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Narrow AI applications such as Google Search and Amazon Alexa are great at solving specific problems, but only as long as you stick to the script.

From self-driving cars to dancing robots in Super Bowl commercials, artificial intelligence (AI) is everywhere. The problem with all of these AI examples, though, is that they’re not really intelligent. Rather, they represent narrow AI – an application that can solve a specific problem using artificial intelligence techniques. And that is very different from what you and I possess.

Humans (hopefully) display general intelligence. We are able to solve a wide range of problems and learn to work out those problems we haven’t previously encountered. We are capable of learning new situations and new things. We understand that physical objects exist in a three-dimensional environment and are subject to various physical attributes, including the passage of time. The ability to replicate human-level thinking abilities artificially, or artificial general intelligence (AGI), simply does not exist in what we today think of as AI.

That’s not to take anything away from the overwhelming success AI has enjoyed to date. Google Search is an outstanding example of AI that most people regularly use. Google is capable of searching volumes of information at an incredible speed to provide (usually) the results the user wants near the top of the list.

Similarly, Google Voice Search allows users to speak search requests. Users can say something that sounds ambiguous and get a result back that is properly spelled, capitalized, punctuated, and, to top it off, usually what the user meant. 

How does it work so well? Google has the historical data of trillions of searches, and which results the user chose. From this, it can predict which searches are likely and which results will make the system useful. But there is no expectation that the system understands what it is doing or any of the results it presents.

This highlights the requirement for a huge amount of historical data. This works pretty well in search because every user interaction can create a training set data item. But if the training data needs to be manually tagged, this is an arduous task. Further, any bias in the training set will flow directly to the result. If, for example, a system is developed to predict criminal behavior, and it is trained with historical data that includes a racial bias, the resulting application will have a racial bias as well.

Personal assistants such as Alexa or Siri follow scripts with numerous variables and so are able to create the impression of being more capable than they really are. But as all users know, anything you say that is not in the script will yield unpredictable results.

As a simple example, you can ask a personal assistant, “Who is Cooper Kupp?” The phrase “Who is” triggers a web search on the variable remainder of the phrase and will likely produce a relevant result. With many different script triggers and variables, the system gives the appearance of some degree of intelligence while actually doing symbol manipulation. Because of this lack of underlying understanding, only 5% of people say they never get frustrated using voice search.

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A massive program like GPT3 or Watson has such impressive capabilities that the concept of a script with variables is entirely invisible, allowing them to create an appearance of understanding. Their programs are still looking at input, though, and making specific output responses. The data sets at the heart of the AI’s responses (the “scripts”) are now so large and variable that it is often difficult to notice the underlying script – until the user goes off script. As is the case with all of the other AI examples cited, giving them off-the-script input will generate unpredictable results. In the case of GPT-3, the training set is so large that eliminating the bias has thus far proven impossible.

The bottom line? The fundamental shortcoming of what we today call AI is its lack of common-sense understanding. Much of this is due to three historical assumptions:

• The principal assumption underlying most AI development over the past 50 years was that simple intelligence problems would fall into place if we could solve difficult ones. Unfortunately, this turned out to be a false assumption. It was best expressed as Moravec’s Paradox. In 1988, Hans Moravec, a prominent roboticist at Carnegie Mellon University, stated that it is comparatively easy to make computers exhibit adult-level performance on intelligence tests or when playing checkers, but difficult or impossible to give them the skills of a one-year-old when it comes to perception and mobility. In other words, often the difficult problems turn out to be simpler and the apparently simple problems turn out to be prohibitively difficult.
• The next assumption is that if you built enough narrow AI applications, they would grow together into a general intelligence. This also turned out to be false. Narrow AI applications don't store their information in a generalized form so it can be used by other narrow AI applications to expand the breadth. Language processing applications and image processing applications can be stitched together, but they cannot be integrated in the way a child effortlessly integrates vision and hearing.
• Lastly, there has been a general feeling that if we could just build a machine learning system big enough, with enough computer power, it would spontaneously exhibit general intelligence. This hearkens back to the days of expert systems that attempted to capture the knowledge of a specific field. These efforts clearly demonstrated that it is impossible to create enough cases and example data to overcome the underlying lack of understanding. Systems that are simply manipulating symbols can create the appearance of understanding until some “off-script” request exposes the limitation.

Why aren’t these issues the AI industry’s top priority? In short, follow the money.

