The Beginner’s Guide to Understanding Artificial Intelligence
Words, experiments and more ways to understand A.I.
Getting started in A.I. can be a bit overwhelming given the pace at which the space is changing. With surging momentum of great progress in the field as well as bottom line results, the hype around A.I. may be warranted.
However, with a plethora of resources available, online courses, blog posts and newsletters regarding this topic, where does one begin?
Here’s an easy way to dip your toes into artificial intelligence, for people who want to learn more but don’t know where to start.
Introduction
The Artificial Intelligence Revolution (Part 2 is here)
Explained Simply: Differences between Artificial Intelligence, Machine Learning and Deep Learning
Fast.ai — a with the goal of making deep learning easier to use and understand
Visual intro to machine learning — a beautiful interactive website
Machine learning process — walkthrough the process on a high level
AI Playbook — begin exploring what’s possible with AI.
AI Glossary — a non-exhaustive list of jargon/terminology
Andrej Karparthy’s blog — collection of essays by a PhD student working on ML.
A more in depth ML introduction with visual examples
Elements of AI — free online courses to start learning the basics of AI created by Reaktor and the University of Helsinki.
Videos
A few great presentations that help explain difficult concepts.
Newsletters
AI weekly — a collection of the best news and resources on Artificial Intelligence and Machine Learning
AIzone — a spotlight on the latest news
AIDL weekly — a weekly newsletter on A.I. published by Waikit Lau and Arthur Chan
Exponential view — Azeem Azhar’s weekly email blast gathers the best notes around how AI is transforming business and society
ML weekly — a weekly newsletter on machine learning by @alirezasmr
Fun stuff
Google’s AI Experiments — collection of fun AI experiments including AutoDraw, like autocorrect for your doodles, and The Infinite Drum Machine
Zo — a social AI chatbot
Lobe — train machine learning models with a free, easy no-code tool
RunwayML — a platform to discover, create, and use artificial intelligence capabilities in your creative work
Teachable Machine — A fast, easy way to create machine learning models for your sites, apps, and more — no expertise or coding required.
Poncho — personalized weather chatbot
Lyrebird — creates a digital copy of your voice
NVIDA AI playground — turn sketches into photo-realistic landscapes
Amper Music — an AI music composer
Prisma — turning your photos/videos into famously styled works of art
Companies/research groups
AI Now Institute — a research group at NYU examining the social implications of artificial intelligence
CHAI (Center for Human-Compatible Artificial Intelligence) — AI research towards provably beneficial systems
Deepmind — an AI company acquired by Google, known for AlphaGo which beat the world’s best Go player
FAIR — Facebook’s AI research
AI Principles — Microsoft’s approach to AI and guidelines for conversational AI
People+AI Guidebook — Google’s guidebook for designing human-centered AI products
OpenAI — a nonprofit AI research company; check out their blog
The Berkman Klein Center for Internet & Society — a research center that seeks to tackle the biggest challenges presented by the Internet.
Conferences
AAAI — started by an international, nonprofit, scientific society devoted to promote research in, and responsible use of Artificial Intelligence.
AI Summit —expo and AI event series for business
CogX — a festival of AI and emerging technology, with a startup expo
ML4ALL — making machine learning accessible to the average software developer or enthusiast
O’Reilly AI Conference — bridging the gap between AI developments in research and their commercial applications in business and industry.
O’Reilly TensorFlow World — brings together everything from healthcare, finance, IoT, and beyond.
World AI Summit — connecting the global AI ecosystem from enterprise to BigTech, startups, investors and science.
Podcasts
Artificial Intelligence Podcast by Lex Fridman — conversations around deep learning, robotics, AI, and more.
The Data Skeptic — scientific skepticism on topics in statistics
Linear Digressions — talks on machine learning, data science and AI simplified.
NLP Highlights — discussing recent and interesting work related to natural language processing.
TWIML — trends in machine learning from AI researchers, practitioners, and innovators.
Conclusion
The first step to learning a complex topic is to get a high-level understanding of what it is and what it can do. I hope these different resources are useful and provide a glimpse into where the industry is headed.
