This meeting is the second part of a look at Artificial Intelligence, a technological change that will sweep this new decade and change the world more swiftly and totally than any other industrial development to date. Rotarians need to form a frontline of understanding of what is happening with emerging technology to better serve our communities close and far.

E-CLUB PROGRAM

PRESIDING TODAY IS: Ken Jaskot, Member

bellDing! We’re now in session.

Welcome all – visitors, fellow Rotarians and guests alike to this E-Club program!

 

Remember the Four-Way Test!

At the beginning of each meeting we remind ourselves of The Four-Way Test.  Therefore, please remember to ask yourself always ...

 

Of the things we think, say or do:

  1. Is it the TRUTH?
  2. Is it FAIR to all concerned?
  3. Will it build GOODWILL and BETTER FRIENDSHIPS?
  4. Will it be BENEFICIAL to all concerned?

 

Reflective Moments

“People are spending way too much time thinking about climate change, way too little thinking about AI.”
         – Peter Thiel, American entrepreneur, venture capitalist, and a co-founder of PayPal,

“We're at a point now where we've built AI tools to detect when terrorists are trying to spread content, and 99 percent of the terrorist content that we take down, our systems flag before any human sees them or flags them for us.”
       – Mark Zuckerberg, CEO, Facebook
 
“It is difficult to think of a major industry that AI will not transform. This includes healthcare, education, transportation, retail, communications, and agriculture. There are surprisingly clear paths for AI to make a big difference in all of these industries.”
       – Andrew Ng, co-founded Coursera and deeplearning.ai
 
“AI is everywhere. It's not that big, scary thing in the future. AI is here with us.”
      Fei-Fei Li, co-director of Stanford's Human-Centered AI Institute and the Stanford Vision and Learning Lab
     

Leadership Quotes

 
“February 23: Happy 115th birthday, fellow Rotarians and members of the family of Rotary! In the 115 years since Rotary was founded, seemingly everything has changed except Rotary values. We began, and remain, committed to fellowship, integrity, diversity, service, and leadership. While our Service Above Self motto dates to 1911, the ethos behind those words had already been ingrained by Rotary's founders. As the pace of change worldwide continues to accelerate, the need for Rotary service is greater than ever.”
  – RIP Mark Daniel Maloney, 2019-20, Rotary Connects the World

 

 

 

 

 

Events

 

 

Artificial Intelligence: A Brief Look... Part 2

 
The modern high-end camera is a good example of an AI-enabled device. The focusing system is essentially a robot - it has servos and actuators, it is capable of operation independent of a human host, its auto-focusing system involves a continuous feedback loop to determine the best focal length and exposure even before the picture is "taken", it makes use of light-sensitive arrays that convert light into digital signals, it typically stores dozens or even hundreds of "photos" that it can then composite, and then has AI routines capable of removing red-eye, improve focusing and compensate for lighting conditions. In most cases, these very complex operations are hidden from the users, who just know that they are taking better photographs than ever before.
 
A self-driving car, also known as an autonomous vehicle, is a connected car that relies on a combination of hardware, software, and machine learning to navigate various weather, obstacles and road conditions using real-time sensory data. Features such as brake assist, lane assist, and adaptive cruise control, for example, can be considered autonomous driving to some degree and are the results of the integration of real-time data, sensors, robotics, and low-level AI.
 
What is necessary for a high automation, self-driving system that is responsible for all execution, monitoring, and fall back?
 
1) A massive database of many, many miles of driving experiences in all sorts of conditions that can be used as the training basis for creating a vehicle’s operating system that can judge its constantly changing environment and predict how to safely proceed on the trip.
 
2) The integration of sensors such as lasers, radar, lidar, camera computer vision systems, GPS tracking, audio and ultrasonic sensors which can read the environment in real-time.
 
3) In order for self-driving software to interface with the hardware components in real-time, processing all sensor data efficiently, it needs a computer with the processing power to handle this amount of data.
 
4) A neural network is a sophisticated algorithm based on complex matrices designed to recognize patterns without being programmed to do so specifically. Neural network algorithms are actually trained using the labeled data to become adept at analyzing dynamic situations and acting on their decisions. Objects need to be detected, localized, recognized, and predicted, then decisions must be made to accommodate situations in real-time.
 
