Over the past century, technological advancement has accelerated significantly. Additionally, over the past ten years, the world of information technology has experienced exponential growth, particularly in the fields of artificial intelligence (AI) and machine learning (ML).
Our lives are being affected by these changes more and more; they have an effect on everything from eLearning to personal economics to leisure. Before discussing how to handle the expected and quick changes in the future, let's take a look back at the AI and machine learning milestones during the last 10 years.
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Past Years of Artificial Intelligence and Machine Learning
1952 and 1956
The terms "machine learning" and "artificial intelligence" first appeared. After more than 50 years, academics George Dahl and Abdel-rahman Mohamed demonstrated in 2010 that deep learning voice recognition systems might outperform current state-of-the-art business solutions. At the same time, Google unveiled Waymo, the name of its self-driving car project. In September 2010, DeepMind, a pioneer in the disciplines of AI and deep learning, was founded. Later, we'll learn more about them.
1997
When IBM's Watson question-and-answer system upset reigning Jeopardy! champions Brad Rutter and Ken Jennings in 2011, AI threatened humanity's ability to dominate the mind. Without a certain, Garry Kasparov's opponent in 1997, Deep Blue, Watson's "ancestor" computer, would have been pleased!
Apple unveiled Siri, their virtual assistant, while IBM machines were demonstrating the superiority of human brain. Convolutional neural networks, a natural language user interface, and speech recognition are all used by Siri. Users are now able to use internet services to search, recommend, respond to queries, and complete tasks.
2012
Everyone is aware of the close bond that exists between cats and the internet. Therefore, it was expected that their entertaining relationship would reach a significant milestone in 2012. By observing unlabeled images from video frames, the Google Brain Team, under the direction of Jeff Dean and Andrew Ng, created a neural network that recognised cats on YouTube.
In addition, Oculus VR was founded in 2012, and it used Kickstarter to raise money for their initial Oculus Rift virtual reality device. Only two years after the company was founded, Facebook bought it because the technology was so intriguing. Beyond virtual reality gaming, the Oculus Rift has a wide range of uses in media, education, and industrial visualisation and design.
2013
Boston Dynamics, the company behind the four-legged robot BigDog, developed Atlas in 2013. Atlas, who stands six feet tall and resembles a humanoid, has developed the ability to move between indoor and outdoor environments and do a range of human tasks, including driving a car, opening and closing doors, climbing a ladder, and connecting and operating a fire hose.
Google unveiled a Google Glass beta test version in 2013. A heads-up display attached to eyeglasses, Google Glass supports AR and AI applications like text translation and facial recognition. While certain augmented reality (AR) applications have been integrated into Android phones as Google Lens, Google Glass has evolved over time from a consumer device into an industrial tool.
2014
2014 saw Google make headlines once more when it paid a stunning $500 million to acquire the previously mentioned DeepMind. Facebook researchers also disclosed their work on DeepFace, a neural network system that recognises faces with an accuracy rate of over 97 percent.
Finally, generative adversarial networks, a machine learning system in which two neural networks compete with one another to produce superior answers to challenges, were developed in 2014. Through this competition, artificially new, original content is produced.
2015
When AlphaGo, powered by DeepMind, defeated a human professional Go master for the first time in 2015, AI proceeded to demonstrate its mastery of video games. In the meantime, Google showed off their driverless vehicle, which is based on the Waymo design.
2016
The best Go player in the world, Lee Sedol, was defeated by AlphaGo in 2016. The Face2Face initiative also gave users the ability to make deepfake films in that year. Deepfake, a combination of "deep learning" and "fake," creates or modifies audio and video content using AI and ML methods. Since technology may be used to modify videos and produce false or defamatory content, this development has generated some concern.
A less spooky development in 2016 was the introduction of Google Assistant, an AI-powered virtual assistant that can converse with users in both directions using Google's natural language processing technology. The user's device's hardware settings can be modified by the Google Assistant, which can also perform Internet searches, schedule events, set alarms, and display data from their Google account.
2018
When a collection of artificial intelligence (AI)-produced artworks created by computers using GAN were sold for USD 400,000 at a Christie's auction in 2018, generative adversarial network technology was once again in the headlines. The artwork was produced by the Paris-based art collective Obvious using a two-part algorithm that examined image data from 15,000 portraits from the 14th to the 20th centuries.
2019
When Google demonstrated a lung cancer diagnosis made possible by artificial intelligence in 2019, the medical industry finally had a chance to take use of the technology's rapid advancement. The system produced results with a higher degree of accuracy than what could be achieved by human radiologists. It was powered by deep learning and used an algorithm that examined computer tomography (CT) scans. Oncologists could benefit greatly from this research since it will give them more effective tools for identifying and treating cancer.
That brings us up to the present, when machine learning and artificial intelligence have their sights set on the ocean. The Mayflower Project intends to traverse the Atlantic Ocean using an AI-controlled ship without a crew, marking the 400th anniversary of the Mayflower's journey from Europe to North America.
2020
The Mayflower Autonomous Ship will be guided across the Atlantic by edge computing and artificial intelligence systems, which is a simple undertaking in comparison to programming a self-driving automobile to drive through the congested streets of Manhattan during rush hour. But the water has its own unique set of unpredictabilities that will undoubtedly put artificial intelligence and machine learning to the test. The trip will take place in the autumn of 2020.
The COVID-19 epidemic is being fought in 2020 on the front lines by AI and ML. Researchers are utilising AI and ML technologies to build possible vaccinations, anticipate the spread of the virus, and conduct virtual drug testing to identify viable treatments among currently available medications. Robotics even has a part to play, as seen in the employment of social connectedness robots to assist nursing home residents in maintaining contact with loved ones while under quarantine.
Basic concerns concerning workers being replaced by machines have been raised by labour experts. Privacy advocates are particularly concerned about the way AI chatbots and virtual assistants are obtaining personal data.
Future of Artificial Intelligence and Machine Learning
Our lives have changed significantly as a result of AI and machine learning during the past ten years, and innovation is accelerating. You may get the skills you need to work in this fascinating field by enrolling in one of the many AI and machine learning courses offered by Simplilearn.
The Artificial Intelligence Courses, for instance, discuss the ideas behind this exciting technology and how it is transforming the digital world. You can gain the skills necessary to become a machine learning engineer and be prepared to face the difficulties and thrills of this cutting-edge technology by learning concepts like real-time data, and algorithm development using supervised and unsupervised learning, regression, and classification.