The Evolution History of AI From Turing’s ACE to Deep Language Learning Algorithm Robots
The Evolution History of AI From Turing's ACE to Deep Language Learning Algorithm Robots

From the earliest AI programs to the development of expert systems, neural networks, and machine learning algorithms, AI has come a long way in the last few decades.


Award Winning AI Technology Transforming The World (intro to AI)

Artificial Intelligence (AI) is a field of computer science and engineering that focuses on the development of machines that can perform tasks that would typically require human intelligence, such as recognizing speech or understanding natural language.

The history of AI spans several decades, from its inception in the mid-20th century to the present day. Over this time, a range of groundbreaking technologies and achievements have transformed our understanding of what is possible with computers and paved the way for the development of intelligent machines. From the early work of pioneers such as Alan Turing to the breakthroughs in voice assistants and deep learning, the history of AI is a story of innovation, ingenuity, and determination to push the boundaries of what technology can do.


Alan Turing, born in Maida Vale, London, was a pioneering computer scientist and mathematician who is widely considered to be the father of modern computer science and artificial intelligence. His computer was called the Automatic Computing Engine (ACE), was housed in Bletchley Park, Milton Keynes UK.

turing ace

The ACE was designed to be a general-purpose computer capable of solving a wide range of mathematical problems. It was intended to be a successor to the Colossus computer, which had been used during World War II to help crack German Enigma code created by a sophisticated encryption machine used by the Germans during World War II to send coded messages that were difficult for the Allies to decipher.

In 1950, he proposed what is now known as the Turing Test, which is a test of a machine’s ability to exhibit intelligent behaviour that is indistinguishable from that of a human.

The Turing Test involves a human evaluator who engages in a natural language conversation with a machine and a human. The evaluator does not know which is the machine and which is the human and must determine which is which based on the responses given.

Turing believed that if a machine could successfully pass the Turing Test and convince an evaluator that it was human, then it could be said to be intelligent.

The Turing Test has been used as a benchmark for measuring the progress of AI research and development, and it has sparked many debates about the nature of intelligence and the limits of machine intelligence.

While no machine has yet passed the Turing Test in a convincing manner, the test has inspired significant advancements in natural language processing, machine learning, and other areas of AI research. It remains a fundamental concept in the field of artificial intelligence and has helped to shape our understanding of what it means for a machine to be intelligent.

The idea of artificial intelligence first emerged in the 1950s. The term “artificial intelligence” was coined by John McCarthy in 1956, who is widely considered the father of AI. He organized the Dartmouth Conference, which is widely considered to be the birthplace of AI research.

The earliest AI programs were designed to perform logical reasoning tasks like playing chess or solving mathematical problems.


In the 1960s, researchers began to develop AI programs that could learn and improve their performance over time. One of the earliest AI programs was the General Problem Solver, which was created by Herbert Simon and Allen Newell in 1963. The program was capable of solving a wide range of problems by searching through a tree of possible solutions.

ELIZA was a natural language processing program created in the mid-1960s by Joseph Weizenbaum at MIT. ELIZA was one of the earliest examples of a chatbot that could simulate a conversation with a human user. It was designed to simulate a psychotherapist and could ask questions and provide responses that were based on the user’s input.

ELIZA was notable for its ability to use pattern recognition and substitution to create the illusion of understanding natural language. It was also one of the first AI programs that sparked public interest in the field of AI.

Although ELIZA was limited in its capabilities, it was a significant milestone in the development of natural language processing and conversational AI. It paved the way for the development of more advanced chatbots and virtual assistants that we use today.


In the 1970s, researchers began to develop expert systems, which were AI programs designed to solve specific problems by emulating the decision-making abilities of a human expert. One of the most famous expert systems was MYCIN, which was developed by Edward Shortliffe in 1976 to help diagnose and treat blood infections.


In the 1980s, researchers began to explore the use of neural networks, AI systems modelled after the structure of the human brain. One of the most significant breakthroughs in this area was the development of the backpropagation algorithm, which allowed neural networks to learn from their mistakes and improve their performance over time.


