Mit Daten in die Zukunft blicken

Fraunhofer IPT High Performance Networked Adaptive Production (Hannover Fair 2018)

Wer sich den Anforderungen der Digitalen Transformation stellen will, muss in der Lage sein, in die Zukunft zu blicken. Nein, nicht mit Hilfe einer Kristallkugel oder mit Tarockkarten. Big Data lässt sich nur mit leistungsfähigen Analysesystemen beherrschen. Wobei hier eine Art „digitaler Dreisprung“ zu erkennen ist: Von der beschreibenden über die vorausschauende Analyse bis hin zu Empfehlungssystemen. Oder, um die englischen Termini zu verwenden: „Descriptive Analytics“, „Predictive Analytics“ und „Prescriptive Analytics“.

Deskriptive, oder beschreibende Analyse entspricht dem klassischen Reporting, wie er von alters her betrieben wird.  Sie beschreibt den Status quo, also die historische Entwicklung des Unternehmens, zum Beispiel anhand von Zielabweichungen. Die darauf aufbauende „diagnostische Analyse“ versucht, aus diesen Ergebnissen Ursachen aufzuspüren, zum Beispiel warum liegen die Kosten über Plan oder warum stockt der Abverkauf? Diese so genannte Plan-Ist-Vergleiche sind heute das Rüstzeug jedes Controllers, und sie werden es auch in Zukunft bleiben. Allerdings lassen sich gerade solche Aufgaben heute weitgehend automatisieren.

Die durch die Automation gewonnene Zeit können Unternehmen in Zukunft für die vorausschauende Analyse, also für „Predictive Analytics“ nutzen – und sie werden sie nutzen müssen, wenn sie mithalten wollen. Es gibt eine Fülle von Software-Tools, die in der Lage sind, aus den Unmengen von Daten Muster zu erkennen oder Zusammenhänge zwischen scheinbar nicht verwandten Daten zu ziehen. Diese Software muss das Unternehmen nutzen und beherrschen, um mit Hilfe der entsprechenden Algorithmen nicht nur Prognosen zu wagen, sondern um die Eintrittswahrscheinlichkeit bestimmter Ereignisse zu berechnen und die Risikoverteilung zu ermitteln.

Leider erfolgen Finanzplanung (GuV, Bilanz & Cash Flow) und operative Planung (Absatz, Produktion, Personal) in den meisten Unternehmen getrennt. Sie haben deshalb oft keinen echten Bezug zu den Treibern des operativen Geschäfts. Mangelnde Berücksichtigung strategischer Ziele können aber zu unterschiedlichen Erwartungshaltungen auf verschiedenen Ebenen innerhalb des Unternehmens und damit zu erheblichem Abstimmungsaufwand führen.

Schneller und effizienter ist es, die auf das Geschäftsmodell abgestimmte Werttreiberplanung, wie sie in vielen Unternehmen heute eingesetzt wird, direkt mit Predictive Analytics zu verknüpfen. So lassen sich wesentlich bessere Voraussagen machen, die Auswirkungen auf das operative Geschäft werden klarer dargestellt.

Ist man aber erst einmal so weit, dann bietet sich der nächste logische Schritt von selber an: Die Automatisierung von unternehmerischen Entscheidungen. Womit wir bei „Prescriptive Anaytics“ angelangt wären. Weiterlesen

Veröffentlicht unter Digitale Transformation, IoT, Predictive Analysis, Smart Industry | Verschlagwortet mit , , , , , , , , , | Hinterlasse einen Kommentar

Donald Trump, Typoglycemiast: Elected to lead, not to proofread!

Jsut as lnog as yuo can uerdtsnad tihs its oaky!

Just about everything about Donald Trump – his hairdo, his sixth-grade vocabulary, his inability to focus on complex issues, his tendency to grope first and think later – have been fodder for journalistic witticisms in the past, but leave it to the Washington Post’s Dave Nakamura to add another wrinkle to the list of the President’s basic deficiencies: spelling.