At this point, AI machines are task-oriented. (There is no “all-knowing” AI machine—yet.) So once an objective is chosen, the first step is to determine what sort of data is needed to provide the desired results. As we’ve seen above, this can be tremendously varied and can be remarkably complex. The data must be collected and categorized and given context points that make it relatable in as broad a manner as possible.
 
The algorithms that will process the data must be written. An algorithm is a step by step method of solving a problem. An algorithm is also needed to manipulate data in various ways, such as inserting a new data item, searching for a particular item or sorting an item. Think of it like a complex recipe. How can the collected data be arranged to provide correct results?
 
The processing begins and the results are analyzed. Corrections are made to what data is collected and how it is identified contextually and how the algorithms handle it. The algorithms are revised. This process continues until the outcomes are acceptable.
 
Marketing: AI for Real-Time Data: The use of real-time data, web data, historical purchase data, app use data, unstructured data, and geolocation information, have introduced the ability to deliver information, product recommendations, coupons and incentives at the right time and place. AI allows companies to engage in personalized marketing and slide the dial closer to one-to-one relationships.
 
Retail Sales: AI for Voice and Image Search: Artificial intelligence in retail is transforming the way people shop and buy items ranging from clothes to cars. Voice search and image search are now widespread. Amazon and many other retailers now incorporate these tools in their apps. Next-generation AI is also taking shape. For example, augmented reality lets shoppers view a sofa or paint color superimposed in their house or office. Virtual reality allows consumers to sit inside a vehicle and even test drive it without leaving home. Audi, BMW and others have developed VR systems for shoppers.
 
Customer Support: AI for Natural Language: AI in retail is emerging as a powerful force, but customer support is also harnessing the technology for competitive advantage. Bots and digital assistants are transforming the way support functions take place. These technologies increasingly rely on natural language processing to identify problems and engage in automated conversations. AI algorithms determine how to direct the conversation or route the call to the right human agent, who has the required information on hand. This helps shorten calls and it produces higher customer satisfaction rates.
 
Manufacturing: AI Powers Smart Robots: Robotics has already changed the face of manufacturing. However, robots are becoming far more intelligent and autonomous, thanks to AI. What is machine learning used for in factories? Many companies are building so-called “smart manufacturing” facilities that use AI to optimize labor, speed production and improve product quality. Companies are also turning to predictive analytics to understand when a piece of equipment is likely to require maintenance, repair or replacement. For example, Siemens is now equipping gas turbine systems with more than 500 sensors that continuously monitor devices and machines. All this data is helping create the manufacturing facility of the future, sometimes referred to as Industry 4.0.
 
Supply Chains: AI for Management: AI use cases in operations and supply chain management are growing. Organizations are turning to algorithms to improve fleet management, warehouse administration, logistics processes, freight brokering and numerous other tasks. This includes emerging areas such as drone deliveries and automated vehicles. The IoT (Internet of Things), which places sensors on raw materials, components and products, is also reshaping business by collecting massive amounts of data, which can be fed into analytics engines to make decisions.
 
Financial Service: AI Enables Intelligent Processing: Banks and other institutions already use AI to detect suspicious activity, including fraud. AI use cases also extend to intelligent process automation and robotic process automation. This includes everything from apps that scan checks and make deposits, to a system that automates the movement of funds based on interest rates. Robo-advisors, which use recommendation engines to replace traditional stockbrokers are also becoming commonplace. Stock trading quants also handle trades using algorithms that incorporate an array of factors, information, and variables.
 
Life Sciences and Medicine: Researchers and healthcare providers are increasingly using machine learning, deep learning and other types of AI to pore over data and, using analytics, spot patterns that help healthcare providers treat at-risk groups more effectively. Pharmaceutical companies and biomedical device makers are tapping AI to develop algorithms that produce more effective drugs, smart prosthetics, robotic surgical systems, and virtual reality applications that help treat conditions such as depression and PTSD.
 
Note: Your comments and questions are appreciated! 
 

OUR CLUB........................................................................

The Mountain State Rotary E-Club (MSRE) is a member club of Rotary International District 7545 (covering most of West Virginia, excluding the Eastern panhandle) and RI Zone 33, which encompasses a large portion of the eastern sector of the United States.
 
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