by Rockwell Anyoha

Can Machines Think?

In the first half of the 20th century, science fiction familiarized the world with the concept of artificially intelligent robots. It began with the “heartless” Tin man from the Wizard of Oz and continued with the humanoid robot that impersonated Maria in Metropolis. By the 1950s, we had a generation of scientists, mathematicians, and philosophers with the concept of artificial intelligence (or AI) culturally assimilated in their minds. One such person was Alan Turing, a young British polymath who explored the mathematical possibility of artificial intelligence. Turing suggested that humans use available information as well as reason in order to solve problems and make decisions, so why can’t machines do the same thing? This was the logical framework of his 1950 paper, Computing Machinery and Intelligence in which he discussed how to build intelligent machines and how to test their intelligence.

Making the Pursuit Possible

Unfortunately, talk is cheap. What stopped Turing from getting to work right then and there? First, computers needed to fundamentally change. Before 1949 computers lacked a key prerequisite for intelligence: they couldn’t store commands, only execute them. In other words, computers could be told what to do but couldn’t remember what they did. Second, computing was extremely expensive. In the early 1950s, the cost of leasing a computer ran up to $200,000 a month. Only prestigious universities and big technology companies could afford to dillydally in these uncharted waters. A proof of concept as well as advocacy from high profile people were needed to persuade funding sources that machine intelligence was worth pursuing.

The Conference that Started it All

Five years later, the proof of concept was initialized through Allen Newell, Cliff Shaw, and Herbert Simon’s, Logic Theorist. The Logic Theorist was a program designed to mimic the problem solving skills of a human and was funded by Research and Development (RAND) Corporation. It’s considered by many to be the first artificial intelligence program and was presented at the Dartmouth Summer Research Project on Artificial Intelligence (DSRPAI) hosted by John McCarthy and Marvin Minsky in 1956. In this historic conference, McCarthy, imagining a great collaborative effort, brought together top researchers from various fields for an open ended discussion on artificial intelligence, the term which he coined at the very event. Sadly, the conference fell short of McCarthy’s expectations; people came and went as they pleased, and there was failure to agree on standard methods for the field. Despite this, everyone whole-heartedly aligned with the sentiment that AI was achievable. The significance of this event cannot be undermined as it catalyzed the next twenty years of AI research.

Roller Coaster of Success and Setbacks

From 1957 to 1974, AI flourished. Computers could store more information and became faster, cheaper, and more accessible. Machine learning algorithms also improved and people got better at knowing which algorithm to apply to their problem. Early demonstrations such as Newell and Simon’s General Problem Solver and Joseph Weizenbaum’s ELIZA showed promise toward the goals of problem solving and the interpretation of spoken language respectively. These successes, as well as the advocacy of leading researchers (namely the attendees of the DSRPAI) convinced government agencies such as the Defense Advanced Research Projects Agency (DARPA) to fund AI research at several institutions. The government was particularly interested in a machine that could transcribe and translate spoken language as well as high throughput data processing. Optimism was high and expectations were even higher. In 1970 Marvin Minsky told Life Magazine, “from three to eight years we will have a machine with the general intelligence of an average human being.” However, while the basic proof of principle was there, there was still a long way to go before the end goals of natural language processing, abstract thinking, and self-recognition could be achieved.

Anyoha SITN Figure 2 AI timeline

Breaching the initial fog of AI revealed a mountain of obstacles. The biggest was the lack of computational power to do anything substantial: computers simply couldn’t store enough information or process it fast enough. In order to communicate, for example, one needs to know the meanings of many words and understand them in many combinations. Hans Moravec, a doctoral student of McCarthy at the time, stated that “computers were still millions of times too weak to exhibit intelligence.”  As patience dwindled so did the funding, and research came to a slow roll for ten years.

In the 1980’s, AI was reignited by two sources: an expansion of the algorithmic toolkit, and a boost of funds. John Hopfield and David Rumelhart popularized “deep learning” techniques which allowed computers to learn using experience. On the other hand Edward Feigenbaum introduced expert systems which mimicked the decision making process of a human expert. The program would ask an expert in a field how to respond in a given situation, and once this was learned for virtually every situation, non-experts could receive advice from that program. Expert systems were widely used in industries. The Japanese government heavily funded expert systems and other AI related endeavors as part of their Fifth Generation Computer Project (FGCP). From 1982-1990, they invested $400 million dollars with the goals of revolutionizing computer processing, implementing logic programming, and improving artificial intelligence. Unfortunately, most of the ambitious goals were not met. However, it could be argued that the indirect effects of the FGCP inspired a talented young generation of engineers and scientists. Regardless, funding of the FGCP ceased, and AI fell out of the limelight.