Of course, since the now legendary “covfefe” affair, the world has grown used to Trump making up not only facts, but entire words. Some observers say that the number of typos in his tweets has been growing recently; a sign that he’s beginning to crack under strain? “Special Council is told to find crimes, wether crimes exist or not”, he typ(o)ed in the wee hours of last Wednesday, going on to misspell “counsel” three times and to commit five other errors in the span of 280 characters.

As someone who would be completely lost (and sometimes still is) without the spell checker in Microsoft Word, I actually sympathize with the guy. Still, given the rest of the muddle that marks today’s White House, I find it another cause to worry . Is he simply too lazy to check his tweets before pushing the “send” button? Is old-age creeping up on him, along with numbness in the fingertips and lack of motor control? Or is this just another proof of his general sloppiness and unwillingness to pay attention to detail when making important policy decisions?

And then there is the question that Americans of all stripes and colors should be asking themselves anxiously: Does the President suffer from dyslexia? Weiterlesen

Veröffentlicht unter An American in Germany, posts in English, Sprache | Verschlagwortet mit , , , , , , , , , , , | Hinterlasse einen Kommentar

Who Wants to be a Millionaire? I Did!

 

Perhaps I have been leading a sheltered life lately, but it is years since I ran across one of those infamous “Nigerian Scams”. Someone overseas offers you a share in a large sum of money or a payment on the condition you help them transfer money out of their country. They used to be everywhere, but I haven’t seen any for quite awhile.

So maybe that’s why my alarm bells didn’t go off at once when I received an invitation by Michael Cardozo to befriend him on Facebook. I did, however, check his Facebook page before responding and found – nothing! No information about himself, no posts, no likes. Just the picture of an thin, elderly guy in a business suit with glasses and a toothy grin and the message: “Greeting, Mr. Tim, how are you doing today?”

For some reason I resisted my normal impulse to simply delete this budding conversation, and instead replied as follows:

Dear Mike

I don’t normally respond to friend requests from people who refuse to share any information about themselves. Why should I?

I suggest you let your pants down at least a little bit so people know what they’re getting into by becoming FB friends with you.

And that’s how I almost became a multi-millionaire. Weiterlesen

Veröffentlicht unter Allgemein, Banken und Facebook, Fake News, posts in English, Social Web | Verschlagwortet mit , , , , , | Hinterlasse einen Kommentar

What Price the Road?

Source: Library of Congress Prints and Photographs Division Washington, D.C. 20540 USA http://hdl.loc.gov/loc.pnp/pp.print

Toll systems in use around the world are hopelessly stuck in the analog age. By using intelligent IoT-based metering governments just might be able to keep pace with rising numbers of vehicles as ride-sharing and electric cars take off.

Toll roads go back a long way and have existed for at least the last 2,700 years. Records show that tolls had to be paid by travelers using the Susa–Babylon highway under the Assyrian regime of King Ashurbanipal, who reigned in the 7th century BC. In 14th century England, some of the most heavily used roads were repaired with money raised from pavage grants, a toll for the maintenance or improvement of a road.

In early US history, many individual citizens would maintain nearby stretches of road and collect a fee from people who used them. Eventually, companies were formed to build, improve and maintain a particular section of roadway, and tolls were collected to finance the enterprise. These private ‘turnpikes’ were business corporations that built and maintained a road for the right to collect fees from travelers. Turnpikes left important social and political imprints on the communities that created and supported them, but they seldom turned a profit.

There were three especially important episodes of toll road construction: the turnpike era of the Eastern United States from 1792 to 1845, the plank road boom 1847 to 1853, and the toll road of the Far West between 1850 and 1902. Political sentiment eventually turned against them, and the Federal Highway Act of 1916 barred the use of tolls on highways receiving federal money.

The prominence of the toll model increased with the rise of the automobile, and many modern tollways all over the world charge fees for motor vehicles exclusively.

