How MNC’s are getting benefitted from AI/ML?
What is AI(Artificial Intelligence)?
Artificial intelligence (AI) is a 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 ideal characteristic of artificial intelligence is its ability to rationalize and take actions that have the best chance of achieving a specific goal.
Applications of Artificial Intelligence:
The applications for artificial intelligence are endless. The technology can be applied to many different sectors and industries.
- Artificial Intelligence in business: Robotic process automation is being applied to highly repetitive tasks normally performed by humans. Machine learning algorithms are being integrated into analytics and CRM (Customer relationship management) platforms to uncover information on how to better serve customers. Chatbots have already been incorporated into websites and e companies to provide immediate service to customers. Automation of job positions has also become a talking point among academics and IT consultancies.
- Artificial Intelligence in Healthcare: Companies are applying machine learning to make better and faster diagnoses than humans. One of the best-known technologies is IBM’s Watson. It understands natural language and can respond to questions asked of it. The system mines patient data and other available data sources to form a hypothesis, which it then presents with a confidence scoring schema. AI is a study realized to emulate human intelligence into computer technology that could assist both, the doctor and the patients
- AI in education: It automates grading, giving educators more time. It can also assess students and adapt to their needs, helping them work at their own pace.
- AI in Autonomous vehicles: Just like humans, self-driving cars need to have sensors to understand the world around them and a brain to collect, process, and choose specific actions based on information gathered. Autonomous vehicles are with an advanced tool to gather information, including long-range radar, cameras, and LIDAR. Each of the technologies is used in different capacities and each collects different information. This information is useless unless it is processed and some form of information is taken based on the gathered information. This is where artificial intelligence comes into play and can be compared to the human brain. AI has several applications for these vehicles
Machine Learning(ML):
Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it to learn for themselves.
The process of learning begins with observations or data, such as examples, direct experience, or instruction, in order to look for patterns in data and make better decisions in the future based on the examples that we provide. The primary aim is to allow the computers to learn automatically without human intervention or assistance and adjust actions accordingly.
MNC’s that are getting benefitted from AI/ML:
1) Apple :
Apple, one of the world’s largest technology companies, selling consumer electronics such as iPhones and Apple Watches, as well as computer software and online services. There might be a perception that Apple is late to the machine learning party, but that’s probably not true, especially since it was the first to launch a voice assistant on a smartphone.
Millions of people talk to Siri, even if we don’t, and Apple is looking to extend the application of the talking assistant through its new smart home device or speaker, the HomePod.Amazon’s Alexa-powered Echo devices and Google Home Assistant for competition, Apple has its work cut out.
Apple has also been active in acquisitions — second only to Google. One of the more notable purchases has been Lattice Data, which has a machine learning system for converting unstructured data — like random text and pictures — into structured data. The company has also allocated significant resources for the development of in-house machine learning systems, many of which are available through its developer program.
2) Pindrop:
Pindrop has developed what the company says is a “pioneering” technology for recognizing fraudulent activity over the phone channel. In other words, its “Phoneprinting” technology can create what Pindrop describes as an “audio fingerprint” of each call by analyzing 1,300 unique call features — such as background noise, location, number history, and call type — to identify unusual activity. The system automatically flags suspicious calls and can even spot ID spoofing, voice distortion, and social engineering. Pindrop’s system is being applied by leading companies such as Lloyds Banking Group.
3) Microsoft:
Over the past few years, Microsoft has successfully been building new features into its Office products and launching new AI-powered tools through its Azure cloud-computing service as the company looks beyond its Windows products to the fast-growing AI market. Perhaps that’s why Microsoft has set its sights on AI and is driving full-steam ahead. The company set up its Artificial Intelligence and Research Group back in 2016 and staffed it with 5,000 computer scientists and engineers. The group’s plan was to help the company develop AI in four main categories, including the company’s Cortana digital assistant, its applications like Office 365, its services, and Azure cloud-computing infrastructure.
