Influential Tech Leaders

In 1972, a woman in Cambridge, England, figured out how to make computers understand what we’re actually looking for. Her name was Karen Spärck Jones. https://lnkd.in/g8tdZ-cQ At the time, searching through documents meant reading titles, checking indexes, or hoping you remembered the right keywords. It was slow, manual work. Karen was working with punch cards and early computers, and she realized something simple but powerful: common words like “the,” “and,” or “of” show up everywhere and don’t help you find anything specific. A rare word, on the other hand, is much more useful. She created a mathematical formula that weighed how important a word was in a particular document against how common it was across the entire collection. She called it term frequency-inverse document frequency — TF-IDF. It let a machine figure out relevance without actually understanding the meaning of the words. It was a quiet paper in a niche academic journal. Most people in computing at the time thought language processing was a librarian’s problem, not serious science. Mainframe computers were expensive and mostly used for military calculations, banking, and census data. Karen had to wait for the engineers and physicists to finish their work before she could run her experiments late at night on the university’s big Titan computer. She fed in stacks of punch cards, dealt with jammed readers, and checked everything by hand. She didn’t have a flashy lab or big funding. She just kept working. Decades later, when the internet exploded with billions of pages, search engines hit a wall. Early directories relied on humans manually categorizing everything. It couldn’t scale. Engineers digging through old research found Karen’s 1972 paper. They took her math, scaled it up, and built it into the core of how modern search works. Google, Bing, academic databases, even the search function in your email — they all use some version of what she created. You type a question. The system filters millions of documents in a fraction of a second and gives you what you need. That filtering logic traces straight back to her. Karen stayed at Cambridge. She taught, mentored other women in computing, and kept pushing the field forward until she retired in 2002. She died in 2007. She never got rich. She never became a household name. The giant tech companies that built empires on search rarely mentioned her. But every time you type something into a search bar and actually get a useful answer, you’re using Karen Spärck Jones’s thinking. She didn’t build the internet. She just taught machines how to listen better.

Alan Turing is called the father of computing. But the first computer programmer? That was a woman. Ada Lovelace was born in 1815. She was the daughter of the infamous poet Lord Byron and the wealthy, mathematically gifted Annabella Milbanke. When she turned 17, Ada was introduced to Charles Babbage. A brilliant mathematician and inventor who showed her a prototype of his “difference engine,” a mechanical calculator. What began as a mentorship soon became an intellectual partnership. Then came the analytical engine. Unlike the difference engine, which could only perform fixed equations, Babbage’s new machine had memory (“the store”), a processor (“the mill”), and used punch cards to process data. But Babbage, for all his genius, saw the machine only as a number cruncher. Ada saw more. She began advanced studies under Augustus De Morgan, one of the leading mathematical minds of the era. In 1842, Italian mathematician Luigi Menabrea published a paper summarizing Babbage’s lectures in Turin on the analytical engine. Ada translated it into English, and added her own notes. Her notes were 3x longer than the paper itself. She added 7 footnotes, labeled A through G. In Note A, she became the first to distinguish between numbers and symbols, realizing a machine could process not just math but music, letters, and logic. In Note G, she included the first published computer program: an algorithm to calculate Bernoulli numbers using Babbage’s engine. In that same note, Ada wrote what is now called “Lady Lovelace’s Objection”. An early critique of artificial intelligence. “The analytical engine has no pretensions whatever to originate anything. It can follow analysis, but it has no power of anticipating any relations or truths.” This led to what is now known as the Lovelace Test, proposed in 2001: a computer can only be said to have intelligence when it can create something entirely original, without human input. To this day, no AI has passed the Lovelace Test. And then, just as she was getting started, she got sick. In 1851, she was diagnosed with cancer. She died a year later at age 36. Her work was largely forgotten. Until 1953. That year, Bertram Bowden republished her notes in “Faster Than Thought: A Symposium on Digital Computing Machines”. And Ada was reintroduced to the world as the first computer programmer. In the 1970s, the U.S. Department of Defense named a new programming language after her: ADA. Ada believed programming would shape mathematics itself. She believed coding would teach us new ways to think. And she was right. But… why didn’t she get credit? Because she was a woman. She couldn’t publish under her name. She couldn’t enter libraries. She couldn’t attend university. In short: she was born 100 years too early. 💡 Follow Justine Juillard to read 365 stories of women innovators in 2025.