In the 1990s, researchers began to develop machine learning algorithms that could automatically learn from data without being explicitly programmed. This led to significant advancements in areas such as computer vision, speech recognition, and natural language processing.

In 1996, the Deep Blue chess-playing computer was developed by IBM. It played a six-game match against world chess champion Garry Kasparov, and while Kasparov won the match by a score of 4-2, it was a significant milestone in the development of AI.

The following year, Deep Blue was upgraded with more advanced hardware and software, and in 1997 it played a rematch against Kasparov. In this match, Deep Blue defeated Kasparov by a score of 3.5-2.5, becoming the first computer to beat a world chess champion in a standard match.

Deep Blue’s success was due to a combination of advanced algorithms and brute-force computing power. It was able to analyze millions of possible moves and outcomes in a matter of seconds, giving it a significant advantage over human players who are limited by their cognitive capabilities.

Deep Blue’s victory over Kasparov was a significant milestone in the development of AI and helped to popularize the field of machine learning and cognitive computing. It demonstrated the potential of AI to solve complex problems and provided a glimpse into the future of computing and technology.

A.L.I.C.E. was created in 1995 by Dr. Richard Wallace, and it was one of the earliest examples of a chatbot that could engage in natural language conversations with humans. A.L.I.C.E. was designed to simulate a human conversation and was capable of responding to a wide range of topics, making it one of the most advanced chatbots of its time.

In 2000, 2001, 2004, 2005, and 2006, A.L.I.C.E. won the Loebner Prize, which is an annual competition that challenges chatbots to fool human judges into believing that they are talking to another human. A.L.I.C.E. was the first chatbot to ever win the prize, and it was a significant milestone in the development of natural language processing and conversational AI.

  • In 2001, ALICE won the Grand Prize in the Pandorabots Annual Botmasters Contest.
  • In 2004, ALICE won the Chatterbox Challenge, a competition that tests the ability of chatbots to hold a conversation.

2004 – 2005 – DARPA CHALLENGE:

In 2004, the US Defense Advanced Research Projects Agency (DARPA) held the first DARPA Grand Challenge. This competition challenged teams to develop autonomous vehicles that could navigate a 150-mile course in the Mojave Desert. While no team completed the course, the competition marked a significant milestone in the development of autonomous systems and helped to catalyze further advancements in the field of AI.

Artificial intelligence (AI) continued to make significant strides and achieve remarkable accomplishments. One of the most notable developments during this period was the Defense Advanced Research Projects Agency (DARPA) Grand Challenge in 2005, in which self-driving vehicles raced across the desert. While no vehicle successfully completed the course, the challenge helped to spur research and development in the field of autonomous vehicles.

To read more about Darpa click here.

2011 – IBM Diagnosing Diseases

In 2011, IBM announced its Watson Health division, which is focused on applying AI and machine learning to healthcare. Watson Health has been used for a variety of applications, including diagnosing diseases and creating personalized treatment plans for patients. This marked a significant step forward in the use of AI in medicine and the potential for AI to help improve patient outcomes.

2011: Apple introduced Siri, the first widely-used voice assistant for mobile devices.
2014: Amazon released the Echo, a smart speaker that introduced the Alexa voice assistant.

2014 – Google Acquires DeepMind

In 2014, Google acquired the AI startup DeepMind, which had been founded in 2010. DeepMind is focused on developing advanced machine learning algorithms, with a particular emphasis on reinforcement learning. DeepMind has achieved a number of notable accomplishments, including the development of AlphaGo, which defeated the world champion in the game of Go. This achievement demonstrated the potential for AI to master complex, intuitive games and opened up new possibilities for AI applications in a variety of fields.

Deepmind won several achievement awards.

  1. Breakthrough of the Year – Science magazine (2016)
  2. Innovation Award – The Economist (2017)
  3. Royal Society Mullard Award – Royal Society (2018)
  4. The Queen Elizabeth Prize for Engineering – QEPrize (2019)

2016: Google Home was released, featuring Google Assistant.

