AI is a bigger concept to create intelligent machines that can simulate human thinking capability and behavior, whereas, machine learning is an application or subset of AI that allows machines to learn from data without being programmed explicitly.
Artificial Intelligence
Artificial intelligence is a field of computer science which makes a computer system that can mimic human intelligence. It is comprised of two words “Artificial” and “intelligence”, which means “a human-made thinking power.” Hence we can define it as,
Artificial intelligence is a technology using which we can create intelligent systems that can simulate human intelligence.
Machine learning
Machine learning is about extracting knowledge from the data. It can be defined as,
Machine learning is a subfield of artificial intelligence, which enables machines to learn from past data or experiences without being explicitly programmed.
Machine learning enables a computer system to make predictions or take some decisions using historical data without being explicitly programmed. Machine learning uses a massive amount of structured and semi-structured data so that a machine learning model can generate accurate result or give predictions based on that data.
• Artificial Intelligence and Machine Learning are the terms of computer science.
• The word Artificial Intelligence comprises of two words “Artificial” and “Intelligence”.
• Artificial refers to something which is made by human or non natural thing and Intelligence means ability to understand or think. AI is implemented in the system.
• One definition of AI can be, “It is the study of how to train the computers so that computers can do things which at present human can do better.”
• Therefore, it is an intelligence where we want to add all the capabilities to machine that human contain.
________________________________________
• Machine Learning is the learning in which machine can learn by its own without being explicitly programmed.
• It is an application of AI that provide system the ability to automatically learn and improve from experience.
• It is a way of “learning” which enables an algorithm to evolve. In this case “learning” means feeding the algorithm with a massive amount of data so that it can adjust itself and continually improve.
Let’s take examples of Artificial Intelligence :
• Advertisements you see on other websites about a product you visited Amazon or Flipkart for.
• Spam filters
• Email categorization
• Self Driving Cars
Let’s take examples of Machine Learning :
• Image Recognition
• Speech Recognition
• For Prediction about something, if we provide appropriate data.
• Deep Blue Computer ( who defeated Garry Kasparov)
Places where AI and ML work simultaneously :
• Personal Assistants ( Google assistant, Siri, Alexa, Cortana, etc.)
• YouTube or Netflix which constantly used to improvise the recommendations and personalization problems.
• Uber and Maps ( for telling directions or time for cab, etc. )
• In mass production and automatic machines, etc.
Careers in AI and ML
Demand for artificial intelligence and machine learning experts is on the rise globally despite a fear that AI will eat away at many jobs. The rate at which global companies are hiring gives us a different picture. The technological advancement is still creating more positions as companies need high-skilled AI talents to develop and maintain a wide range of applications. According to Indeed, employers demand for AI talents has more than doubled over the past three years and the number of job postings as a share of all job postings have increased by 119 percent. The top 10 jobs in demand right now are:
1. Data Scientist
2. Software Engineer
3. Machine Learning Engineer
4. Software Architect
5. Data Analyst
6. Data Warehouse Engineer
7. Full Stack Developers
8. Research Scientist
9. Front End Developer
10. Product Manager
AI and machine learning has also strongly gaining ground in India, which is one of the top 15 countries in terms of talent, corporates who use ML, and authors who write about it. Cheaper cost of set up and availability of talent has made India a favourite place for tech giants such as Microsoft, Google and IBM to set up shop.
United States
US has been the leader in attracting AI and machine learning talent. A study by Pysa shows that the top 20 AI companies are spending more than $650 million to hire AI talent and that there are more than 10,000 positions available at top employers across the country. The total annual investment among the 20 employers that are looking to hire AI talents is $33,292,647, which indicates that the future success of the companies heavily depends on AI technologies and the talent to create them.
According to Glassdoor and Pysa, the top recruiters in US are Amazon, Google, Microsoft, NVIDIA, Facebook, Intel, Rocket Fuel, General Electric, Cylance, Oculus VR, Booz Allen Hamilton, Huawei, Adobe, Accenture, iRobot, Magic Leap, Rethink Robotics, BAE Systems, HERE, IBM, Samsung, Lenovo, MoTek Technologies, Uber, PCO innovation, Rakuten Marketing, and Wells Fargo. However, none of the reports listed Apple among the top recruiter.
Apart from US, Canada, Japan, Europe, China and India are the emerging countries for recruiting experts from AI and ML field
India
India too is not far behind other countries in terms AI hiring, the country is expected to see a 60 per cent rise by this year due to increasing adoption of automation. The presence of multi-billion dollar IT companies, global software product companies with their research and development bases in India and venture capital industry focused on AI and machine learning has given rise to a talent pool. Further, as India is heading towards Digital India, the IT industry will require 50 percent more workforce equipped with digital skills. “The growing opportunities in the digital technology arena including government initiative like Digital India will add jobs in digital technologies, AI, robotics. The IT industry is expected to add around 1.8-2 lakh jobs this year,” said Alka Dhingra, general manager, IT staffing at TeamLease Services. Most of the machine learning talent pool is spread across five cities: Bangalore, Chennai, Hyderabad, Mumbai/Pune belt and Delhi NCR region.
