO of IRobot adds, “China has a great history of being an effective fast follower… The question will be, can they innovate?”  To that end, China has three enormous advantages: scale, growth momentum and money, according to a May 7th article in Bloomberg BusinessWeek.

Through a sweeping proposal released in China dubbed “Made in China 2025,” Beijing will focus on automating key sectors of the economy that include car manufacturing, electronics, appliances, logistics and food production.  At the same time, they plan to increase their own production of robots to over 50% of total Chinese sales by 2020.

A Chinese start-up named E-Deodar has developed proprietary technology that allows it to create $15,000 factory robots, a cost about one-third cheaper than foreign ones.  It has mastered technology for servomotors, drivers and control panels to gain a proprietary competitive advantage, and is said to act much like a Silicon Valley startup.  Says it’s General Manager Max Chu, “People ask me, how long can you make robots?” he says. “I say it’s simple, we will make robots until there’s no more people in factories.”

The U.S. is not sitting idle.  We’ve all seen the Roomba vacuums that promise to make domestic life a bit easier.  China and others nations are now collaborating on building them for the global market.   But while building vacuum cleaners is one thing — the industrial goal is here is much bigger.  Amazon, for instance, hopes to build logistics systems that create near-humanless warehouses with packages delivered by drones or driverless vehicles.  JD.com is rushing to automate its business in the quest to replace tens of thousands of warehouse workers and deliverymen.  It’s currently testing drones to deliver packages in rural regions and experimenting with robots to deliver on college campuses, according to Bloomberg.

As its Chief Technology Officer said recently, it’s all about “who can learn… who can get better faster.  We are all just starting out.”

But while this might be the most disconcerting part of all for today’s low-skill worker, an interesting — and completely opposite — counterpoint has been voiced by Wall Street Journal editor Greg Ip.  We’ll provide Ip’s counterpoint in our next and concluding post on the ascendance of robots. Stay tuned…


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In our prior post (“The Evolving Promise of Unbreakable Computer Security”) we suggested that the evolution of quantum computing would make it possible to create virtually unbreakable computer security due to its ability to create almost absurdly difficult encryption through the use of complex prime number “decompositions” that even today’s super-computers could not solve.

As a counterpoint today we offer the opinions of editors at The Economist, offered in the April 8, 2017 issue, in which they suggest that “computers will never be secure,” and that “to manage the risks, [we need to] look to economics rather than technology.”

We’ll let you be the judge as to which opinion might ultimately prevail.

The Economist editors suggest that “computer security” itself is a contradiction in terms.  Hardly a day passes that we don’t read about the latest cyber-attack (we’ve helped several of our ERP clients after they were harassed or held hostage through ransomware attacks).  Recently the central bank of Bangladesh lost $81 million… Yahoo almost torpedoed its sale to Verizon due to massive data breaches… and allegations persist about Russian hacking of the U.S. elections.

Today, there is a huge black market for data theft and extortion tools, including hackers for hire.  And soon enough, the Internet of Things (of which we’ve written frequently) will present even more devices that never expected to be hacked, but are ripe for attack.  The bottom line is “there is no way to make computers completely safe.  Software is hugely complex.”

And perhaps common sense would dictate that when you have millions of lines of code, like Google or Microsoft, errors are inevitable.  The Economist states that “the average program has 14 separate vulnerabilities, each a potential point of illicit entry.”  And after all, we are reminded, there’s the internet, where security was pretty much an afterthought.

So, what to do?  According to the Economist’s editors, it’s all about managing the risk.  Their suggestions include:

  • Start with regulation. If you can’t weaken encryption for just the bad guys, then make sure encryption is strong for everyone.  “The same protection that guards messages in WhatsApp also guards bank transactions and online identities.”
  • Set basic product regulations. They suggest promoting “public health” for computing, with solutions ranging from “internet-connected gizmos” that are updated when flaws are found, to forcing users to change passwords and user names often.  Enforce reporting laws already in place that make companies disclose when they are hacked.
  • Overall, says The Economist, incentives to take security seriously are weak, and the long-established disclaiming of liability by providers may soon bump up against traditional protection and liability laws, especially where computer products become embedded in devices traditionally protected by established liability law. In other words, the courts may one day force the liability issue.  And there’s nothing like the government to come down hard with new rules.
  • Cyber liability insurance. It’s a small but growing market for protecting consumers.  Product companies may soon find buying it preferable to the destructive consequences they might otherwise assume in liability cases.

Finally, they note that when the internet was new, no one took security seriously, and no one objected.  But today’s internet is ubiquitous, and not taking security seriously, given the known risks and consequences, is no longer forgivable.  As the editors conclude, “changing attitudes and behavior will require economic tools, not just technical ones.

