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To JFK, Automation Was A-OK

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    “Automation  does not need to be our enemy. I think machines can make life easier for men, if men do not let the machines dominate them.”  ~ John F. Kennedy

    Artificial Intelligence Concept Image

    The late President John F. Kennedy will be forever remembered for his incredible vision of getting Americans to the moon.  But even a person of his foresight would be surprised to see how  technologies like robotics, artificial intelligence, and machine learning have pioneered a new age of automation in the 21st century.  Yes, Mr. President.  Machines can and do make life easier for men.

    And in fact, using machines to handle hazardous, inefficient, and repetitive jobs is a practice that is at least a century old. Indeed, the automated weaving loom was the first machine to  use interchangeable punch cards  to  instruct a machine to perform automated tasks. That’s not so different from today’s computer programs that can be programmed for  various  tasks. 

    Automation technologies are already all around us in the form of robotics  (ie, industrial machinery)  and  software (ie, payroll). However, the rise of artificial intelligence (AI) is enabling new-use cases for both enterprises and consumers, especially when combined with intelligent edge solutions.

    A New Age of Automation

    Thanks to rapid  technology  growth, we are at the dawn of a new age of automation. Robots and computers can already perform routine physical work tasks more cheaply and efficiently than humans.  Now, they can  solve  cognitive problems often associated with human intelligence. 

    Tasks that were once thought to be difficult to automate, such as real-time judgment, emotion-sensing,  and  long distance  driving,  can be automated successfully today. And with AI inferencing, the machinery and devices around us are  increasingly more capable of performing tasks that require cognitive capabilities. 

    That’s the good news.

    Machine Learning Technology

    The not-so-good news? The calculations for AI Inferencing are power-hungry, which is why AI these days is still primarily confined to devices that are either constantly plugged  in, or  have large enough batteries to store power necessary for all operations. 

    Automation for Work

    AI-driven automation uses  rule-based  models and machine learning  to find patterns in massive quantities of data. Unlike robotics-driven automation that substitutes for routine human labor, AI-driven automation can substitute for more “thoughtful” tasks such as problem-solving, strategic planning, and real-time perception.  

    AI can have a significant impact in helping us better predict outcomes across many information-heavy fields,  such as  business, management, marketing, and especially health. With the help of AI inference, we would be able to make more confident predictions under conditions of uncertainty.

    Intelligent machines and software  powered by AI are shaping the framework of workplaces of crucial  industries,  such  as manufacturing and agriculture. Thanks to improved image processing techniques, quality checks can be streamlined in  factories, reducing project times. 

    Smart farmer using artificial intelligence with his crop

    AI is also playing a major role in automating agriculture. Today’s farmers can leverage smart cameras that can provide incredible real-time insights. Crops and weeds can be identified in real-time, herbicides can be triggered to kill the weeds,  and landscape analysis can be done in real-time.

    Automation in Everyday Life 

    AI  will become an even larger part of our lives than it already is. A device enabled with AI can be a chauffeur, an assistant, a doctor, a coach, a nutritionist, a master of knowledge, and a companion — all wrapped into one. 

    Through machine learning, a device can learn human behavior so that apps can better predict what you might want,  and when you might want it. Music streaming services already recommend songs and artists based on your past listening behavior. Same for video streaming services.  As AI inferencing improves, it will be possible to have a versatile companion that can grow with the user, evolving as they evolve,  while keeping all personal information and preferences private and secure.

    As the  COVID-19 pandemic continues to improve,  more companies are investing in technologies that can better automate aspects of healthcare,  such as early diagnosis and contact tracing. For general health, smart wearables like the Apple Watch Series or the  FitBit can monitor your biometrics and make suggestions to improve your physical wellbeing. Other apps can detect stress, and recommend relaxing activities; or learn  your  grocery shopping habits,  and make personalized shopping suggestions. 

    How Ambiq Contributes

    Whether it’s a smart wearable device or a portable medical device, intelligent edge solutions cannot solve complex problems without advanced inference. However, these devices need to handle information in real-time without relying on network connections back to the cloud.  

    Only an ultra-low-power and small form factor onboard can provide the needed inference performance.  Ambiq’s  ultra-low-power wireless  SoCs  are accelerating edge inference in devices limited by size and power. Ambiq’s products enable  IoT  companies to deliver solutions with a much longer battery life and more complex, faster, and advanced ML algorithms right at the  endpoint.

    Instead of running complex AI inferencing in the cloud on large, power-hungry computers,  Ambiq® and its  SPOT®-enabled technology enable  battery-powered endpoint devices to run optimized models for pattern recognition on microcontrollers no bigger than a grain of rice — all while consuming only milliwatts of power. 

    Quite simply, Ambiq’s solutions can enable endpoint intelligence everywhere. Which makes life easier.

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