science & technologyTechnology

What Experts Say on – The Tomorrowland ‘Starring AI & ML’

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What Experts Say on – The Tomorrowland ‘Starring AI & ML’

Mr. Pichai Sundarajan

Pichai Sundarajan, an Indian-American businessman who is the chief executive officer of Alphabet and Google was born in Chennai, India, Pichai earned his degree from IIT Kharagpur in metallurgical engineering. Moving to the United States, he attained an M.S. from Stanford University in materials science and engineering and further attained an MBA from the Wharton School of the University of Pennsylvania, where he was named a Siebel Scholar and a Palmer Scholar, respectively

The adoption of artificial intelligence seems to be increasing at the present due to the pandemic, says the research conducted by the International Business Machines (IBM). Artificial intelligence is fundamentally identifying patterns from large sets of data. From the pattern identified, the result or the conclusion or the outcome is drawn. The features of artificial intelligence have led to the expedite in the growth of AI. Virtual assistants, automation key workflows, maintaining network security intrigued the use of artificial intelligence across the world. More than half of Indian IT professionals have admitted to the reason why the rollouts happened was because of artificial intelligence. This proves the crucial role AI plays in the miscellaneous role in development of diverse fields. The customer’s drive to have renewed and quality products have eventually led to the increasing spread and broadening of AI. Its role in the field of business is driven by the three capabilities of automating IT and processes, building trust in AI outcomes, and understanding the language of business. In the field of technology or to satisfy user needs various features like speech-to-text, text-to-speech, and video intelligence has been some of the booming factors that dragged people into this technology. The big 4 accounting companies involve providing financial and accounting needs or advice including dealing with large sets of data history and deriving conclusions from it. To do this manually can be a tedious work job but with AI it is seamlessly done. They implement AI into products, to provide all the benefits associated with the end customers, to liberate serious workflow, and operations to increase day-to-day productivity, and to provide informed and strategic insights. For example, Deloitte, a multinational company that provides audit, assurance, consulting risk, and financial advisory, created an AI-enabled document review process. Though many cinematic universes portray artificial intelligence and robots as a conjectured notion, it is not robots always. The Chief Executive Officer of Google says, ‘Building general artificial intelligence in a way that helps people meaningfully – I think the word moonshot is an understatement for that. I would say it’s big as it gets.

Machine learning is a branch of artificial intelligence that is based on the idea that systems can learn from data, and identify different patterns with which precise decisions can be made with minimal to no human interventions. Over history, the amount of data received from users have potentially grown and has made it hectic for analysts who work constantly with data. When analysts received moderate amounts of data it was less laborious. In order to manage the big data that the analysts were provided with, it led to the birth of machine learning, a branch of artificial intelligence. The key difference between machine learning and artificial intelligence is, AI is working on mimicking human abilities through a machine including cognitive ability, which is a broad science whereas machine learning is a subset of the bread science that talks about the training needed for the machine. Likewise artificial intelligence, machine learning is also diverse and is being utilized for the benefit of the customers. To exemplify, financial services, government, health care, retail, oil and gas, transportation.

Mr. Pichai says “Deep learning and AI techniques have been around for many years. But there wasn’t much computational power to run these algorithms. For instance, Google Translate uses machine learning which has phenomenally improved the translation prowess,”

In the health industry, wearable devices and sensors are used as an interpreter to assess a patient’s health in real-time. In health care, unstructured data takes a huge amount of time to analyze that costs time. But machine learning represents almost 80% of the information held or locked. Human intervention can sometimes throw ambiguity and vagueness, but machines can make help sort the data and make it analyzable. The healthcare industry and machine learning are integrated through natural language processing (NLP).

Despite artificial intelligence and machine learning playing a huge role in various sectors, human intervention is as necessary as any technology. On foreseeing the future, many predictions as to the future will be taken over by robots and technology can be intimidating but without human beings, it wouldn’t have been possible. Technology is a subsidiary that has the potential to make our life better


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