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Artificial Intelligence: How to prepare yourself for the future
- 1. Artificial Intelligence (AI): How to position yourself for the future Folasade Adedeji
- 2. Content 1. Introduction 2. Facts about AI 3. Machines getting smarter 4. Job landscape in 2022 5. What is AI 6. Applications of AI 7. How does AI work 8. Limitations 9. Careers in AI 10. The future with AI 11. What to do 12. Ways to succeed in ML career 13. Where to get skilled
- 3. 1. Bible Text Jeremiah 29:11 NLT For I know the plans I have for you, says the Lord. “They are plans for good and not for disaster, to give you a future and a hope.
- 4. Some facts about AI University course enrolment in AI and ML is increasing all over the world. Experts predict that by 2020, 85% of all customer service interactions will be handled without the need for a human agent.’’ – Forbes According to the world economic forum, 75 million jobs will be obsolete by the year 2022, but then, the advancement of robotics and artificial intelligence will make 58 million jobs more than it destroyed.
- 5. Machines getting smarter An algorithm was able to detect an Ebola outbreak more than a week before it was announced by the World Health Organization. Driverless cars are forecast to make up 75% of all traffic by 2040. Human-robot marriages would be legal by the year 2050.’’ – CBC Radio
- 7. What is AI - Definition Artificial intelligence (AI) is the ability of a computer program or a machine to think and learn. It is also a field of study which tries to make computers "smart". They work on their own without being encoded with commands. AI uses algorithms to predict the future, while humans use our intuition to predict the future. The algorithm is based on previous data, while the intuition is based on our previous experience in life
- 8. What contributes to AI Artificial intelligence is a science and technology based on disciplines such as: Computer Science, Biology, Psychology, Linguistics, Mathematics, and Engineering. A major thrust of AI is in the development of computer functions associated with human intelligence, such as reasoning, learning, and problem solving. Out of the following areas, one or multiple areas can contribute to build an intelligent system
- 9. Relationship of AI to Other disciplines
- 10. Applications of AI AI has been dominant in various fields such as: Gaming : Playing games against the computer Natural Language Processing : Natural language processing (NLP) describes the interaction between human language and computers, In any case, the computer is able to identify the appropriate word, phrase, or response by using context clues, the same way that any human would e.g chatbots, hiring tool, conversational search, Siri, Alexa
- 11. Expert Systems An automated reasoning system that attempts to mimic the performance of the human expert. It offers advice or make decisions. Application in medical diagnosis.
- 12. Speech recognition A technology that allows spoken input into systems. You talk to your computer, phone, or device and it uses what you said as input to trigger some action. The technology is being used to replace other methods of input like typing, clicking, or selecting in other ways. Applications: car Bluetooth system, digital assistance.
- 13. Intelligent Robots Intelligent robotics are the robots that functions as an intelligent machine, that is, it can be programmed to take actions or make choices based on input from sensors. They have sensors to detect physical data from the real world such as light, image courtesy of may field robotics
- 14. Today, many fields including, legal, finance, biotech, infotech, nanotech, energy, healthcare, education etc. is wide open to revolutionary transformational developments. AI will most likely, have a similar impact as the Internet had.
- 15. Example of application of AI: Japanese cucumber farmer use deep learning and Tensorflow to sort cucumber
- 17. How does AI work AI works by combining large amounts of data with fast, iterative processing and intelligent algorithms, allowing the software to learn automatically from patterns or features in the data. AI is a broad field of study that includes many theories, methods and technologies, as well as the following major subfields:
- 18. AI subfields Machine Learning Neural network, Deep learning, Cognitive computing, Computer vision, Natural language processing
- 19. Using these technologies, computers can be trained to accomplish specific tasks by processing large amounts of data and recognizing patterns in the data.
- 20. Limitations AI thrives on data any inaccuracies in the data will be reflected in the results. AI systems are trained to do a clearly defined task. The system that detects fraud cannot drive a car or give you legal advice. In fact, an AI system that detects health care fraud cannot accurately detect tax fraud or warranty claims fraud. These systems are very specialized. They are focused on a single task and are far from behaving like humans.
- 21. Careers in AI Machine learning engineer: need the knowledge of modern programming languages like Java, Python, Scala Data scientist: Need a knowledge of platforms and tools like Hive, Hadoop, MapReduce, Pig, Spark. Programmming languages like Perl, Python, Scala, SQL Business intelligence developer: data warehousing, data mining, sql, Research scientists Big data engineers/architect: Solutions architect Algorithm developers
- 22. The future with AI Some skills are going into extinct, AI is creating more jobs No permanent jobs , keep learning new skills A degree is no longer sufficient to be indispensable at work Creative thinkers, innovative and inventive workers will make the head way Digital and media literacy will be paramount Customer demands will always change
- 23. What to do You shouldn’t worry about AI replacing you. Instead, It’s time to rethink your position in the job market It’s time to question your current career path, and consider if it would be wise to make a few changes. Keep yourself in the loop Follow the newest trends in your in your market Do some research on where your industry is heading. What’s the new and upcoming trends within your industry? Find some industry leaders, and listen carefully to what they’ve got to say
- 24. What to do Get accustomed with both new and disruptive technologies Can you apply it in your current role? Train yourself for both new and disruptive AI technologies Go after that new and disruptive AI job Refining the Soft Skills Understanding your customers through qualitative research Getting up to speed with analytics, coding, and math Adopting a growth mind set
- 25. Ways to succeed in ML career Understand what machine learning is. Be curious. Translate business problems into mathematical terms Be a team player Learn Python and how to use machine learning libraries Take online courses or attend a data science bootcamp.
- 26. Where to get skilled Google Machine Learning Crash Course Udacity Coursera EdX
- 27. THANK YOU