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Who is Yann LeCun: How A Movie Changed The World

Few people have left their mark in machine learning and computing more than Yann LeCun. This founder of convolutional neural networks is dead set on bringing AI to help humanity. But, who is he really?
Updated March 21, 2024
Yann LeCun in the set of 2001: A Space Odyssey, generated with Midjourney
Yann LeCun in the set of 2001: A Space Odyssey, generated with Midjourney

As human beings, we’re thrust into the responsibility of being pioneers — of not just being shepherds of this world but also improving it. Watch it grow, experience its losses, and try again. 

We’ve done this time and time again through technology. Babbage’s mechanical computer. The Enigma Machine. Apollo 11. Internet and social media. And now, we’re embarking on the next step of computing: artificial intelligence.

This journey starts with the people who are leading us into this new age. Not just the CEOs like Elon Musk, Sam Altman, and Mark Zuckerberg, but the people who understand AI and deep learning on a foundational level and know how we can navigate this brave new world. People like Yann LeCun.

Later in this article, you’ll learn every little detail in Yann LeCun’s life and his work on machine learning. That includes his education, how he made his mark in the industry, the awards he received, and what he’s up to now. 

From Paris, With Love: Early Life and Education

As a young boy, Yann LeCun spent his formative years in France, in the suburban areas surrounding Paris. His last name was originally “Le Cun,” until he dropped the whitespace upon learning that Americans might confuse “Le” for his middle name — but that will come much, much later.

For now, let’s go back to when he was nine years old. Somewhere in Paris, Kubrick’s 2001: A Space Odyssey was playing, and LeCun was lucky enough to catch a screening. It was on this day, after seeing HAL, that LeCun became interested in machine learning — this is when he started his journey toward artificial intelligence and changed the world of computing as we know it.

He finished his Bachelor’s in ESIEE Paris and obtained a PhD in Computer Science from Sorbonne University. During his doctorate years, he started working on a then-theoretical backpropagation method for neural networks, allowing them to learn by self-adjusting weights to reduce errors. 

Little did he know that somewhere, hundreds of miles away, another rising star in machine learning was working on the same concepts. His name is Geoffrey Hinton.

LeCun’s Breakthroughs in Machine Learning

LeCun and Hinton became acquainted in the mid-1980s and soon became lifelong friends. They would later establish a Neural Computation and Adaptive Perception program through the Canadian Institute for Advanced Research. As of 2014, LeCun is still at the helm of the program, now called Learning in Machines & Brains, along with Yoshua Bengio.

LeCun, Hinton, and Bengio. Those names are forever etched in the history of artificial intelligence as the “Godfathers of Deep Learning.”

But what exactly did LeCun do to earn that title? 

After earning his doctorate, LeCun started working in Bell Labs, a world-renowned center for computer science research. During his time there, he developed three important algorithms:

  • Convolutional Neural Networks: A subset of neural networks that use filters to the input to detect local patterns and features, making it smaller and more efficient. It relies on backpropagation for self-learning. CNNs are used in image recognition to this day. 
  • Graph Transformer Networks: In collaboration with Hinton and other scientists, LeCun developed a system that can recognize printed and handwritten text. More than 10% of all checks in the USA are processed using GTNs. This would soon revolutionize optical character recognition.
  • Optimal Brain Damage: A regularization method that efficiently removes unnecessary nodes in neural networks.

LeCun is also interested in fostering the next generation of computer scientists. He joined NYU as a tenured professor in 2003, teaching in fields such as computer vision and mobile robotics. In 2012, he was named the inaugural director of the NYU Center for Data Science, something that he had to give up two years later to focus on his next venture.

Where Is He Now?

Yann LeCun joined Facebook (now Meta) in December 2013. Since joining Facebook, LeCun was able to implement his knowledge in AI to reduce hate speech and misinformation in the platform by 88% in 2020.

AI at Meta Landing Page

With OpenAI’s sudden burst into the scene, other companies shifted from using AI to streamline their services to offering AI as a standalone product. Earlier this month, Mark Zuckerberg officially announced that he’s putting all his eggs in the basket and they’ll start developing an AGI.

LeCun’s Awards and Recognition

In 2018, Yann LeCun received the Nobel Prize for Computing (Turing Award), the highest recognition in the field of computer science. He shared this award with Bengio and Hinton.

Over the years, he also received numerous awards, such as:

  • 2014: IEEE Neural Network Pioneer Award
  • 2015: PAMI Distinguished Researcher Award
  • 2018: IRI Medal from the Industrial Research Institute (IRI)
  • 2018: Harold Pender Award from the University of Pennsylvania
  • 2019: Golden Plate Award from the American Academy of Achievement
  • 2022: Princess of Asturias Award in Scientific Research, along with Yoshua Bengio, Geoffrey Hinton and Demis Hassabis
  • 2023: Chevalier (Knight) of the French Legion of Honour by the President of France
  • 2024: Global Swiss AI Award 2023 at the World Economic Forum (WEF) in Davos

The Future of AI in LeCun’s Perspective

Unlike Sam Altman, Yann LeCun doesn’t believe that human-level AI is just around the corner. He states that artificial intelligence at this level would require a multitude of breakthroughs before becoming a reality. It’s for this reason that he believes AI regulation at this stage is “premature,” since we won’t know what we’re up against until it’s fully realized.

He states that an AGI can only really happen when we’ve learned to integrate something that all humans possess into machines: common sense, which he also calls the foundation of reasoning.

Here’s what the future looks like in Yann’s perspective: in about a decade or so, smartphones will be obsolete, and they’ll be replaced with AR glasses equipped with virtual assistants. He doesn’t believe that LLMs like ChatGPT can scale up to AGI and that they’re just a “[waste] of time.”

What is Yann LeCun’s Legacy?

Yann LeCun will go down in history as one of the pioneers in artificial intelligence. His name will forever be tied to computer vision with his development of CNNs. Not only that, but he has also mentored some of the best minds in machine learning today like Wojciech Zaremba, Corinna Cortes, and Alexandre Lebrun.

The Bottom Line

Yann Lecun is a man of many berets. A computer scientist. An engineer. An educator. But the one that fits him best is this: a gamechanger.

His journey started in a small theater in the suburbs of France and placed him as the Chief Scientist and VP of one of the largest companies in the entire world. Who knows what would’ve happened if he watched Rosemary's Baby instead of 2001: A Space Odyssey? Would he still have been one of the, if not the foremost, experts in deep learning? 

As we’re nearing singularity, people like LeCun, Hinton, and Bengio — the minds that enabled this to happen — are invaluable to the companies creating AGI. But what they offer extends beyond knowledge. They offer wisdom and insights into what should and shouldn’t be pursued.

The bottom line is this: Yann LeCun is more than just a “Godfather of Deep Learning.” He’s one of the select group of people responsible for changing the world.

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Written by John Angelo Yap
Hi, I'm Angelo. I'm currently an undergraduate student studying Software Engineering. Now, you might be wondering, what is a computer science student doing writing for Gold Penguin? I took up studying computer science because it was practical and because I was good at it. But, if I had the chance, I'd be writing for a career. Building worlds and adjectivizing nouns for no other reason other than they sound good. And that's why I'm here.
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