For example, Office 365 subscribers can use what Microsoft called “ink analysis” to convert handwritten words in PowerPoint into text and allow users to draw their own shapes and have them transformed into objects. The service also allows users to sketch out an entire slide with text boxes and drawings and then convert it into a professional-looking slide using AI.
Microsoft introduced a slew of new AI services for Office 365 at the end of 2017, including Acronyms for Word and Time to Go for Outlook. The AI-based Acronyms feature helps Word users understand the shorthand created by companies by searching previous definitions found in emails and other documents and applying it to the document you’re currently working on.
The Windows maker has used its AI virtual assistant, Cortana, to make its Outlook email app far more useful as well. Microsoft believes Cortana is one of the biggest keys to AI’s progression. Cortana is used in myriad ways on Windows devices and in Microsoft’s apps, including its Outlook email program. Cortana can automatically detect trips, meetings, and deliveries through a feature called Time to Leave. The digital personal assistant sifts through emails and then sends users a notification that it’s time to leave for an appointment, and it can even factor in traffic data when it tells you when you go — to help ensure you get there on time.
4) Alibaba :
The leading cloud computing platform in Asia, Alibaba offers clients a sophisticated Machine Learning Platform for AI. Significantly, the platform offers a visual interface for ease of use, so companies can drag and drop various components into a canvas to assemble their AI functionality. Also included in the platform are scores of algorithm components that can handle any number of chores, enabling customers to use pre-built solutions. Expect huge AI growth from Alibaba. Artificial intelligence (AI) is integral in Alibaba’s daily operations and is used to predict what customers might want to buy. With natural language processing, the company automatically generates product descriptions for the site.
5) Baidu :
Another company that has been very active in the mergers and acquisitions scene is the Chinese search giant Baidu. The company is particularly interested in natural language processing, with a view to developing a workable voice-activated search function.
One of the many machine learning acquisitions Baidu made last year was Kitt.ai, which is said to have a portfolio of chatbots and voice-based applications. The financial terms of that particular deal were not disclosed but Baidu is said to be the 10th biggest-spender on acquisitions in the world, according to CB Insights, which says Google spends the most.
Google’s voice search and voice dictation for Google Docs are not totally terrible, but the problem for tech companies is that human users expect voice systems to be comparable in quality to the experience of talking to another human, and they’re a long way from that now.
The solution may not lie entirely in the software. Machine learning may provide powerful ways of learning how people speak. But an eventual solution may require an upgrade of the hardware. Specifically, the microphones may need to become more sensitive or something. Whatever the solution, voice systems are yet to pass that quality or usability threshold.
6) IBM :
IBM has been a leader in the field of artificial intelligence since the 1950s.A long time ago — way back in the 1990s — IBM challenged Russia’s greatest chess player, Garry Kasparov, to a match against its Deep Blue computer.
Kasparov trounced Deep Blue in the first match, but then the Russian grandmaster raged against the machine after losing to it in subsequent contests. He probably still hasn’t got over it, claiming there was something amiss in the way IBM played. Others, however, have urged Kasparov to play along and admit defeat, but he still refuses to do what he’s told.
The successor to Deep Blue is the famous Watson AI computer, which beat the best contestants on a US television quiz show called Jeopardy!.
Watson Machine Learning is available much like Google Cloud AI machine learning is, but being elitist, IBM probably charges more. And IBM’s chess challenge has been usurped in terms of media hype by the recent human-vs-machine contest over an ancient board game called “Go”, which was won by the machine, of course. In this instance, the machine — or algorithm — was developed by DeepMind, which Google bought a few years ago for about $525 million.
Its efforts in recent years are around IBM Watson, including an AI-based cognitive service, AI software as a service, and scale-out systems designed for delivering cloud-based analytics and AI services. It has been acquisitive, purchasing a number of AI startups over several years. It benefits from having a strong cloud platform.