“The key to artificial intelligence has always been the representation” by Jeff Hawkins.
Artificial Intelligence is a field of computing where intelligent machines uplift human cognitive abilities & experiences. AI can reproduce certain human-like behavior, such as interacting, recognizing, learning & understanding, making it a powerful technology. AI refers to a large field of science enclosing not only computer science but also philosophy, psychology & other areas. AI technology is concerned with getting computers to do jobs that would generally require human intelligence.
The founder of AI Alan Turing defines this discipline as: “AI is the science and engineering of making intelligent machines, especially intelligent computer programs”.
It’s high time for the technology leaders to look at how AI can be used to improve speed, quality, functionality & even lead to excellent revenue growth.
Narrow AI: A chess computer could defeat a human in playing chess, but it couldn’t solve a tough math problem. Practically all recent Artificial Intelligence is “narrow”, meaning it can only do what it is designed for. It means for every problem a particular algorithm requires to be designed to solve it. Narrow AI is mostly much better at the job they were made for than humans, like calculus, chess computers, translation, face recognition.
General AI: The holy dish of AI is a General AI, a single system that can learn about each & every problem and then solve it. This is precisely what humans do: we can specialize in a particular topic, from sports to art, from abstract mathematics to psychology and, we can become experts at all of them. An Artificial Intelligence and machine learning system integrates & uses mainly machine learning & several other types of data analytics methods to achieve artificial intelligence capabilities.
The growing availability, precision, and ease of implementation of artificial intelligence methods generate opportunities for companies to use them in their business.
For example, insurance companies get started with AI to read claims from their clients, to have the understanding, of the claim is easy or difficult & it can give a suggestion on how to handle the claim. The insurance employee then only needs to do a quick check before approving the recommendation. It can save precious time & increase the quality of the work. This is just one example. Here we share 5 applications in which we will see a huge development in the coming years of lean transformation.
• Image recognition.
• Speech recognition.
These developments will make applications cheaper & more precise, opening the door for business to use them during organization transformation.
IBM Watson, which we know from playing Jeopardy, has matured its image recognition expertise in the field of medicine. IBM Research has been operating on sound learning techniques for computer vision that could be utilized to recognize whether skin irregularities are melanoma. They developed a group of methods that can separate skin lesions & methods that can find the area and surrounding tissue for melanoma and tested it on a large publicly available dataset.
The vision of IBM is that at a particular point medical staff can send a picture of skin irregularities to Watson, the same way that they send blood samples to the lab. Facial recognition, which was used in security cameras, now has also been generated in other areas. In a survey, it was found that a quarter of all British shops use facial recognition software. The software is used for security, but also to track customers to observe their behavior as an effect of product displays or the traffic flow in the store.
Popular examples are Microsoft’s Alexa, Apple’s Siri & Google Home. Today we have applications on our phone & in our home that can respond to our voice. One of the business applications is the use of speech recognition in health care. A lot of physicians are working with an electronic health record (HER) to record patient information. Using speech recognition, the patient record can be recorded in a flexible & quick manner, which allows the physician to give more attention to the patient.
Closed domains, however, have a very good business application such as responding to questions at customer service. Some years ago, there was a development in question answering interest, when IBM Watson defeat humans in a game of Jeopardy, a well-known American quiz show. More recently another development was made by Google, which can now give chatbots the ability to have a short-term memory, which gives the chatbot the ability to mimic real-life conversations more realistic. In the area of customer service, Chatbots are swiftly becoming the norm, one example being IPsoft’s Amelia. Standard queries are already handled automatically, with only the difficult ones being forwarded to human decision-makers.
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Recently there was a big achievement in the field of games when the world Champion of Go was defeated by a computer for the first time. The top Go players of the world depend for a large part on their intuition to come to the best moves. Google’s AlphaGo, understood how to play like a top human player by studying millions of human games. It then became even stronger by playing against another version of itself millions of times, which finally enabled it to defeat the world champion. If computers can defeat human players in one of the most complicated games that currently exist, then where does the possibility for Artificial Intelligence stop?
· Amazon has used machine learning to lead suggestions for many years. The company is using deep learning to renovate business processes & to develop new product categories, such as its virtual assistant and maintaining its competency in digital transformation.
· Google has sketched its Artificial Intelligence specific chips to stimulate machine learning in its data centers & on IoT devices.
