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Voice Recognition Changes the Wireless World, Business and Industry Trends Analysis

With the advent of voice recognition via Siri, Apple’s virtual personal iPhone assistant, the wireless market changed irrevocably.  Siri not only translates spoken words into text in the form of e-mails, text messages and reminders, it responds to voice commands for such tasks as making phone calls, and it searches the internet for answers to spoken questions.  Siri created a major boost to both business and consumer interest in voice recognition.  
Significant advancements in voice recognition on the latest smartphone software from Microsoft, Apple and other leading firms continue to be introduced.  Using technology originally developed by Nuance Communications as an app, Siri and similar technologies turn voice recognition capability into a mobile everyday tool.  It understands natural language including colloquialisms and some nuances of context.  For example, ask Siri “Will the weather be nice?” and the response might be “No, probably not so nice today through this Wednesday,” along with the display of the local weather forecast for the next six days.  Ask it to find the calorie count in a Big Mac and Siri searches online for nutritional information from McDonald’s and displays it.
Siri continues to evolve with subsequent updates to Apple’s mobile operating system.  Siri’s voice can now be either male or female, there are new animations, and the system has faster response times.  In addition, Siri checks more sources for answers to queries, and performs more tasks such as returning calls, voicemail playback and controlling iTunes Radio.  This technology has been incorporated in Apple’s HomePod digital assistant, intended to compete with similar products pioneered by Google and Amazon.  Most importantly, these technologies rely on artificial intelligence and machine learning in order to continuously improve accuracy and capabilities.
Smartphones are only the beginning of the voice recognition revolution.  This capability is rapidly being added to all types of electronics, appliances and much more.  Voice recognition is already available in advanced entertainment systems in many automobiles.  The fuel for this trend will be state-of-the-art technologies that are available to third-party developers, including Microsoft’s Cortana, Google’s Home and Amazon’s Lex (Alexa, which powers the extremely popular Amazon Echo digital assistant device.)
The newest smartphones have cutting-edge cameras capable of scanning 3-D objects.  Samsung and Apple both offer models (the Galaxy and the iPhone respectively) with cameras that can scan faces to unlock phone screens, rather than relying on fingerprint recognition or a manually typed passcode.  In the near future, smartphone cameras will be able to scan text and translate it into different languages.  Apple acquired PrimeSense, a company that developed depth-sensing camera systems used in Microsoft’s Kinect motion-sensitive devices, to help build its face recognition technology.
OpenAI ( created GPT-3, or Generative Pre-trained Transformer 3.  It uses language-processing algorithms mined from roughly 570 gigabytes of data gathered by internet crawling, enabling it to answer questions, write essays and summaries, translate languages, create memos or program computer code. 
Elsewhere, the Allen Institute for Artificial Intelligence (AI2, developed a model that can create images from a text caption.  In the same vein, the University of North Carolina, Chapel Hill’s scientists came up with a method that combines images with existing language models, resulting in amped up reading comprehension.  These are breakthroughs that will greatly enhance machines’ ability to perform complex tasks.
Unfortunately, facial recognition is vulnerable to cyberattack.  A common practice by scammers is to print a photo of a person’s face, cut out the eyes, and use the altered image as a mask (many recognition systems scan for eye movement).  Another method is to use software to combine facial characteristics from different people to form a new identity with a “Frankenstein face.”  This can be a part of “synthetic identity fraud”—setting up an entirely new, false identity, including name, address and various types of accounts, sometimes with an engineered face added.  Identity verification company, Inc. ( reported more than 80,000 attempts on U.S. state workforce agencies to fraudulently claim unemployment benefits between June 2020 and January 2021 using masks or AI generated images.

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