Consider, for example, the development approach of building capabilities, such as stacking blocks, for a three-year-old. It is entirely possible, of course, to develop an AI application that would learn to stack blocks just like that three-year-old. It is unlikely to get funded, though. Why? First, who would want to put millions of dollars and years of development into an application that executes a single feature that any three-year-old can do, but nothing else, nothing more general?

The bigger issue, though, is that even if someone would fund such a project, the AI is not displaying real intelligence. It does not have any situational awareness or contextual understanding. Moreover, it lacks the one thing that every three-year-old can do: become a four-year-old, and then a five-year-old, and eventually a 10-year-old and a 15-year-old. The innate capabilities of the three-year-old include the capability to grow into a fully functioning, generally intelligent adult.

This is why the term artificial intelligence doesn’t work. There simply isn't much intelligence going on here. Most of what we call AI is based on a single algorithm, backpropagation. It goes under the monikers of deep learning, machine learning, artificial neural networks, even spiking neural networks. And it is often presented as “working like your brain.” If you instead think of AI as a powerful statistical method, you'll be closer to the mark.

Charles Simon, BSEE, MSCS, is a nationally recognized entrepreneur and software developer and the CEO of FutureAI. Simon is the author of Will the Computers Revolt?: Preparing for the Future of Artificial Intelligence, and the developer of Brain Simulator II, an AGI research software platform.

Document capture, the digitizing of paper and making them searchable, is decades-old tech. But everybody's making new document capture tools, including OpenText, which dusted off its tools and is adding AI and machine learning to them as part of its broader Content Cloud Editions 21.4 quarterly feature release at the end of October.

Box and Adobe have recently built document capture tools, and even Salesforce plans to release one next year. It's no coincidence, said Forrester Research analyst Cheryl McKinnon, as AI and machine learning have proven to be great leaps forward to augment optical character recognition that often had to isolate certain zones of a document and data points such as invoice numbers or dollar amounts to be most effective. AI and machine learning (ML) can look at a whole document and better process its contents.

"We had all this useful data locked up in what I like to jokingly call 'dumb file formats,' and paper is the dumbest," McKinnon said. "Things like machine learning and AI are coming into the mix. You don't need to be worried about where on the document to go find the invoice number. The systems are trained enough where it's going to recognize invoice numbers either with computer vision or other kind of text analytics."

OpenText's new Intelligent Capture adds AI to its document capture capabilities in Content Cloud Editions. Executive vice president and chief product officer Muhi Majzoub said that a couple of other tech trends have influenced vendors to invest in document capture during the past two years, including remote work and smartphones. Tuning apps and algorithms for smartphone cameras instead of scanners was a customer need as people left offices en masse last year, something that looks to be permanent for some companies.

"We have done a lot of work for mobile devices, but we are not completely done -- that's an area that continues to improve, and we are innovating," Majzoub said. "Especially when it comes to travel and receipts and expenses. Nobody has access to a physical scanner and we're all working at home."

Salesforce, Microsoft 0365 integrations added

Also included in the fourth-quarter updates is Intelligent Viewing, a feature that applies AI and ML to scanned document images and extracts data and redacts information to enable search, yet maintain information governance policies. The Return-to-Work Playbook Management helps organizations quickly create, approve and distribute their operational restart plans and procedures, in the same vein as Salesforce Work.com features.

Other new features in OpenText Content Cloud Editions 21.4 are OpenText and Documentum integrations with Salesforce Sales Cloud and Salesforce Marketing Cloud, as well as Microsoft Office 365 and Teams. These integrations enable users to share documents in those application environments while maintaining security, data governance and version control rules set in OpenText.

"From a metadata point of view, it's also kind of interesting," McKinnon said. "If you wanted to use Salesforce as your system of record for official customer numbers or project numbers, that can be transferred into the metadata the content management system has. So you have that common identifier, no matter what system the customer data or documents related to that customer is in."

Don Fluckinger covers enterprise content management, CRM, marketing automation, e-commerce, customer service and enabling technologies for TechTarget.

Phishing Attempts Grew by 640% Last Year

WATERLOO, Ontario, Feb. 18, 2020 /PRNewswire/ -- OpenText™ (NASDAQ: OTEX) (TSX: OTEX) today issued the 2020 Webroot Threat Report, highlighting not only the agility and innovation of cybercriminals who continue to seek out new ways to evade defenses, but also their commitment to long-established attack methods. Most notably, Webroot observed a 640 percent increase in phishing attempts and a 125 percent increase in malware targeting Windows 7®. The report is derived from metrics captured and analyzed by Webroot's advanced, cloud-based machine learning architecture: the Webroot® Platform.