Ironically, in the absence of government funding and public hype, AI thrived. During the 1990s and 2000s, many of the landmark goals of artificial intelligence had been achieved. In 1997, reigning world chess champion and grand master Gary Kasparov was defeated by IBM’s Deep Blue, a chess playing computer program. This highly publicized match was the first time a reigning world chess champion loss to a computer and served as a huge step towards an artificially intelligent decision making program. In the same year, speech recognition software, developed by Dragon Systems, was implemented on Windows. This was another great step forward but in the direction of the spoken language interpretation endeavor. It seemed that there wasn’t a problem machines couldn’t handle. Even human emotion was fair game as evidenced by Kismet, a robot developed by Cynthia Breazeal that could recognize and display emotions.

Time Heals all Wounds

We haven’t gotten any smarter about how we are coding artificial intelligence, so what changed? It turns out, the fundamental limit of computer storage that was holding us back 30 years ago was no longer a problem. Moore’s Law, which estimates that the memory and speed of computers doubles every year, had finally caught up and in many cases, surpassed our needs. This is precisely how Deep Blue was able to defeat Gary Kasparov in 1997, and how Google’s Alpha Go was able to defeat Chinese Go champion, Ke Jie, only a few months ago. It offers a bit of an explanation to the roller coaster of AI research; we saturate the capabilities of AI to the level of our current computational power (computer storage and processing speed), and then wait for Moore’s Law to catch up again.

Artificial Intelligence is Everywhere

We now live in the age of “big data,” an age in which we have the capacity to collect huge sums of information too cumbersome for a person to process. The application of artificial intelligence in this regard has already been quite fruitful in several industries such as technology, banking, marketing, and entertainment. We’ve seen that even if algorithms don’t improve much, big data and massive computing simply allow artificial intelligence to learn through brute force. There may be evidence that Moore’s law is slowing down a tad, but the increase in data certainly hasn’t lost any momentum. Breakthroughs in computer science, mathematics, or neuroscience all serve as potential outs through the ceiling of Moore’s Law.

The Future

So what is in store for the future? In the immediate future, AI language is looking like the next big thing. In fact, it’s already underway. I can’t remember the last time I called a company and directly spoke with a human. These days, machines are even calling me! One could imagine interacting with an expert system in a fluid conversation, or having a conversation in two different languages being translated in real time. We can also expect to see driverless cars on the road in the next twenty years (and that is conservative). In the long term, the goal is general intelligence, that is a machine that surpasses human cognitive abilities in all tasks. This is along the lines of the sentient robot we are used to seeing in movies. To me, it seems inconceivable that this would be accomplished in the next 50 years. Even if the capability is there, the ethical questions would serve as a strong barrier against fruition. When that time comes (but better even before the time comes), we will need to have a serious conversation about machine policy and ethics (ironically both fundamentally human subjects), but for now, we’ll allow AI to steadily improve and run amok in society.

Rockwell Anyoha is a graduate student in the department of molecular biology with a background in physics and genetics. His current project employs the use of machine learning to model animal behavior. In his free time, Rockwell enjoys playing soccer and debating mundane topics.

This article is part of a Special Edition on Artificial Intelligence.

For more information:

Brief Timeline of AI

https://www.livescience.com/47544-history-of-a-i-artificial-intelligence-infographic.html

Complete Historical Overview

http://courses.cs.washington.edu/courses/csep590/06au/projects/history-ai.pdf

Dartmouth Summer Research Project on Artificial Intelligence

https://www.aaai.org/ojs/index.php/aimagazine/article/view/1904/1802

Future of AI

https://www.technologyreview.com/s/602830/the-future-of-artificial-intelligence-and-cybernetics/

Discussion on Future Ethical Challenges Facing AI

http://www.bbc.com/future/story/20170307-the-ethical-challenge-facing-artificial-intelligence

Detailed Review of Ethics of AI

https://intelligence.org/files/EthicsofAI.pdf

246 thoughts on “The History of Artificial Intelligence

  1. During the Times Heals all wounds you say that “holding us back 30 years ago was no longer a problem. , which estimates that the ” the , is supposed to have the words Moore’s Law infront of it the article was a great thing though thank you for the information and apologies for being nitpicky.