In recent years, tolls have been used as way to ease traffic jams in inner cities. In 2003 Ken Livingstone, then London’s mayor, introduced a system called the Congestion Charge Zone (CCZ). Motorists pay at least £11.50 a day ($15.20) to drive into the center of town. At first, the system seemed to work wonderfully: the number of cars entering central London fell by almost a quarter, but since about 2012 the numbers have been creeping up again. One reason is that delivery trucks and taxis are clocking up more miles within the zone. Another is the spread of bus lanes reserved for public transport – especially the famous red London double-deckers. Today, more time is being lost to gridlock than before the introduction of the CCZ. According to a report in the business magazine The Economist, the average vehicle speed in central London fell from 32kph in 2013 to 28.5kph in 2016. Weiterlesen

Veröffentlicht unter Allgemein, autonomous driving, IoT, Mobilität | Verschlagwortet mit , , , , , , , , | Hinterlasse einen Kommentar

Vor 22 Jahren: Wasser Marsch

Dieser Beitrag erschien am 28. Februar 1995 im Cole-Blog.

An heißen Sommertagen gehe ich gerne mit meiner kleinen Tochter mittags auf die Isar-Insel zum baden. Dazu müssen wir den Fluß allerdings durchwaten, der mir an dieser Stelle etwa bis zum Nabel geht. Vor kurzem stehe ich da, Picknickkorb auf der Schulter, Wasser bis zum Bauch – da klingelt das E-Netz-Handy. Mit der freien Hand angelte ich das Ding aus der Tasche, hob ab und hatte Renate Knüfer von der Firma Quarterdeck an der Strippe, die mich fragte, wie es mir ginge. „Naß“, meinte ich und hatte einige Mühe, Sie davon zu überzeugen, daß ich wirklich aus der Isar aus mit ihr telefonierte.


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Self-driving cars: Getting There

Autonomous vehicles are disrupting traditional business models within one of the world’s largest industries and it’s happening much sooner than anyone expected. What are the forces behind the push for self-driving cars? Is the necessary road infrastructure in place, or do we still need to build it? What happens, if an autonomous vehicle needs to make life-or-death decisions? What, in effect, are the possibilities – and the risks – involved when humans hand over control to robo-chauffeurs?

“Four years“. That was the answer given by Jensen Huang, CEO of Nvidia early last year when he was asked how long it would take for artificial intelligence to enable fully automated cars. And then a funny thing happened. Suddenly, self-driving vehicles began to crop up on public roads all over the place.

At the Barcelona Motor Show in May, Audi unveiled the 2018 Audi A8, which it claimed as the world’s first production car to offer Level 3 autonomy. Level 3 means the driver doesn’t need to supervise things at all, so long as the car stays within certain guidelines. In Audi’s case that means never driving faster than 60kmph (37 mph). Audi has billed this feature as the AI Traffic Jam Pilot.

In the US, Las Vegas became the first city in America to have a self-driving shuttle operating in real-time traffic. However, on its first day of service in downtown Las Vegas, the shuttle collided with a truck. The driverless bus was not able to back off when the truck was backing into the alley so, technically at least, the human driver caused the crash, not the shuttle.

In September, General Motors showcased the third generation of its autonomous Chevrolet Bolt, which they developed jointly with recently-acquired Cruise Automation, headquartered in San Francisco. Kyle Vogt, the CEO of Cruise Automation, called it the “first production model self-driving car in the world”.

The self-driving vehicle is something that’s time has come much faster than anyone expected. For Jensen Huang and Nvidia it means big bets are paying out even sooner than they’d hoped. The company has invested heavily in research involving machine learning, which Huang says is the “bottom-up approach to artificial intelligence” – and probably the most promising technology today. Machine learning requires the processing of huge amounts of data, and as it turns out, the company’s computational graphics processing units (GPUs) can do the job both faster and using less energy than traditional central processing units (CPUs) that power most desktops, laptops and mainframe computers today. Weiterlesen

Veröffentlicht unter autonomous driving, IoT, Künstliche Intelligenz | Verschlagwortet mit , , , , | Hinterlasse einen Kommentar

IoT Goes Fishing

Aquabyte, a fish-farm monitoring startup, has developed a smart camera system and web dashboard. The solution consists of a smart camera system and web dashboard that utilizes computer vision technology. The camera is installed on a fish farmer’s net pen, and real-time farm metrics can be accessed via the web dashboard. Underwater 3D cameras and gauge parameters of temperature and oxygen help track the critical data. Typical metrics that Aquabyte’s cameras and machine learning algorithms will track include lice count, biomass estimation, appetite detection, and feed calculations.

