The pace of technological innovation has increased dramatically over the last century. Furthermore, over the past decade, advances in the information technology world have grown exponentially, particularly in the world of artificial intelligence (AI) and machine learning (ML).
These changes will impact our lives, and everything from entertainment to personal finances to e-learning. Let's look back at the AI and machine learning milestones of the past decade, then consider ways to navigate the inevitable rapid changes of the future.
Unleash the power of AI and ML with machine learning courses.
Also, accelerate your career with Simplilearn's NLP training. Gain superior knowledge and skills in all industries.
The ever-changing world of AI and ML
The terms “machine learning” and “artificial intelligence” first appeared in 1952 and 1956, respectively. Fast forward over half a century later, in 2010, researchers George Dahl and Abdel Rahman Mohamed proved that deep learning speech recognition tools could beat modern cutting-edge industry solutions. At the same time, Google announced an autonomous car project now known as Waymo. Finally, Deepmind, a pioneer in the field of AI, was founded in September 2010. I'll explain in more detail later.
In 2011, AI put human spiritual control at risk when Watson, the IBM question and answer system, broke the dangers of governance! Champions Brad Latter and Ken Jennings. Watson's “ancestor” Deep Blue, the computer that defeated Russian chess grandmaster Garry Kasparov in 1997, would have been proud!
While IBM machines were introducing human intelligence, Apple introduced Siri, a virtual assistant. Siri uses speech recognition, a natural language user interface, and convolutional neural networks. This technology allows users to perform searches, create recommendations, answer questions, and perform tasks through Internet services.
Everyone knows that the internet and cat share a deep and lasting relationship. Therefore, it was not surprising that this entertaining partnership experienced a major milestone in 2012. The Google Brain team, led by Jeff Dean and Andrew NG, has developed a neural network that recognizes cats on YouTube by viewing unlabeled images from video frames.
2012 was also the year in which Oculus VR was incorporated and funded the first Oculus Rift Virtual Reality headset using Kickstarter. The technology was so exciting that Facebook acquired the company just two years later. Oculus Rift is used in many applications other than VR games, including industrial visualization and design, education, and media.
In 2013, Boston Dynamics, the maker of the four-legged robot BigDog, created Atlas. With a 6-foot-tall humanoid form, the Atlas has evolved to operate both indoors and outdoors, allowing you to perform a variety of human activities, including driving vehicles, opening and closing, climbing ladders, and installing and operating fire hoses. The purpose is to carry out search and rescue operations in environments that are too dangerous for humans.
In 2013, Google also introduced a beta-test version of Google Glass. Google Glass is a head-up display attached to glasses that supports AR and AI applications, including face recognition and text translation. Over time, Google Glass has moved from consumer products to industrial tools, but some AR applications have been integrated into Android phones as Google lenses.
Google turned its head again in 2014 when it bought Deepmind, which it mentioned early for $500 million. Meanwhile, Facebook researchers have revealed their work with Deepface, a neural network system that identifies faces with more than 97% accuracy.
Machine Vs. machine
Finally, in 2014, we saw the invention of generative adversary networks, a machine learning system in which two neural networks compete with each other to create better solutions to problems. This competition artificially creates new original content.
In 2015, AI continued to master the game when Deepmind-powered Alphago beat the human pro Go Master for the first time. Meanwhile, Google has demonstrated an unmanned vehicle equipped with Waymo models.
In 2016, Lisedl, the world's biggest go-player, lost to Alphago. Also, that year, the Face2Face program allowed users to create DeepFake videos. A combination of the terms “Deep Learning” and “Fake,” Deepfake uses AI and ML techniques to create or manipulate audio and video footage. The development drew a share of the controversy as technology can manipulate videos and create fraudulent or honourable content.
In a creepy note, in 2016, we also witnessed the birth of Google Assistant, an AI-powered virtual assistant that engages in two-way conversations courtesy of Google's natural language processing algorithms. Google Assistant can conduct Internet searches, schedule events, set alarms, change hardware settings for users' devices, and view information in their users' Google accounts.
In 2018, a set of machine-made AI-made paintings sold by Gan for 400,000 US dollars at Christie auctions has made the news again for 2018. Clearly, the Paris-based art group of artists and AI researchers created the artwork using a two-part algorithm that analyzes image data from 15,000 portraits from the 14th to the 20th century.
Imitation, medicine, mayflower
Google has improved Google Assistant and released Google Duplex. Google Duplex allows for realistic and natural conversations by mimicking the human voice. Users can currently make restaurant reservations using Google Assistant. There are also plans to expand your ability to book other types of appointments on a daily basis and in some cases act as a translator. Think of robocall. A real human voice is much smarter and sometimes indistinguishable.
The healthcare sector benefited from the rapid advancement of AI technology when Google demonstrated lung cancer diagnosis provided by artificial intelligence in 2019. With deep learning and algorithms that analyze computed tomography (CT) scans, the system has provided greater accuracy than what human radiologists can offer. This development is a potential jackpot for oncologists and provides a better tool for cancer diagnosis and treatment.
It brings us to today, when AI and machine learning set their sights on the ocean. The Mayflower Project is set to send crewless, AI-controlled ships throughout the Atlantic, coinciding with the 400th anniversary of Mayflower's voyage from Europe to North America.
Artificial intelligence and edge computing systems are easier tasks than programming self-driving cars to navigate downtown Manhattan streets during rush hour. However, the ocean comes with its own set of unpredictable variables that will undoubtedly lead AI and machine learning to test. The voyage is planned for the fall of 2020.
Responsive increase in ethical and human questions
In 2020, AI and ML are at the forefront of the fight against the Covid-19 pandemic. Researchers use AI and ML tools to predict the spread of the virus, perform virtual drug testing, find potential treatments between existing drugs, and design potential vaccines. Robotics plays a role in using social connectivity robots to help residents of the Holy Clergy stay in touch with their loved ones during quarantine.
Technological advances tend to outweigh social norms. New rules of engagement need to be established to ensure that ethical development and practices are in place.
At the basic level, workers experts have expressed concern about people who are losing their jobs to robots. Privacy advocates are also wary of virtual assistants and natural sounding chatbots (with functional vocabulary) collecting personal information.
Using AI and ML to regulate and defend the malicious use of similar technologies will be a developing trend in the coming years, as certified ethical hackers know.
I'm looking beyond 2020
AI and machine learning have made major changes to our lives over the past decade, and the pace of innovation has accelerated. Simplilearn offers a full range of AI and machine learning courses that can provide you with the skills you need to be part of this exciting industry.
For example, the Caltech Post Graduate program in AI and Machine Learning courses explores this fascinating concept of technology and how the digital world changes. Learn concepts such as real-time data and develop algorithms using unsupervised, unsupervised learning, regression, and classification to become a machine learning engineer, ready to tackle the challenges and excitement of this cutting-edge technology.