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The idea of “quantum computing” has been around for a while, but lately, some very blue-chip sorts of companies have begun investing in it seriously.  Names like HP, Google and Microsoft, to name a few.

Quantum computing is best thought of as the ‘next generation’ of computing technology, in which the weird and dazzling properties of the atomic and sub-atomic worlds govern what a computer is capable of.  Quantum theory was born about a century ago, but its practical use has long been out of man’s reach.  But the day is coming. Everything in the natural world can be described by quantum mechanics – but it operates on a very different plane from the natural order of things we humans have come to know.  And sometimes, quantum properties can act downright… weird.

For example, in computers, the fundamental notion of a “bit” of information is defined by a flow of electric current that, like a switch, is either “on” or “off.”  There’s no confusion, and that foundation allows computers to work from flowing electrons, and software programmers to create code that depends on it.  But in the quantum world, things aren’t so simple.

Without veering off into strange properties and the famous Heisenberg Principle which says that the mere observation of an atomic particle or event can change its very nature (you can determine a particle’s direction of movement or its location, but not both at the same instant)… the bottom line is that a quantum bit can be both on and off simultaneously.  As scientists learn to harness the power of this notion of a ‘qubit,’ it promises to unleash phenomenally more powerful hardware and software than ever seen before.

Which brings us to the future of computing.

One of the most promising possibilities in quantum computing is that of unbreakable security.  The unique properties of this on-while-off status of a qubit gives it the capability of working out prime numbers that, when multiplied together make up ridiculously large primes whose reverse uncoupling (or “decomposition”) is mathematically extremely complex, and is the basis of most modern cryptography in use today.

The new algorithms produced by quantum computing promise to deliver cryptographic solutions that quantum computers can crunch through, but which are well beyond anything that even today’s supercomputers are capable of.

Meanwhile, companies like those mentioned earlier all have research programs for determining how best to harness these quantum capabilities in software and applications.  Early interest has come from governments and defense contractors, not to mention the NSA, as well as a growing number of startups.  These efforts are based on the work of Dr. Peter Shor who, at Bell Labs in 1994, first showed how a quantum computer would be capable of solving the prime riddle.

In the future, that capability would be useful “for all manner of currently intractable problems” notes a recent article in The Economist (March 11, 2017).  Applications including those requiring extremely precise timing, perfectly accurate GPS triangulation and massively complex encryption will likely be among early efforts.

While these machines and software are ultimately among mankind’s greatest engineering challenges, one tends to believe that in the long history of computing, they’re simply the next step on the trail, in the seemingly never ending evolution of the computer.

(Note: In our next post, we’ll present a counterpoint to our “unbreakable security” thinking above, courtesy of the editors at The Economist. Stay tuned…)



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going-viralEvery blogger, web poster and Twitter or Facebook aficionado dreams of the day one of their posts goes viral.  (We wrote of our own brief brush with viral fame back in 2010 with a post on multi-tasking that reached  2,500 hits – still trivial by internet viral-ity standards.)

But as it turns out, going viral is usually not what it appears to be.  When we see a Facebook post with thousands of shares, or a YouTube video with millions of hits, we’re inclined to think that’s the result of countless ‘personal’ shares, “like infected individuals passing along the flu,” as Derek Thomson, author of Hit Makers: The Science of Popularity in an Age of Distraction, noted in a recent article for Time.

Apparently, for a long time no one really knew whether a popular idea or product was truly viral.  It was hard to track precise word-of-mouth buzz.  But online, scientists have been busily studying information as it pings around the Internet, and in 2012 researchers at Yahoo studied the spread of messages on Twitter.

Their conclusion: nothing really ever goes viral.

Thompson notes that more than 90% of messages did not ‘diffuse’ at all.  About 95% of what we see on Twitter comes directly from its source, or from one degree of separation.

Thompson writes: “Popularity on the Internet is still driven by the biggest broadcasters – not by a million 1-to-1 shares, but rather by a handful of 1-to-1 million shares.”  They come from a wide range of blast points –not just the legacy TV companies like NBC, CBS or Fox, but from places like Reddit or, yes, the Kardashians.

While the viral myth is enchanting to writers because it feels so uplifting, promising small-time writers, photographers, artists and videographers a shot at widespread artistic fame, alas, it rings mostly false.  While it might feel good to think of the Internet as a bastion of democracy where anybody can become a star by making something interesting or good enough, it’s not really the case.

In the end, as Derek Thompson says, “virality is a David myth obscuring the fact that the Internet is still run by Goliaths.”


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