"In the cybersecurity industry the only certainty is that there is no certainty, and there is no single silver bullet solution," said Hal Lonas, Senior Vice President and CTO, SMB and Consumer, OpenText. "The findings from this year's report underline why it's critical that businesses and users of all sizes, ensure they're not only protecting their data but also preparing for future attacks by taking simple steps toward cyber resilience through a defense-in-depth approach that addresses user behavior and the best protection for network and endpoints." 

Download the full report here.

Notable Findings:

• Phishing URLs encountered grew by 640 percent in 2019. 
  • 1 in 4 malicious URLs is hosted on an otherwise non-malicious domain.
  • 8.9 million URLs were found hosting a cryptojacking script.
  • The top sites impersonated by phishing sites or cybercriminals are Facebook, Microsoft, Apple, Google, PayPal and DropBox.
  • The top five kinds of websites impersonated by phishing sites are crypto exchanges (55%), gaming (50%), web email (40%), financial institutions (40%) and payment services (32%).
• Malware targeting Windows 7® increased by 125 percent.
  • 93.6 percent of malware seen was unique to a single PC – the highest rate ever observed.
  • 85 percent of threats hide in one of four locations: %temp%, %appdata%, %cache%, and %windir%, with more than half of threats (54.4%) on business PCs hiding in %temp% folders. This risk can be easily mitigated by setting a Windows policy to disallow programs from running from the temp directory.
  • IP addresses associated with Windows exploits grew by 360 percent, with the majority of exploits targeting out-of-date operating systems.
• Consumer PCs remain nearly twice as likely to get infected as business PCs.
  • The data reveals that regions most likely to be infected also have the highest rates of using older operating systems.
  • Of the infected consumer devices, more than 35 percent were infected more than three times, and nearly 10 percent encountered six or more infections.
  • The continued insecurity of consumer PCs underscore the risk companies face in allowing employees to connect to business networks from their personal devices.
• Trojans and malware accounted for 91.8 percent of Android™ threats.

Explore all the findings here.

The 2020 Webroot Threat Report presents analysis, findings and insights from the Webroot Threat Research team on the state of cyber threats. The report analyzed samples from more than 37 billion URLs, 842 million domains, 4 billion IP addresses, 31 million active mobile apps, and 36 billion file behavior records. The statistics presented in this annual threat report are derived from metrics automatically captured and analyzed by the Webroot® Platform, our advanced, cloud-based machine learning architecture. This system provides proactive protection for users and networks against both known and zero-day, never-before-seen and advanced persistent threats. Threat intelligence produced by the platform is used by Webroot┬« endpoint security products and by technology partners through Webroot BrightCloud® Threat Intelligence Services.

The Webroot┬« Platform harnesses the cloud and artificial intelligence to protect businesses and individuals against cyber threats. We provide endpoint protection, network protection, and security awareness training solutions purpose built for managed service providers and small businesses. Webroot BrightCloud® Threat Intelligence Services are used by market leading companies like Cisco, F5 Networks, Citrix, Aruba, A10 Networks, and more. Leveraging the power of machine learning to protect millions of businesses and individuals.  Learn more at webroot.com.

ECM market Survey 2020

This research report is equipped with the information categorized for Enterprise Content Management ECM Market by parameters such as players, brands, regions, types and application. The report also details the information about the global market status, competition landscape, growth rate, future trends, market drivers, challenges, opportunities and porter’s forces analysis with respect to these elements.

Get a PDF Sample Copy @ 
https://www.marketresearchvision.com/request-sample/415884

The following manufacturers are covered in this report:, Alfresco Software, Inc., Everteam, Fabasoft, Hyland Software, Inc., IBM Corporation, Laserfiche, M-Files Corporation, Microsoft Corporation, Newgen Software, Inc., Opentext Corporation, Oracle Corporation, Xerox Corporation

Product Type Segmentation, Content Workflow, Document Management, Imaging and Capturing, Web content Management, Records Management, ,

Industry Segmentation, BFSI, Government, Manufacturing, Telecom and IT, Consumer Goods and Retail, ,

The Enterprise Content Management ECM market research report has been compiled through extensive primary research through interviews, surveys, and observations of seasoned analysts and secondary research. The report also features a complete qualitative and quantitative assessment by analyzing data gathered from industry analysts and Enterprise Content Management ECM market participants across key points in the industry’s value chain.