Most people don’t know her name. And yet, almost every device you touch... your phone, your laptop, your Wi-Fi router, depends on a few hundred lines of code she wrote in 1985. Back then, computer networks had a fatal flaw. Backup paths created loops. Data would enter those loops… and spin forever. Packets multiplied, systems froze, entire networks crashed. It was like sending cars onto a roundabout with no exits. Eventually, everything jammed. The internet of the 1980s could not grow unless someone solved this. Radia Perlman did. Working at DEC in the mid-1980s, she created the Spanning Tree Protocol. This brilliant idea allowed switches to talk, detect loops, disable the dangerous ones, and instantly re-route traffic when a primary path failed. She taught networks how to heal themselves. Those few hundred lines of code became the backbone of the modern internet — running silently in offices, data centers, and across continents. As you read this in 2025, her algorithm is quietly protecting global networks from failure. But Radia Perlman walked into rooms where she was mistaken for an assistant. Her work was overlooked, attributed to others, forgotten in footnotes. When people later called her the “Mother of the Internet,” it was a compliment and an irony. Because great engineering is often invisible. And so was she. But she kept creating anyway. Over the 1990s and 2000s, she earned 100+ patents. She wrote textbooks that shaped generations. She developed new security methods. She was inducted into the Internet Hall of Fame in 2014. All built with the same philosophy: Make systems that survive. Make systems that keep going. Make systems that quietly hold the world together. Today, in her seventies, Radia Perlman is still working. And the protocol she wrote almost 40 years ago still runs beneath our digital lives. The internet was built to withstand failure. So was she. And maybe that’s the lesson that sometimes the people who change the world aren’t loud, or famous, or celebrated. Sometimes they’re just… invisible. But their work holds everything up. #INTERNET #inspiration #motivation #wisdom #computer #computerscience

• Born in Bratislava, moved to Canada young • BSc in Computer Science from University of Toronto • MSc from University of British Columbia • PhD at Stanford under deep learning pioneer Fei-Fei Li, focusing on connecting vision + language systems • Created legendary Stanford CS231n course that taught an entire generation CNNs and computer vision • Co-founded OpenAI and worked on early deep learning research • Recruited by Elon Musk to lead AI at Tesla Autopilot • Built large-scale production computer vision systems for millions of cars using end-to-end neural networks • Helped push the shift from hand-engineered rules -> neural network driven perception stacks • Coined the term “Software 2.0” -> replacing explicit code with learned neural weights • Coined “Vibe Coding” -> where humans describe intent and AI writes software • Famous for saying: “The hottest new programming language is English” • Built some of the most influential AI education content: Zero-to-Hero, nanoGPT, neural networks from scratch • Founded Eureka Labs to rethink AI education • Elon Musk once called him “arguably the 2nd guy in the world in computer vision” Researchers publish papers, Engineers ship products, Very few people redefine entire fields. Andrej Karpathy did all three