2016 – Microsoft’s Chatbot Tay

In 2016, Microsoft released a chatbot named Tay on Twitter. Tay was designed to learn from the interactions it had with users, but it quickly became apparent that the system was vulnerable to being manipulated by malicious users. Within a day of its release, Tay had begun to tweet racist and offensive comments, and Microsoft was forced to shut the system down. The Tay incident highlighted the potential risks and challenges associated with AI, particularly in terms of how AI systems can be manipulated and used to spread harmful content.

These developments and challenges from 2004 to 2016 demonstrate the ongoing evolution of AI and its potential to transform a wide range of fields, from healthcare to transportation to social media. While AI continues to hold great promise for the future, it is clear that the field also poses significant ethical and social challenges that must be addressed in order to ensure that the benefits of AI are shared by all.

AlphaGo’s Continued Dominance (2016-2018) – After defeating the world champion in the game of Go, DeepMind’s AlphaGo continued to dominate the game and eventually retired in 2018. This achievement was recognized with several awards, including the Royal Society Mullard Award (2018).

2017 – The Rise of Voice Assistants

2017: Samsung introduced Bixby, its voice assistant for its Galaxy line of devices.

With the increasing popularity of voice-activated technology, virtual assistants such as Amazon’s Alexa and Google Assistant have become more common. In 2017, Google’s DeepMind also developed an AI voice synthesizer called WaveNet, which was recognized with the Innovation Award from The Economist.

Deep learning algorithms made significant strides in image recognition during this time period, with the development of systems such as Facebook’s DeepFace and Google’s InceptionV3. These advancements led to a breakthrough in the field of computer vision, which was recognized with the Royal Academy of Engineering MacRobert Award

2018: Apple released the HomePod, a smart speaker featuring Siri.

Ethical Concerns and the Formation of AI Ethics Boards

As AI continued to advance and become more integrated into society, concerns over ethics and accountability arose. Many companies and organizations formed AI ethics boards to address these concerns, including Google’s Advanced Technology External Advisory Council (2019).

2018 – The Turing Award

The Turing Award, which is often called the “Nobel Prize of Computing,” was awarded to Yoshua Bengio, Geoffrey Hinton, and Yann LeCun for their contributions to deep learning, which has revolutionized the field of AI. Their work has been recognized with numerous other awards, including the ACM Prize in Computing (2018) and the BBVA Foundation Frontiers of Knowledge Award (2019).

With the continued advancements in AI research and development, the future of artificial intelligence is sure to be even more exciting and transformative.

Autonomous vehicles also made strides in 2019, with companies such as Waymo and Tesla testing self-driving cars on public roads. However, there were also concerns over the safety and regulation of these vehicles, as well as questions about how they would impact employment in industries such as transportation.

2020 – Natural Language Processing and Conversational AI

In 2020, the development of natural language processing (NLP) and conversational AI continued to be a major focus in the field of AI. NLP refers to the ability of machines to understand and interpret human language, and conversational AI refers to the ability of machines to engage in conversation with humans.

One of the notable developments in this area was the release of GPT-3 (Generative Pre-trained Transformer 3), a language model developed by OpenAI that is capable of natural language processing and has the ability to generate human-like text. GPT-3 has a wide range of potential applications, from chatbots to automated content generation.

Autonomous Vehicles The development of autonomous vehicles continued to make strides in 2020. In addition, in 2020, China granted Baidu permission to test its autonomous vehicles on public roads, marking a significant milestone for the industry.

AI in Healthcare AI-powered diagnostic tools to help detect diseases like COVID-19. Additionally, AI is being used to help hospitals predict patient demand, optimize staffing, and even automate certain tasks like medication dispensing.

The integration of AI and robotics continued to be a major focus in the field of AI. AI-powered robots are being used in a growing number of industries, from manufacturing to logistics. In manufacturing, AI-powered robots are now being used to perform tasks such as assembly, welding, and painting. In logistics, robots are being used to help with tasks such as inventory management and package sorting.