    1. iam a new student of AI and i need your help during my research reports/thesis

      am from Uganda +256 East Africa.

  2. Intelligence is not common to everyone. If you are smart enough to figure out problems and solve without much stress, then you are intelligent. AI is still no match for human intelligence but its quite unbelievable hearing scientists create supercomputers that operate faster than the human brain.

  3. Thanks for the article explaining the history of Artificial Intelligence from head to toe. But there is a mistake in it.
    “This is precisely how Deep Blue was able to defeat Gary Kasparov in 1997, and how Google’s Alpha Go was able to defeat Chinese Go champion, Kie Je, only a few months ago.” The name should be “Ke Jie” not “Kie Je”. Hope this can be corrected soon.

  4. In the section The Future it states “Even if the capability is there, the ethically would serve as a strong barrier against fruition. ” Maybe switch ‘ethically’ to ‘ethical questions’ or ‘ethical feasibility.’ Sorry for nit picking, otherwise great article.

  5. The information is great, it’s been a long time since last time I read a long story. I have more understanding about AI. Thanks.

  6. I am a fifth grader, and I found this topic to be so interesting I decided to do a research project on it and at first I had trouble on finding sources, but once I found this I loved it! Everything in this passage was useful and I also absorbed a lot from it. I would like to say thank you very much to the author for helping me make my research project a success and i look forward to absorbing more into the topic through articles that Rockwell Anyoha hopefully makes. Again thank you very much! With all the information this article provided I was able to create a college leveled essay about Artificial Intelligence!

  7. Dear Rockwell,
    thank you for your interesting overview!!
    One question: What does the Y-achsis in your graphic stand for?
    Thanks for answering!
    C

  8. Punctuation typo in “Time Heals All Wounds” section:
    “`30 years ago was no longer a problem. , which estimates`”

  9. You’re so cool! I do not believe I’ve read anything like that before. So great to discover somebody with some original thoughts on this subject matter. Seriously.. many thanks for starting this up. This web site is one thing that’s needed on the web, someone with some originality!

  10. A speed of the actions, performed by this kind of AI, is the same as the human brain, but the quality of tasks is much higher. It can be compared to the fact of how people are higher by their intelligence from the animals. Both are smart, by it is clear who is able to do more, in the shortest period of time, and with higher quality, in the result.
    This article is food for thought, by no means.

  11. science is trying so much by artificial intelligence but still not succeed. but maybe one day they can. thanks for your post

  12. A ery good article that explains the history of AI very well. Would have liked a little bit about the history of AI in healthcare so far, to prepare us for the courses ahead.

  13. A great piece of information. It takes a while to go through this article, but it is very resourceful. Thanks for sharing. Helped a lot.

  14. Good things come to people who wait, but better things come to those who go out and get them (Good luck to all Harvard undergraduate students)

  15. Amazing history of AI, We know that Artificial Intelligence is a computer science that develops programs to mimic human intelligence. The level of intelligence may range from recognizing patterns in data to deriving insights for problem solving.

  16. A great piece of information. And a lot more on the comments. This helps me some get some more ideas for my next article on Artificial Intelligence. Thanks for sharing. It helped a lot.

    1. I totally agree with Peter Lee. This is an excellent blog on AI history. Looking forward to reading such articles ahead to get more inspiration and the knowledge shared.

  17. “The History of Artificial Intelligence” wow nice title and article also, thanks for this awesome tutorial. you give the best article to your readers.

  18. Wonderful information about the AI, with the help of artificial intelligence the scientists are making the robots that will do behave like humans ,its a great achievement for us ,thanks for sharing this important achievement with us.

  19. Hello Rockwell Anyoha
    Thanks for sharing a good information related to AI and included health data and best transparency

  20. Hello!
    This was an awesome article and histogram.

    I hope that you continue to expand more and include information about the use of simulation in the AI process and the General Problem Solver in terms of AI advancement.
    Those two topics will help the readers deeply understand two important foundational concepts behind how AI came to be.

