I recently asked some of the leading experts in Artificial Intelligence, and Machine Learning for their opinion on the most important developments of AI from 1949 and the key trends in 2018. Here are my unbiased list:

• 1949 Edmund Berkeley publishes Giant Brains: Or Machines That Think in which he writes: “Recently there have been a good deal of news about strange giant machines that can handle information with vast speed and skill….These machines are similar to what a brain would be if it were made of hardware and wire instead of flesh and nerves… A machine can handle information; it can calculate, conclude, and choose; it can perform reasonable operations with information. A machine, therefore, can think.”
• 1950 — Alan Turing publishes “Computing Machinery and Intelligence.” Alan Turing creates his Turing Test to determine whether or not a computer has human-like intelligence.
• 1950 Isaac Asimov published his Three Laws of Robotics.
• 1951 Marvin Minsky and Dean Edmunds build SNARC (Stochastic Neural Analog Reinforcement Calculator), the first artificial neural network, using 3000 vacuum tubes to simulate a network of 40 neurons.
• 1952 — Arthur Samuel writes the first computer learning application
• 1955 — John McCarthy, the computer scientist coined the term “artificial intelligence”
• 1957 — Frank Rosenblatt designs the first artificial neural network
• 1967 — Computer-based pattern recognition begins with the nearest neighbor algorithm
• 1979 — Stanford University students invent the self-navigating Stanford Cart
• 1981 — Explanation Based Learning (EBL) is introduced by Gerald Dejong, allowing a computer to create a set of rules based on training data
• 1985 — Terry Sejnowski creates NetTalk, which learns to pronounce words
• The 1990s — Machine learning work shifts from a knowledge-driven approach to a data-driven approach, extracting patterns from large amounts of data
• 1993, Vernor Vinge publishes “The Coming Technological Singularity,” in which he predicts that “within thirty years, we will have the technological means to create superhuman intelligence. Shortly after, the human era will be ended.”
• 1997 — IBM’s Deep Blue system defeats the world champion of chess
• 2005 — Ray Kurzweil, the issue is computer power and, using Moore’s Law, he predicted that machines with human-level intelligence will appear by 2029. Follow that out further to, say, 2045, we will have multiplied the intelligence, the human biological machine intelligence of our civilization a billion-fold.
• 2006 — Geoffrey Hinton coins the term “deep learning,“ to explain new algorithms that empower computers to distinguish objects and images and video
• 2010 — Microsoft’s Kinect is released, tracking 20 human features to allow people to interact with the computer through movements and gestures
• 2011 — IBM’s Watson beats two of Jeopardy’s greatest champions
• 2011 — Nevada becomes the first jurisdiction in the world where autonomous vehicles can be legally operated on public roads.
• June 2012 Jeff Dean and Andrew Ng report on an experiment in which they showed a very large neural network 10 million unlabeled images randomly taken from YouTube videos, and “to our amusement, one of our artificial neurons learned to respond strongly to pictures of… cats.”
• October 2012 A convolutional neural network designed by researchers at the University of Toronto achieve an error rate of only 16% in the ImageNet Large Scale Visual Recognition Challenge, a significant improvement over the 25% error rate achieved by the best entry the year before.
• 2015 Google DeepMind’s AlphaGo (version: Fan) defeated 3 time European Go champion 2 dan professional Fan Hui by 5 games to 0.
• 2016 — The biggest success story of the year was probably AlphaGo (Nature paper), a Reinforcement Learning agent that beat the world’s best Go players.
• 2017 — Stephen Hawking warns emergence of artificial intelligence (AI) could be the “worst event in the history of our civilization”. This is also the year in which China starts looking like a major player in the field of AI. Facebook made a big splash with PyTorch. Tensorflow 1.0 of Google with a stable and backwards-compatible API was released in February. Facebook and Microsoft announced the ONNX open format to share deep learning models across frameworks.
• 2018 Year of explosion on AI. Artificial Intelligence impacts multiple fields. Tesla was one of the first auto makers to launch a self-driving vehicle. In their effort to keep pace with Tesla, traditional automakers like Audi are poised to release their own self-driving cars in 2018.
• 2018 AI scientist, Amit Ray Published the seminal book, Compassionate Artificial Intelligence, AI -5.0.
• 2018 — Tesla and SpaceX CEO, Elon Musk warns A.I. could create an “immortal dictator -it would live forever -from which we can never escape.”
• 2018 Google CEO Sundar Pichai said “one of the most important things that humanity is working on. It’s more profound than, I don’t know, electricity or fire”
• 2018 Nvidia, has recently introduced their GPU cloud, which promises to be another interesting alternative to train Deep Learning models. Success of TensorFlow, Self-driving cars, AlphaGo Zero will continue this year. AI with IOT, Big Data, Data Science are the top trends of artificial intelligence.

