In the Fifties, the founders of the field, Hyman Minsky and Joseph McCarthy described artificial intelligence as any task performed by a machine that was previously seen as requiring human intelligence.
Obviously, this is a fairly loose definition, which is
why you will sometimes see arguments about whether the thing is really
artificial intelligence or not.
- Under the above definition, modern AI-powered systems, such as virtual assistants, can be described as having demonstrated "narrow AI"; the ability to generalize their training when performing a limited set of tasks, such as speech recognition or computer vision.
- AI systems typically exhibit at least some of the following behaviors associated with human intelligence: planning, learning, reasoning, problem-solving, knowledge representation, perception, movement, and manipulation (and to a lesser extent: social intelligence and creativity).
- Artificial intelligence (AI) promises to deliver some of the most incredible innovations of this century. Self-driving cars, automated personal assistants, and automated disease diagnostics are all products of the emerging artificial intelligence revolution that will reshape the way we live and work. As the demand for talented engineers has doubled in the past few years, there are unlimited opportunities for professionals who want to work in and develop AI.
- While the functions of designing and improving AI applications are increasing, some analysts expect these efforts to significantly destabilize economic mobility. This is because AI systems can process unlimited amounts of data, and humans-and we mean the millions of people in today's labor market - are simply not up to the task.
- A recent report by the McKinsey Global Institute suggests that about a third of the U.S. workforce will be at risk of being laid off by 2030. Workers in data-intensive industries are particularly at risk, including financial and Administrative Professionals, legal support staff, marketing content writers, and IT workers.
- Although it was unclear what posts would be eliminated and how many new ones would be created. The World Economic Forum predicts that artificial intelligence will lead to a net increase of 58 million jobs globally.
- beyond the impact of the new AI economy on the workforce of the future, university students and young professionals will benefit from entering this burgeoning field. Breaking into the AI field, however, is not simply learning computer science or getting a college degree. It takes initiative, courage, and knowledge. In fact, 50% of top AI professionals report a skills gap, a real "talent crisis," according to Ernst & Young.
Learning artificial intelligence:
AI has a high learning curve, but for enthusiastic
students, what they will make from the AI market far outweighs how much they
invest time and effort while learning. Success in this field usually requires a
bachelor's degree in Computer Science or a related discipline such as
mathematics. Higher positions may require a master's or doctoral degree, although
a university degree is no longer a tough requirement by top employers such as
Apple and Google. On the whole, your success will largely depend on factors
that have nothing to do with formal education.
Artificial intelligence courses and curricula
Computer science coursework (plus getting to know the
basics of data science, machine learning, and Java) is a good starting point.
There are a number of new undergraduate and graduate programs emerging every
day that are designed to prepare a person for a major in artificial
intelligence.
As we note below, artificial intelligence consists of
several overlapping disciplines. Understanding statistical methods, for
example, is just as important as having a background in Computer Science. In
addition to the topics listed here, it may be useful to take interdisciplinary
courses in areas such as cognitive science to provide a conceptual framework
for AI applications.
Sample of core subjects in the artificial intelligence curriculum:
*Mathematics and statistics
- Linear algebra.
- The calculus.
- Matrices and linear transformations.
- Integration and approximation.
- Modern regression.
- Probability theory.
- Bayesian networks.
- Probabilistic graphical models.
*Computer science
- Computer systems and programming.
- Principles of calculation of necessity.
- Principles of functional programming.
- Fundamentals of data science.
- Parallel and sequential data structures and
algorithms.
- Logic programming and computational logic.
- Software development.
*Specialized materials
- Machine learning, deep learning, and enhanced
learning.
- Information theory, reasoning, and learning
algorithms.
- Neural networks for machine learning.
- Artificial intelligence representation and
problem-solving.
- Natural language processing.
- Computer vision and image analysis.
Once you've mastered some of the basics, find the
artificial intelligence subfields that interest you most and shape your
curriculum accordingly. The following list shows more specialist subjects that
you may take as electives while pursuing a degree; these topics are also worth
exploring at any stage of your career.
Additional classes may be available to teach students
certain applications of AI in areas such as biology, healthcare, and
neuroscience.
Sample of specialized kits for artificial intelligence:
*Machine learning
- Deep enhanced learning and control.
- Applied machine learning.
- Machine learning to extract text.
- Advanced data analysis.
*Decision-making robots
- Neural computation.
- Independent agents.
- Cognitive robots.
- Strategic thinking of artificial intelligence.
-Robot mobility and dynamics.
*Linguistics
- Information retrieval and search engines.
- Speech processing.
- Computational visualization.
- Computational photography.
- Vision sensors.
The professions of artificial intelligence
1-
Director of analytics
2-
Principal scientist
3-
Machine learning engineer
4-
Computer vision engineer
5-
Data scientist
6-
Data engineer
7-
Algorithm engineer/developer
8-
Computer scientist
9- Statistician
10- Research engineer
Interestingly, the number of
industries using artificial intelligence is growing to such an extent that no
major enterprise will be affected by this rapidly evolving technological
revolution.