What if you could save millions of lives by thinking differently about machines? Alan Turing did exactly that. In 1936, Alan Turing was a 24 year old mathematician at Cambridge asking a question that seemed purely theoretical. Could there be a universal computing machine capable of solving any problem that could be described as a series of logical steps? His answer, published in a paper titled On Computable Numbers, laid the mathematical foundations for every computer that would ever be built. Most people saw it as abstract mathematics with no practical application. Turing saw the future of computation. Then World War II changed everything. In 1939, Turing joined the Government Code and Cypher School at Bletchley Park. His mission was breaking Enigma, the encryption machine Nazi Germany used for military communications. The challenge was staggering.  Enigma had 159 million million million possible settings. Checking them manually would take longer than the war would last. Turing  built a machine that could think through the problem logically, eliminating impossible settings until the correct one emerged. The Bombe machine, as it was called, could break Enigma codes in hours instead of millennia. By the end of the war, Bletchley Park was decrypting thousands of messages daily. Historians estimate that breaking Enigma shortened the war by at least two years and saved millions of lives. But Turing was not satisfied with wartime applications.  After the war, he continued developing the theory of machine intelligence. In 1950, he published Computing Machinery and Intelligence, proposing what became known as the Turing Test. Can machines think? If you cannot tell whether you are conversing with a human or a machine, does the distinction matter? This paper became the foundation of artificial intelligence research. Turing never saw the impact of his work. In 1954, at age 41, he died from cyanide poisoning. The inquest ruled it suicide, though some historians question that conclusion. Today, the Alan Turing Institute serves as the UK national institute for data science and artificial intelligence, carrying forward his legacy. The tools you use every day, from smartphones to AI assistants, exist because one mathematician asked whether machines could think and then proved they could. When you encounter someone whose thinking seems too different, too unconventional, too far ahead of current understanding, ask yourself whether you are dismissing the next Alan Turing. What unconventional thinking in your organisation gets dismissed because it does not fit established patterns? #AlanTuring #AI #Innovation #Legacy #BritishHistory

The forgotten first programmers: six women who coded history — and were erased from it. In 1945, six women pulled off a computing miracle: programming the world’s first general-purpose computer, ENIAC — with no manuals, no training, and no precedent. Betty Holberton, Jean Bartik, Kay McNulty, Ruth Teitelbaum, Marlyn Meltzer, and Frances Spence were hired during WWII as “human computers” to calculate missile trajectories. When ENIAC was built, these women were tasked with programming it — but weren’t even allowed in the lab at first. How do you program a machine no one’s ever seen before? With paper, pencil, pure logic, and sheer determination. They created algorithms and flowcharts from scratch, then physically wired the giant machine to perform complex calculations. When ENIAC debuted on February 14, 1946, it made headlines — but none of the programmers were invited or credited. The engineers who built the hardware took all the glory. Why? Because programming was seen as “women’s secretarial work” rather than highly skilled math and logic. Soon, men took over the field and rewrote computing history. These women didn’t stop there. They pioneered the first software applications, memory systems, and reusable code. Yet their story was buried for decades — until Kathy Kleiman rediscovered them in the 1980s and fought to give them their rightful place in history. Their legacy reminds us: women have always been trailblazers in tech. The future of computer science must honor that truth — so every girl dreaming of coding knows she’s part of a proud, powerful legacy. Watch Kathy Kleiman’s talk on how she found the ENIAC Six and restored their place in history. Let’s make sure these stories aren’t just footnotes anymore.