    I appreciate the shared links from everyone too.
    Great article.
    Thank you

  21. Machines can work as they are programmed, but Yes, now with advancement of technology programming can made that machine react according to circumstances, most probably which means they can think, but it is just program made by humans.

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  31. Very interesting topic about Artificial Intelligence. It’s crazy how far we’ve become in the last 20 years where AI was almost unheard of and now you can use it for customer service chat bots, smart phones and it is embedded in so much app development at this point.

    I just hope it doesn’t get out of hand once AI gets smarter and used for military purposes.

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  35. I think that robots with deadly Force should only be operated by human law enforcement

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  86. AI is the best answer to the question, “can machines think?” AI enables machines to not only think but also to make good decisions by distinguishing between good and bad.

  87. Thanks for sharing this information with us.
    It is intelligence demonstrated by machines, as opposed to the natural intelligence displayed by animals including humans.

  88. It is intelligence demonstrated by machines, as opposed to the natural intelligence displayed by animals including humans.

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  94. it would be great, if there were some examples in the text. It is interesting how such work is carried out when it comes to animals. Maybe any more articles or videos to have a look?))

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  98. Thanks for sharing your thoughts on artificial intelligence. AI has the potential to change our lives in countless ways, especially because it seems like every company is integrating AI into something. There are many different ways to define AI, but for our purposes, we’ll focus on AI as computer programs that read data, learn from it, and draw logical conclusions based on that data.

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  100. It’s hard to believe that artificial intelligence has only been around for a few decades. In that short time, AI has made incredible progress, and today it is being used in a variety of ways, from medical diagnosis to automated customer service. But what does the future hold for AI? Some experts believe that AI will eventually surpass human intelligence, leading to a “singularity” in which machines can take over many of the tasks currently performed by humans. Other experts are more cautious, warning that AI could be used to control and manipulate people rather than help them. What is certain is that AI will continue to evolve as we are making more VR applications, and its impact on our world will only grow in the years to come.

  101. It is understood that machines can think by using artificial intelligence. Machine learning and deep learning are techniques used in AI to make machines think like humans. In this field, we can see computers performing tasks better than a human and it has become an essential part of daily activities.

  102. No mention of John Von Neumann? Who do you think wrote the book on how to store data? Manchester Mark 1 was based on his architecture.

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  105. Businesses use artificial intelligence for a variety of purposes, including data aggregation and job process streamlining. Artificial intelligence (AI) technology is also used by many businesses in an effort to lower operating expenses, boost productivity, boost sales, and enhance customer experience.

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    1. It is a matter of debate whether or not machines can truly “think” in the same way that humans do. Some people believe that machine learning algorithms and artificial intelligence systems are capable of thinking, as they can perform tasks that would be considered intelligent if a human were to do them. For example, some AI systems are able to recognize patterns, make decisions, and even learn from their experiences, much like a human being.

  107. I enjoyed how “Artificial Intelligence is Everywhere” was developed. The world is being transformed by artificial intelligence. AI has an influence on almost everything around us. Furthermore, I believe AI in mobile app development is thriving in the context of AI. Because it lowers the overall cost of developing a mobile app.

  108. Isaac Asimov was one of science fiction writers imagined Artificial Intelligence and Machine Learning as early as the 1940s. His ideas on AI are expressed through Robots which take on human or humanoid forms (Androids). The seeds of modern AI were planted by early philosophers who explained human thinking as the mechanical manipulation of symbols. Alan Turing, a British mathematician and computer scientist proposed the concept of Artificial Intelligence in the year 1950 with his work titled “Computing Machinery and Intelligence.”.

    AI with large data, larger RAM and high computing power makes supercomputing synonymous with AI. Quantum computing and artificial intelligence is ideal marriage to achieve significant progress.  We can accurately diagnosing diseases, improving online learning and making humans potentially obsolete. We may teach AI not to kill by making laws hardwired in AI algorithms or make human, human health and human rights priority #1 while launching any AI application.

  109. It is a matter of debate whether or not machines can truly “think” in the same way that humans do. Some people believe that machine learning algorithms and artificial intelligence systems are capable of thinking, as they can perform tasks that would be considered intelligent if a human were to do them. For example, some AI systems are able to recognize patterns, make decisions, and even learn from their experiences, much like a human being.