The report also provides exhaustive PEST analysis for all five regions namely; North America, Europe, APAC, MEA and South America after evaluating political, economic, social and technological factors affecting the market in these regions.

PaperFree partner M-Files recently announced a breakthrough in enterprise content management - the ability to access ALL enterprise documents within a company's Office 365 installation.  This is made possible with several new M-Files advancements that allow it to integrate with SharePoint Online, Outlook, and Teams seamlessly.  This new integration makes data access even easier for M-Files users - now all critical information is easy to find, no matter where it resides.  And, now that data is available in commonly-used applications, users enjoy even faster lookup and increased productivity.  These new integrations also come at a time where M-Files is expanding functionality dramatically with the recent M-Files for Salesforce connection.

M-Files is a notable ECM solution because of its unique intelligent metadata process that uses artificial intelligence to seamlessly connect documents and content.  Information is found by what it is, not by where it is.  This means that all information relating to a document, customer file, or project is immediately available and connected, no matter the need for accessing the data.  And, data is safe with configurable access.

M-Files is an ideal solution for many enterprises looking for more advanced management of their data.  PaperFree is happy to evaluate your ECM needs and show you how we can revolutionize your processes, workflows, and data management with M-Files.

This article was based on a July 1, 2019 M-Files press release.

Google recently announced the availability of its 'Code with Google' utility - a new tool for teaching school-age children the basics of computer coding.  It works with a combination of Google's own curriculum and other resources, and is free.  The resource was created to make coding learning tools available in a educational environment where tech skills are stressed, but rarely taught.  It is often the more affluent school districts that have the resources to create coding courses - and the talent in less well off districts is left behind.  Google hopes to bridge this gap, especially with the availability of affordable Chromebooks for schools.

By making resources free and hardware affordable, Google hopes to inspire the next generation of tech developers to build and pursue their talents.  And, with their suite of cloud-based tools it's becoming easier than ever to access knowledge and learning.

To celebrate the program, Google also gifted a million dollar grant to the Computer Science Teachers Association.  The program also offers the potential of scholarships, internships, and other work learning opportunities to participants.

This article was based on a July 8, 2019 Tech Crunch article by Darrell Etherington.

PaperFree partner Microsoft recently shared news of how its Azure cloud product is being used to share and analyze data that researchers have collected in an effort to solve the mysteries of sudden infant death syndrome (SIDS) and childhood cancers.

Microsoft's first partnership, with Seattle Children's Research Institute, aims to draw understanding about the causes of SIDS and hopefully methods to prevent it.  This cause is close to the Microsoft family - chief data analytics officer John Kahan lost his son to it.  The team at Microsoft started their task with public data about 26 million births and deaths, and then studied nearly 100 parameters about every child born in the US over a six year span.  With the help of the Azure platform, the team were able to make several important connections between datasets and increased chances of SIDS occurring.  Then, the data was handed over to the Seattle Children's Research Institute for expert analysis.

This team effort has since resulted in an impressive collaborative genomics database between Seattle Children's and Microsoft data scientists.  This database is also shared with top SIDS researchers around the world.  The result of this partnership has been a peer-reviewed paper published in the medical journal Pediatrics - in which researchers were able to make a connection between SIDS and maternal smoking during pregnancy.  Azure advanced modeling techniques were used to draw this conclusion, and the researchers hope to use sequenced whole genomes as additional data in their Azure platform.  Ultimately, Azure may be a key tool in finally understanding the mystery of SIDS and how to prevent it.

Azure is also in use for pediatric cancer research.  St. Jude Children's Research Hospital recently developed the St. Jude Cloud with the help of Microsoft and DNAnexus.  This platform works to make genomics data sharing and collaboration much easier between researchers.  By developing the platform to analyze data against the human genome template, connections can be more easily made.  Now, 450 institutions across 16 countries have instant access to critical research data to help them solve childhood cancer.

Microsoft's developments are in nearly every medical office and research institution, offering them a unique opportunity to create effective cloud and AI-based solutions for healthcare needs and research.

This article was based on a May 21, 2019 Microsoft blog post by Peter Lee

Riviera Beach, a city of 6 million on Florida's eastern coast, recently found itself in the grip of hackers who brought down its 911 and email system.  Their attack started with a simple email to the police department in May, whose attachment contained a virus that quickly infected computers on the network.  However, what the city did next is what's newsworthy - they paid the $600,000 ransom to the hackers to get their system back.  At this time, it's unknown if the hackers held up their end of the deal.  The city is also in the process of replacing computers and working with security experts to recover from the attack.  It is reported that the attack on Riviera Beach is part of a larger operation to target US cities, which has cost taxpayers millions of dollars.

