ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING
Artificial Intelligence and Machine Learning is a popular topic in the tech industry. Perhaps more than our daily lives Artificial Intelligence (AI) is impacting the business world.
The world is seeing extraordinary advances in artificial intelligence (AI). There are new applications in finance, defense, health care, criminal justice, education, and other key industries. Algorithms are improving fraud detection, health diagnoses, voice recognition systems, as well as advertisement targeting in e-commerce and political campaigns.
What is Artificial Intelligence?
Artificial intelligence (AI) is wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence. AI is an interdisciplinary science with multiple approaches, but advancements in machine learning and deep learning are creating a paradigm shift in virtually every sector of the tech industry.
THE FUTURE OF ARTIFICIAL INTELLIGENCE
Artificial intelligence is impacting the future of virtually every industry and every human being. Artificial intelligence has acted as the main driver of emerging technologies like big data, robotics and IoT, and it will continue to act as a technological innovator for the foreseeable future.
THE EVOLUTION OF AI
IFM is just one of countless AI innovators in a field that’s hotter than ever and getting more so all the time. Here’s a good indicator: Of the 9,100 patents received by IBM inventors in 2018, 1,600 (or nearly 18 percent) were AI-related. Here’s another: Tesla founder and tech titan Elon Musk recently donated $10 million to fund ongoing research at the non-profit research company OpenAI — a mere drop in the proverbial bucket if his $1 billion co-pledge in 2015 is any indication. And in 2017, Russian president Vladimir Putin told school children that “Whoever becomes the leader in this sphere [AI] will become the ruler of the world.” He then tossed his head back and laughed maniacally.
THE FUTURE IS NOW: AI'S IMPACT IS EVERYWHERE
- Transportation: Although it could take a decade or more to perfect them, autonomous cars will one day ferry us from place to place.
- Manufacturing: AI powered robots work alongside humans to perform a limited range of tasks like assembly and stacking, and predictive analysis sensors keep equipment running smoothly.
- Healthcare: In the comparatively AI-nascent field of healthcare, diseases are more quickly and accurately diagnosed, drug discovery is sped up and streamlined, virtual nursing assistants monitor patients and big data analysis helps to create a more personalized patient experience.
- Education: Textbooks are digitized with the help of AI, early-stage virtual tutors assist human instructors and facial analysis gauges the emotions of students to help determine who’s struggling or bored and better tailor the experience to their individual needs.
- Media: Journalism is harnessing AI, too, and will continue to benefit from it. Bloomberg uses Cyborg technology to help make quick sense of complex financial reports. The Associated Press employs the natural language abilities of Automated Insights to produce 3,700 earning reports stories per year — nearly four times more than in the recent past.
- Customer Service: Last but hardly least, Google is working on an AI assistant that can place human-like calls to make appointments at, say, your neighborhood hair salon. In addition to words, the system understands context and nuance.
What Is Machine Learning?
A subset of artificial intelligence (AI), machine learning (ML) is the area of computational science that focuses on analyzing and interpreting patterns and structures in data to enable learning, reasoning, and decision making outside of human interaction. Simply put, machine learning allows the user to feed a computer algorithm an immense amount of data and have the computer analyze and make data-driven recommendations and decisions based on only the input data. If any corrections are identified, the algorithm can incorporate that information to improve its future decision making.
How Does Machine Learning Work?
Machine learning is made up of three parts:
- The computational algorithm at the core of making determinations.
- Variables and features that make up the decision.
- Base knowledge for which the answer is known that enables (trains) the system to learn.
Machine Learning Use Cases :
Machine learning has applications in all types of industries, including manufacturing, retail, healthcare and life sciences, travel and hospitality, financial services, and energy, feedstock, and utilities. Use cases include:
- Manufacturing. Predictive maintenance and condition monitoring
- Retail. Upselling and cross-channel marketing
- Healthcare and life sciences. Disease identification and risk satisfaction
- Travel and hospitality. Dynamic pricing
- Financial services. Risk analytics and regulation
- Energy. Energy demand and supply optimization
BENEFITS WHICH MNC’s ARE GETTING FROM ARTIFICIAL INTELLIGENCE /MACHINE LEARNING
Artificial intelligence is moving forward, and whether we like it or not, machine learning will play an essential role in our technological future. The largest and best companies in the world already know this, and they are investing heavily in AI.
Usage of Artificial Intelligence
Over the last few years, AI has emerged as a significant data science function and, by utilizing advanced algorithms and computing power, AI is transforming the functional, operational, and strategic landscape of various business domains.
Most AI technologies — from advanced recommendation engines to self-driving cars — rely on diverse deep learning models. By utilizing these complex models, AI professionals are able to train computers to accomplish specific tasks by recognizing patterns in the data.