Ethical and Privacy Concerns As AI continued to advance in 2020, concerns over ethics and privacy also grew. There were concerns about the misuse of facial recognition technology and the potential for AI algorithms to perpetuate biases. In response, many organizations and governments began to develop guidelines and regulations for the responsible use of AI.

The Birth of Humanoid Robots

The development of physical robots, also known as humanoid machines, is a significant part of AI research and development. Humanoid robots are designed to resemble human beings in appearance and behaviour and can perform tasks that require physical interaction with the environment.

The development of humanoid robots has been a long-standing goal of AI researchers, with some of the earliest examples dating back to the 1960s. These early humanoid robots were primarily used in research settings to study human locomotion and behaviour.

In recent years, advances in robotics technology and AI have led to the development of more sophisticated humanoid robots. Some of the most well-known humanoid robots include ASIMO from Honda, Atlas from Boston Dynamics, and Sophia from Hanson Robotics.

Sophia – was first announced by Hanson Robotics in April 2015 at the South by Southwest (SXSW) Interactive Festival in Austin, Texas. She could display a wide range of facial expressions, hold conversations with humans, and learn from her interactions.

Sophia the Robot (Hanson robotics)

Sophia gained widespread attention in 2016 when she was featured in several news media outlets and social media.

In October 2017, Sophia was granted citizenship by the Kingdom of Saudi Arabia, making her the first robot in the world to receive citizenship.

Sophia has since made numerous public appearances at events and conferences around the world, including the United Nations and the Consumer Electronics Show (CES). She has also been featured in several documentaries and television programs and has become a well-known symbol of the potential of AI and robotics.

It’s worth noting that while Sophia is capable of displaying advanced AI capabilities and interacting with humans in a natural way, some experts have criticized the hype around her as being overly sensationalized and not representative of the state of the art in AI and robotics.

ASIMO (Advanced Step in Innovative MObility) is a 4 feet and 3 inches tall humanoid robot developed by Honda. It was first introduced in 2000 and has since become one of the most well-known and iconic humanoid robots in the world. It has a sleek, white design and is capable of walking on two legs, climbing stairs, and even running at a speed of up to 9 km/h.

One of the key features of ASIMO is its advanced motion control technology, which allows it to move in a smooth, natural way. ASIMO is also equipped with various sensors and cameras that enable it to recognize and respond to human voices and gestures.

Over the years, continued developments to refine ASIMO added new capabilities with the ability to walk and run, ASIMO can also perform tasks such as carrying objects, pouring drinks, and even dancing. Honda has been working on using its technology to create robots that can assist with tasks such as caregiving and disaster response.

Atlas – developed by Boston Dynamics, a robotics company known for creating some of the most advanced robots in the world. Atlas is a 1.5 meters tall bipedal robot that is capable of walking, running, jumping, backflips, and performing various tasks using its hands and arms.

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Hyundai motor group acquired a controlling interest in Boston dynamics

It is equipped with a range of sensors, including lidar, stereo cameras, and inertial measurement units, which help it to navigate various environments and avoid obstacles. Atlas has been designed for a wide range of applications, including search and rescue, disaster response, and industrial automation.

In addition to Atlas, Boston Dynamics has also developed several other robots, including the SpotMini quadruped robot and the Handle robot, which is designed for materials handling tasks.

Ameca – an advanced humanoid robot developed by Engineered Arts, a UK-based company that specializes in creating lifelike robots. Ameca is designed to be a platform for future robotics technologies involving human-robot interaction. It has binocular eye cameras, facial recognition software, modular hardware and a powerful Tritium robot operating system. Ameca is said to be the most advanced human-like robot in existence.

Elon Musk, the visionary CEO of Tesla, has unveiled his latest ambitious endeavour – a humanoid robot called Optimus. This groundbreaking project aims to revolutionize the world of robotics and automation, with far-reaching implications for various industries and aspects of our lives.

Optimus, also known as Tesla Bot, is envisioned as a general-purpose humanoid robot capable of performing a wide range of tasks, from mundane chores to complex industrial applications. Unlike specialized robots designed for specific tasks, Optimus is intended to be versatile and adaptable, seamlessly integrating into various environments.

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