This case highlights how ill-prepared municipalities are to defend themselves against cyberattacks.  Many have been slow to respond to the urging of government agencies to lock down their systems; barriers such as budgets, manpower, or poor city council support make it difficult to put any protections in place.  But, with more and more cities losing data and systems to cyberattacks, something needs to be done.

Small cities and other government entities (such as hospitals) are a promising target to hackers - they lack the resources to fend off attackers, but may find it more economical to simply pay a ransom than hire security experts.  This is what hackers are banking on, and they attack city after city until they get something to stick.  There is additional concern that these attacks may be a part of something larger that is looking for holes in our safety net.  Such vulnerabilities could lead to something larger, such as a large scale attack on power grids that could cripple multiple cities and emergency services in one go.  Experts hope that it doesn't take a catastrophe to get cities to take notice and urge them to upgrade their security measures now.

This article was based on a June 20, 2019 Business Insider article by Sinead Baker.

PaperFree partner M-Files recently announced an exciting new addition to their lineup - M-Files for Salesforce.  This product efficiently integrates M-Files functionality into the popular Salesforce interface, adding document management abilities as well as enhanced compliance and oversight.  This added capability improves productivity because Salesforce users no longer have to go search a separate repository for information relating to a customer account - their focus can remain on accounts, opportunities, and deals in progress.  Documents related to a customer account or project in process are simply listed alongside other Salesforce information.  Among a multitude of features the new product offers:

• Cloud and on-premise content repositories
• Version history
• Added security
• Collaboration features
• Workflows
• eSignatures
• Compliance support

M-Files for Salesforce also skips the hassle of importing data by integrating with popular content storage utilities such as Microsoft OneDrive, SharePoint, Dropbox, Google Drive, and more.  This integration means that the linked documents in Salesforce are always up to date and available.  Like the M-Files content management product, M-Files for Salesforce uses AI to extract information and classify documents intelligently so users don't have to spend their time classifying and organizing documents in a repository.  This saves time in filing and retrieving information, which returns increased productivity among workers.

This article was based on a June 11, 2019 M-Files press release

More and more retailers are turning towards a cashless model by accepting cards and other electronic payments...and nothing else.  This is done to speed convenience - surely tapping your phone on a reader to get your morning bagel sandwich is faster than digging a $5 bill out of your wallet, getting change, and oh, make sure to leave a buck in the tip jar.  Some retailers also claim that cashless business is safer and more economical because there's nothing to steal, no armored truck deliveries, no taking an employee off the line to check cash in under dual custody, and no bank runs for change (a day's worth is quite heavy...).  However, some are starting to raise alarm that the very currency that has existed longer than just about every tech we rely on daily is no longer good enough to buy your morning smoothie.

The Philadelphia City Council recently discussed this issue, in the context that not everyone chooses to...or can...pay for things by card or other electronic means.  Ultimately they passed a local ordinance that requires businesses to accept cash.

There are many Americans (approximately 8.4 million) who don't have access to banking services and they often hail from lower incomes.  For these people, credit factors can be a barrier to opening an account, as are minimum balance requirements and even physically getting to the bank.  The homeless don't have addresses or enough available identification to bank.  Many simply live solely on cashed checks.  The concern here is that as more and more stores become cashless, those who pay in cash will have less access to the goods and services they are happy to pay for.  There is also concern that retailers would be further divided into where the rich shop, and where the poor shop.

And then there's kids, who across the board rarely have access to a debit card to pay for a soda.  There's also many people who choose to live off the grid and purposefully don't have bank accounts or credit cards.  Fortunately, more governments are becoming aware of the issue and are addressing it through local ordinances.  Several states and municipalities have started requiring that cash be accepted at businesses.

Though there's dissent to the idea of governments saying what private businesses can and can't do, there has fortunately emerged a middle ground that addresses this - gift cards.  The Mercedes-Benz Stadium in Atlanta has converted to a cashless concessions model, and supplemented cash payers by installing Visa debit card kiosks through the stadium.  There, spectators turn their cash into card payments that could still be used outside of the stadium.  Though its usage is low, the kiosks account for kids, foreign visitors, and more with little downside.  Such installations could be a compromise to allow all access to cashless stores while respecting the independence of businesses to do business as they like.

This article was based on a May 28, 2019 CNet article by Erin Carson