Artificial Intelligence Market Size by Company Type
How to work Machine Learning
??Top AI companies in the world and how does they use AI and ML
? Amazon
Trade giant Amazon has invested in both the consumer-oriented side of AI and in applications for companies and their processes. Alexa, the company’s AI language assistant, integrated into its echo speaker series, is well-known worldwide. However, Amazon Web Services (AWS), a set of machine learning programs and pre-trained AI services for businesses, hasn’t yet done so much. AWS currently has more than 10,000 customers, including Siemens, Netflix, Tinder, NFL, and NASA.
? Apple
The development of products such as Siri and the company’s new Create ML tool, which MacOS and iOS developers can use to create efficient and straight forward training courses for their apps.
Apple uses artificial intelligence and machine learning in products like the iPhone, where it enables the FaceID feature, or in products like the AirPods, Apple Watch, or HomePod smart speakers, where it enables the smart assistant Siri. Apple is also growing its service offering and is using AI to recommend songs on Apple Music, help you find your photo in the iCloud, or navigate to your next meeting using Maps.
? Banjo
Banjo was founded after the tragic bombings of the Boston Marathon 2013. The start-up uses AI to search social media to identify real-time events and situations that could be critical for emergency services and other organizations to operate faster and smarter. The company has raised more than $120 million in funding to date, including investors such as the Japanese telecommunications giant SoftBank.
? DJI
The first Chinese company on the list, DJI, is still officially a start-up but has already been valued at 15 billion dollars. The company has a market share of more than 70 percent in the global drone market and is increasingly entering the AI market. The latest drones use AI and image recognition to avoid objects. Soon, an entry into autonomous vehicles and robotics can be expected. DJI has recently entered into a partnership with Microsoft for a drone-to-computer streaming project.
Facebook’s AI research group, known as FAIR, says it is committed to advancing the field of machine intelligence and developing new technologies to provide people with better ways to communicate.
Google has acquired AI start-ups as if there were going to be no more soon. Over the past four years, Mountain View has created no fewer than twelve new artificial intelligence companies. The most important purchase was the $400 million deal for DeepMind, the board game playing Go champion.
There is also Google’s machine system TensorFlow, which is now free for all, and the ongoing Tensor AI chip project for machine learning on the device.
? HiSilicon
When Huawei CEO Richard Yu unveiled the Kirin 980 at IFA 2018 in Berlin, the competition was very keen. HiSilicon, Huawei’s chip manufacturer, has significantly enhanced the second generation of the world’s first AI smartphone chip. The Kirin 980 can do things like face recognition, object recognition, image segmentation, and intelligent translation at high speed.
? IBM
IBM has created a machine learning platform that can integrate AI into business processes, such as building a chatbot for customer support. Customers include Big Four Auditor, KPMG and Bradesco, one of Brazil’s largest banks.
Intel
Intel has also been on a shopping spree when it comes to artificial intelligence companies and has acquired both Nervana and Movidius as well as a selection of smaller AI start-ups. Nervana enables companies to develop specific deep learning software, while Movidius was founded to bring AI applications to devices with deficient performance. Intel is also working with Microsoft to provide AI acceleration for the Bing search engine.
? Microsoft
Microsoft is involved in Artificial Intelligence on both the consumer and business sides. Cortana, Microsoft’s AI digital assistant, is in direct competition with Alexa, Siri, and Google Assistant. Artificial Intelligence features are a large part of the company’s Azure Cloud service, which provides chatbots and machine learning services to some of the biggest names in the business.
? Nvidia
Nvidia’s graphics processors are the be-all and end-all for machine learning and artificial intelligence. The Delaware-based company is active in healthcare, higher education, retail, and robotics. With deep learning and GPU development, Nvidia is concerned with integrating AI into every level of the vehicle, manufacturing and autonomous driving.
? Qualcomm
Like HiSilicon with its Kirin 980, Qualcomm is another chip manufacturer that is committed to artificial intelligence. AI plays a crucial role in the Snapdragon 855 mobile platform. The chip uses a signal processor for AI speech, audio and image functions. Qualcomm Snapdragons power some of the most popular smartphones on the market. If you’re interested in AI in the smartphone, you should keep an eye on Qualcomm.
Startup Companies using AI
Top Common Challenges in AI
- Computing Power
- Trust Deficit
- Limited Knowledge
- Human Level
- Data Privacy and Security
- The Bias Problem
- Data Scarcity
Conclusion
According to a recent survey, 37% of organizations are still looking to define their AI strategies. To integrate AI into your own business, you need to identify how AI can serve your business, possible use cases of AI in your business. This article gathers the most common use cases covering marketing, sales, customer services, security, data, technology, and other processes
Artificial Intelligence and Machine Learning are products of both science and myth. The idea that machines could think and perform tasks just as humans do is thousands of years old. The cognitive truths expressed in AI and Machine Learning systems are not new either. It may be better to view these technologies as the implementation of powerful and long-established cognitive principles through engineering.
