AI and Machine Learning – Learning Pathway #1

Welcome to the AI and ML Learning Pathway. Here we aim to give you an understanding of the core concepts of Artificial Intelligence and Machine Learning research. Across the learning path we will cover in more detail: AI basics, what is AI and how does it work; AI Research, what are the key areas of research, their limitations and future perspectives; among other topics.

Artificial Intelligence (AI) is the umbrella term that describes the process of machines making intelligent decisions in order to achieve some goal. Machine Learning (ML) is a subfield of AI, distinguished by the ability of a program to improve based on past experience.

Today, AI is rapidly expanding mostly due to a ML technique known as deep learning, which seems to have the potential to transform just about everything. Advances in machine vision research using deep learning from companies such as Tesla, Waymo, and Zoox bring the feasibility of self-driving cars ever-closer. Progress in Natural Language Processing (NLP) has allowed big tech companies, such as Apple and Amazon, to develop their popular SIRI and Alexa products and Open AI to develop a language model called GPT-3 that reproduces human-like text that took many by surprise. Google’s DeepMind has famously used deep learning to become better than human experts in various games including video games from ATARI and Starcraft to the notoriously complex Chinese game of Go and recently developed a program, Alphafold, which solved the significant biological problem of protein folding, promising a revolution in the development of new drugs.

Applying AI to medicine holds great promise from the classification of disease using radiological records to the use of NLP to read through vast numbers of Electronic Health Records. However, medicine is a complex field with high stakes and the power of AI is limited by the messiness of data in the real world. Recent attention has focused on the problem of AI recapitulating biases that are found in training data, such as racial and gender biases found in society, and poses difficult technological and ethical problems.

The benefits of AI also come with the dangers of its misuse and many organizations are focusing on both the short and long-term threats AI poses to humans. The future of AI has never looked brighter, but only time will tell if this powerful technology will live up to its hype.

Skills

Posted on

30 January 2021

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