„The development of computer vision over the past couple years along with the advent of deep learning has opened up dramatic opportunities to build new vision-related products that can solve very practical, real world problems,“ said Bryton Shang, Founder and CEO of Aquabyte. „The same computer-vision models I worked on for tissue cancer diagnosis are applicable in a way that can transform the fish farming industry and the future of protein consumption around the world.“

Fish farming is the fastest growing sector of food production in the world with more fish being farmed than beef, representing nearly $160B in yearly production. The industry is rapidly expanding, with experts anticipating that protein consumption will increase world-wide by at least 50 percent by 2050. One of the largest challenges in filling the gap between current supply and projected demand is driving down the cost of feed, which currently represents 50 percent of the cost of fish farming.

Veröffentlicht unter Digitale Transformation, IoT | Verschlagwortet mit | 1 Kommentar

Mozilla Announces Project Thing

Mozilla, the maker of the popular Firefox web browser, wants to get its foot into the door of IoT. With this in mind, the not-for-profit organization founded in 1998 by members of Netscape, has announced Project Thing, a gateway system that will allow a community of makers, testers, contributors, and end-users to effectively create their own private Internet of Things and to control devices and machines directly from the web.

On its blog, Mozilla points out that the lack of a single standard for connecting various devices in a major roadblock on the way to successful IoT implementation. The author writes: 2 If the future of connected IoT devices continues to involve proprietary solutions, then costs will stay high, while the market remains fragmented and slow to grow. Consumers should not be locked into a specific product, brand, or platform. This will only lead to paying premium prices for something as simple as a ‘smart light bulb’.”

Mozilla’s solution is to provide a decentralized network using open standards and frameworks, allowing almost anyone to build a Things Gateways using such popular device as the Raspberry Pi, small single-board “general purpose computer” designed in the United Kingdom and widely used in areas such as robotics. The setup process provides a secure URL that can be used to access and control your connected devices from anywhere. The system now offers the ability to use the microphone on your computer to issue voice commands, as rules engines and a floor-plan view to lay out devices on a map of a home or factory.

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Ein Handy für den Einkaufswagen

Dieser Beitrag erschien am 14. Januar 1995 im Cole-Blog.

Man gewöhnt sich schon verdammt schnell an die Dinger. Das fiel mir auf, als ich im Spätnovember zur Comdex 94 flog und bei der Ankunft entdeckte, dass ich ohne nachzudenken und völlig selbstverständlich mein D-Netz-Handy eingepackt hatte. Dabei gibt es in den Staaten gar keinen digitalen Mobilfunk – noch nicht, jedenfalls. Von wegen Amerika, du hast es besser…


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Platz für ein Handy ist in der kleinsten Hütte

Dieser Beitrag erschien am 12. Januar 1995 im Cole-Blog.

D-Netz-Telefone sind billig wie nie: 389 Mark bei Vobis für den Motorola-Knochen! Kein Wunder, daß der Trend zum Zweitgerät in vollem Gange ist. Sogar meine Frau, sonst eher skeptisch gegenüber dem Segen moderner Telekommunikation, hat es jetzt erwischt. Für ihren motorisierten Einkaufswagen (einen Fiat 500 als Auto zu bezeichnen fällt mir irgendwie schwer) schaffte sie sich ein Motorola-Handy samt Schwanenhals-Halterung und Stromanschluss via Zigarettenanzünder an. Merke: Für ein Mobiltelefon ist in der kleinsten Hütte Platz.


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Veröffentlicht unter Allgemein | Hinterlasse einen Kommentar