    However, others argue that true thinking requires consciousness, self-awareness, and other qualities that are uniquely human and that machines do not possess. It is also important to note that there is still much we do not understand about human thought and consciousness, so it is difficult to definitively say whether or not machines can think in the same way that we do. Ultimately, the question of whether or not machines can think is a complex and multifaceted one that depends on how we define “thinking” and what we consider to be the essential qualities of thought.

  110. Wow! I just found out that the early development of AI was discovered in the early 20th century. Previously I thought it was just discovered in the 21st century

  111. A.I. will become increasingly important in the future, and we need to ensure that we take the right steps to maximize its benefits. Thank you!

  112. Good As far as me being a member here, I wasn’t aware that I was a member for any days, actually. When the article was published I received a notification, so that I could participate in the discussion of the post, That would explain me stumbuling upon this post. But we’re certainly all members in the world of ideas.

  113. Veritably nice write-up!! The position of engagement in your content made me stick to your blog post. disquisition and looking for the occasion can be a way toward growth, reaching the top now. Will be staying for your coming post!!! You have mentioned veritably useful points in the blog. Reach a famed web and mobile app development company for trending ideas and strategies.

  114. Hey just wanted to give you a quick heads up.
    The text in your article seem to be running off the screen in Safari.
    I’m not sure if this is a formatting issue or something to do with browser compatibility but I figured I’d post to let you know.
    The layout look great though! Hope you get the issue resolved soon.

  115. Fantastic article . It is really interesting to read this article in 2023 with the release of chatgpt and talks of googles next AI.

  116. Hello, in the picture of the timeline, you dont have a description of what the blue line represents. i assume its about funding, but i would like to know excactly what the numbers are for.

    1. Just asked the same question. I would like to credit this blog-post, but I would like to know what I am looking at 🙂

  117. An excellent summary of the application of machine learning to time series forecasting can be found in this paper. The author does a fantastic job of laying out the ideas and methods involved in using AI for this purpose and offers succinct and understandable examples to support his arguments. The essay also discusses the numerous difficulties encountered while working with time series data and provides workable answers to these difficulties. I thought this essay was overall well-written and educational, and I heartily suggest it to anyone curious about learning how AI is used for time series forecasting.

  118. I enjoyed how “Artificial Intelligence is Everywhere” was developed. The world is being transformed by artificial intelligence. AI has an influence on almost everything around us. Furthermore, I believe AI in mobile app development is thriving in the context of AI. Because it lowers the overall cost of developing a mobile app.

  119. I think the first Dragon Speech recognition software was released in about 1990. The Mac had speech recognition perhaps 2-3 years later. The 1997 Dragon software was merely a release for Windows years after its firs release which was probably for MS or PCDOS.

  120. Oh, I’m amazed! I’ve just learned that the early exploration of AI dates back to the early 20th century. Before, I had always believed it was only discovered in the 21st century.

  121. In the ARTIFICIAL INTELLIGENCE TIMELINE you attribute a quote to “Arthur C. Clarke and Steve Kubrik”. I could find no reference on the ‘net to “Steve Kubrik.” Did you mean Stanley Kubrick? (And this must have been in reference to the AI character of HAL-9000 in _2001_, a book by Clarke and a film of the same name by Kubrick.)

    Also, I agree with other commenters that the Y axis in this graph needs a legend. (And it would be VERY interesting to see how this graph looks if you extend the X axis to the current LLM era.)

  122. I would like to express my sincere appreciation for the insightful article titled “A Brief History of Artificial Intelligence” published on https://sitn.hms.harvard.edu/flash/2017/history-artificial-intelligence/. The article brilliantly traces the evolution of artificial intelligence (AI) and provides a comprehensive overview of its historical milestones. It not only presents the major breakthroughs in AI research but also delves into the societal impact and ethical considerations associated with this transformative field. The clear and concise writing style, coupled with the inclusion of relevant examples and references, makes it an engaging and informative read. This article serves as a valuable resource for anyone interested in understanding the origins and progression of AI. I commend the authors and the website for their efforts in delivering such exceptional content to the readers.

  123. It’s really nice to know about AI history as it’s going to write it’s own new future in upcoming years.

  124. If you don”t mind proceed with this extraordinary work and I anticipate a greater amount of your magnificent blog entries. 

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