Artificial intelligence
It is a branch of computer science
dealing with the simulation of intelligent behavior in computers & the capability of a machine to imitate intelligent human behavior.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.
Carrier in Artificial Intelligence
AI has been a sound career choice for a while now because of the growing adoption of the technology across industries and the need for trained professionals to do the jobs created by this growth. Pundits predict that AI will create close to 2.3 million jobs by 2020. However, it is also forecasted that this technology will wipe out over 1.7 million jobs, resulting in about half a million new jobs worldwide.
Norvig and Russell go on to explore four different approaches that have historically defined the field of AI-
Thinking Humanly
Thinking Rationally
Acting Humanly
Acting Rationally
AI is rapidly evolving, which is one reason why a career in AI offers so much potential. As technology evolves, learning improves. Van Loon described the three stages of AI and machine learning development as follow:
- Stage one is machine learning - Machine learning consists of intelligent systems using algorithms to learn from experience.
- Stage two is machine intelligence - Which is where our current AI technology resides now. In this stage, machines learn from experience based on false algorithms. It is a more evolved form of machine learning, with improved cognitive abilities.
- Stage three is machine consciousness - This is when systems can do self-learning from experience without any external data. Siri is an example of machine consciousness.
Courses under AI
Python
Deep Learning
Machine Learning
Neural Networks
Computer vision
Natural Language Processing
Subsets of Machine Learning
In addition to the development of machine learning that leads to new capabilities, we have subsets within the domain of machine learning, each of which offers a potential area of specialization for those interested in a career in AI.
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Neural Networks
Neural networks are integral for teaching computers to think and learn by classifying information, similar to how we as humans learn. With neural networks, the software can learn to recognize images, for example. Machines can also make predictions and decisions with a high level of accuracy based on data inputs.
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Natural Language Processing (NLP)
Natural language processing gives machines the ability to understand human language. As this develops, machines will learn to respond in a way a human audience can understand. In the future, this will dramatically change how we interface with all computers.
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Deep Learning
Deep learning is at the cutting-edge of intelligent automation. It focuses on machine learning tools and deploying them to solve problems by making decisions. With deep learning, data is processed through neural networks, getting closer to how we think as humans. Deep learning can be applied to images, text, and speech to draw conclusions that mimic human decision making.
Specific Jobs in AI
Although we talk about AI and machine learning as broad categories, the jobs available are more accurate. Some of the jobs described by Van Loon during the webinar include:
- Software analysts and developers.
- Computer scientists and computer engineers.
- Algorithm specialists.
- Research scientists and engineering consultants.
- Mechanical engineers and maintenance technicians.
- Manufacturing and electrical engineers.