· China’s BATs – Baidu, Alibaba, and Tencent – are investing soundly in composition for agents in artificial intelligence while growing into areas previously controlled by US companies: autonomous vehicles, chip design & virtual assistants.
· These tech firms are using AI to generate billion-dollar services & to modify their operations. To develop their AI services, they’re following a friendly scenario:
1) Find a solution to an internal challenge or opportunity,
2) Perfect the solution at scale within the company and,
3) Launch a service that swiftly attracts mass adoption. Hence, we see Microsoft, Amazon, Google, and China’s BATs launching machine learning and artificial intelligence development platforms and stand-alone applications to the broader market based on their own experience using them.
ABB’s Predictive Emission Monitoring System (PEMS) uses an empirical model to forecast emission concentrations based on process data & it has been progressively implemented as a segment of a complete Environmental Management system in one of the foremost gas processing plants in the world. PEMS – which is also known as an inferential analyzer – can’t compute emissions straightly but utilizes an empirical model to predict emission concentrations based on process data, such as operating pressure, fuel flow, load & ambient air temperature. Additionally, virtual analyzers serve other purposes:
In the US, several states allow artificial intelligence (AI) technologies based on models like PEMS as an alternative monitoring technique.
Alphabet is Google’s parent company. Waymo, the company’s self-driving technology division, started as a project at Google. Today, Waymo wants to bring self-driving technology to the world not only to move people around but to decrease the number of crashes. Its autonomous vehicles are recently plying riders around California in self-driving taxis.
Chinese company Alibaba is the world’s biggest e-commerce platform that sells more than eBay & Amazon integrated. Artificial intelligence is fundamental in Alibaba’s daily tasks and is used to forecast what customers might want to purchase. With natural language processing, the company automatically produces product descriptions for the site.
Another way Alibaba utilizes artificial intelligence is in its City Brain project to develop smart cities. The project uses computer language used for artificial intelligence algorithms to help decrease traffic jams by evaluating every vehicle in the city. Additionally, Alibaba, through its cloud computing division called Alibaba Cloud, is helping farmers detect crops to improve yield & cuts costs with artificial intelligence.
Apple which is one of the world’s biggest tech companies, selling customer electronics such as Apple Watches & iPhones and, as well as computer software & online services. Apple uses machine learning & artificial intelligence in products like the iPhone, where it provides the FaceID feature, or in products like the HomePod, AirPods, Apple Watch, or smart speakers, where it enables the smart assistant Siri. Apple is using AI to help you find your photo in the iCloud & to suggest songs on Apple Music.
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Amazon uses Artificial Intelligence in the game with its digital voice assistant, Alexa. Another ingenious way Amazon uses AI is to parcel things to you before you even think about buying them. They gather a lot of data about each person’s buying habits & have such confidence in how the data collected by them will help them in suggesting items to its customers and now predict what they need even before they need it by using predictive analytics.
In a time when many market-led stores are fighting to find out how to stay pertinent, America’s biggest e-tailer provides a new comfort store concept called Amazon Go. In this store, no checkout is needed. The stores have artificial intelligence technology that records what items you pick up & then automatically charges you for those items through the Amazon Go app on your phone. As there is no checkout, you bring your bags to collect with items & cameras are stalking each & every activity to detect every item you put in your bag to finally charge you for it.
They are including intelligent capabilities to all its products & services, including Skype, Cortana, Office 365, Bing and are one of the world’s largest AI as a Service (AIaaS) vendors.
One of the primary ways Facebook uses artificial intelligence technology & deep learning is to add structure to its unstructured data. They use DeepText, a text understanding engine, to automatically understand & interpret the content and emotional feeling of the hundreds of posts (in multiple languages) that its users post every millisecond. DeepFace helps social media to identify you in a photo that is shared on their platform. This technology is better at facial recognition than human beings. The company also uses artificial intelligence to automatically find & delete images that are published on its site as revenge porn.
It’s the need of the hour for all leaders in every industry to think about whether, how & where they should be investing in AI-based technologies. It means understanding the available AI technologies & then analyzing existing & potential business processes, data assets, staffing models, and markets to find ways that AI can be used to enhance speed, quality & functionality, as well as to lead excellent revenue growth.
But visualizing the possible is not just about the opportunities. Executives require to put on their insight where AI has the power to disrupt their business or even their entire industry. Now, it is time to start this discussion. In two to four years, it may be behind time.