Please comment regarding notable omissions and inaccuracies.

In this article, we will share the best ways to make money online through freely available deep learning frameworks. The key for earning money from AI is to “Focus on the simple problems of AI and grow step-by-step”. Tech giants are shifting their focus from mobile devices to artificial intelligence.

No, it’s not just a thing of the movies, artificial intelligence systems are used today in medicine, robotics, remote sensors, and even in ATMs. This booming field of technology is one of the most exciting frontiers in science and this is the solid opportunity to make money.

1. Learn and Know the Present State of AI

We have all seen science-fiction movies which portray “robots” as being evil and harming others and now we are waiting to see Compassionate AI, which will help people to change the world for a better place to live. We are in the almost final stages in the growth of AI solutions and the next revolution of AI is compassionate AI.

Just spend an hour a day learning Machine Learning, by end of the year you will be among the top 15% expert in the world.

You must learn the boundaries of AI. In one end, it is the killer robots, what Elon Musk CEO of SpaceX, is talking about and in anther end, it is the Compassionate Superintelligence, the vision of the notable AI scientist, Dr. Amit Ray. You must also know the contribution of Geoffrey Hinton, Andrew Ng, Yann LeCun, and Ray Kurzweil.

2. Be an Online AI Teacher:

The current exponential technologies will make an enormous wealth. Learn the AI technologies from depth and then teach AI to others. Develop course materials and videos and sell them online at appropriate avenues.

3. Earn from Smartphone AI:

Try to develop simple new AI apps on smart phone and earn. New AI chatbots are gold mines to earn. The new AI apps in our smart phones are an incredible example of the power of AI to transform our society and as AI becomes a greater part of our everyday lives. We all know AI how have helped facebook to remove thousands of fake accounts and “suspicious behaviors.” We also know how the Siri platform of Apple remains behind the quality level of Google Assistant, which uses some of the same game-changing algorithms that power Google Translate and Google Image Search.

Hence, in the lower end you can develop chatbot frameworks for smartphones and at higher end you can develop machine learning engines.

4. Earn by Creating Massive AI Data:

Massive amounts of data are required to fuel AI and to train the algorithms that are part of AI solutions. Human intelligence grow by observing. Human have a lot of visual and auditory experiences. An AI system needs to learn the same way and be fed with videos and dynamic information. Wherever you are create massive AI data and sell that at high price. Big educational research institutes are ready to pay huge amount for big data. The key principles of AI solution is privacy, security, inclusiveness, fairness, reliability, transparency and accountability. The accuracy of the data is the sole power for money.

5. Join AI and Machine Learning Competitions:

Challenge yourself with real-world machine learning problems. Join the ML Competitions and earn money. Kaggle Competitions are very popular.

In summary, you will see an wave of value creation over the coming years resulting from artificial intelligence. You can focus on your strong areas and focus on the companies that are using these technologies to change the game and provide a materially improved experience for humanity.

Wish you all the best. Thanks!

Your claps and comments are most welcome!