Programming was first introduced to me in my undergrad at an all-women's college. I loved solving logical problems, but I quickly realized I wasn't going to be the best coder in the room. That distinction belonged to my friend Shaama. She lived in the computer lab, coding with such passion that even the stern "Mother Superior" called her parents to praise her exceptional skills - a rare occurrence usually reserved for troublemakers!. Yet at home, Shama faced resistance. "Why computer science?" her family questioned her decision. All she could say was, "Why not?" What she lacked were visible role models—women who had blazed the trail before her. Throughout history, brilliant women worked in the shadows, tackling work men often avoided. 𝗔𝗱𝗮 𝗟𝗼𝘃𝗲𝗹𝗮𝗰𝗲 𝘄𝗿𝗼𝘁𝗲 𝘁𝗵𝗲 𝗳𝗶𝗿𝘀𝘁 𝗰𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗮𝗹𝗴𝗼𝗿𝗶𝘁𝗵𝗺 in the 1840s, envisioning computing capabilities most couldn't grasp. During WWII, 𝗝𝗲𝗮𝗻 𝗝𝗲𝗻𝗻𝗶𝗻𝗴𝘀 𝗮𝗻𝗱 𝗙𝗿𝗮𝗻𝗰𝗲𝘀 𝗕𝗶𝗹𝗮𝘀 𝗽𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗲𝗱 𝗰𝗼𝗺𝗽𝗹𝗲𝘅 𝗺𝗶𝗹𝗶𝘁𝗮𝗿𝘆 𝗰𝗮𝗹𝗰𝘂𝗹𝗮𝘁𝗶𝗼𝗻𝘀—work dismissed as less important than hardware, their contributions unrecognized for decades. 𝗚𝗿𝗮𝗰𝗲 𝗛𝗼𝗽𝗽𝗲𝗿, 𝘁𝗵𝗲 "𝗤𝘂𝗲𝗲𝗻 𝗼𝗳 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲," 𝗿𝗲𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝗶𝘇𝗲𝗱 𝗽𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 by creating the first compiler that made programming languages universally accessible. 𝗥𝗮𝗱𝗶𝗮 𝗣𝗲𝗿𝗹𝗺𝗮𝗻 𝗲𝗮𝗿𝗻𝗲𝗱 𝘁𝗵𝗲 𝗺𝗼𝗻𝗶𝗰𝗸𝗲𝗿 "𝗠𝗼𝘁𝗵𝗲𝗿 𝗼𝗳 𝘁𝗵𝗲 𝗜𝗻𝘁𝗲𝗿𝗻𝗲𝘁"—though she humbly rejects it, noting the internet wasn't invented by any single person. Her pioneering network algorithms nonetheless became crucial building blocks for how we connect online today. 𝗛𝗲𝗱𝘆 𝗟𝗮𝗺𝗮𝗿𝗿 𝘀𝗵𝗮𝘁𝘁𝗲𝗿𝗲𝗱 𝗲𝘅𝗽𝗲𝗰𝘁𝗮𝘁𝗶𝗼𝗻𝘀 𝗰𝗼𝗺𝗽𝗹𝗲𝘁𝗲𝗹𝘆. Known as a glamorous film star, she secretly invented frequency-hopping technology to prevent Nazi jamming of torpedo signals—foundational to WiFi, Bluetooth, and GPS we use daily. The military initially dismissed her work before classifying it as too valuable to implement. 𝗘𝗺𝗺𝘆 𝗡𝗼𝗲𝘁𝗵𝗲𝗿 upended mathematics despite being barred from faculty positions because of her gender. Einstein called her "the most significant creative mathematical genius" of her time, yet she lectured under male colleagues' names. These women didn't merely participate in technological revolution—they drove it forward against systems designed to exclude them. Today, women like 𝗔𝗻𝗶𝘁𝗮 𝗕𝗼𝗿𝗴 and "Godmother of AI" 𝗙𝗲𝗶-𝗙𝗲𝗶 𝗟𝗶 continue shaping technology—fighting algorithmic bias and championing human-centric technology. This Women's History Month, let us reclaim this narrative. When we understand that women have always been at computing's cutting edge, we see clearly that technology advances fastest and humanity moves forward when diverse minds contribute. Tag women in tech that inspire you! #womenshistorymonth #womenintech #techpioneers #hiddenfigures

John von Neumann died in early 1957, but much of his work was absolutely fundamental to the evolution of computing and AI. Today some of it is more relevant than ever. The von Neumann computer architecture consists of a central processing unit (CPU), memory, and input/output mechanisms, still the structure used today. He also pointed to the potential for parallel computing architectures, which have underpinned AI compute, especially since 2010. His book 'The Computer and the Brain' discussed the potential of brain-inspired computing, which led to the development of neural networks. He co-authored the seminal text on game theory, 'The Theory of Games and Economic Behavior', which underpins many branches of AI, including the algorithms underlying AlphaGo and related models. His work on stochastic methods, including Monte Carlo analysis, are fundamental to many AI techniques including Bayesian inference and Markov Chains. His work on self-reproducing automata shaped cellular automata, generative algorithms, and Generative Adversarial Networks. Today his theoretical constructs on self-reproduction are exceptionally relevant as agentic AI rapidly rises. I was aware of bits and pieces of this, but this was all brought into focus by reading the slightly fictionalized story of von Neumann and his contemporaries, 'The Maniac' by Benjamin Lebatut, an absolutely fascinating yarn. Highly recommended.

Kristen Nygaard (1930–2002) and Ole-Johan Dahl (1931–2002) were Norwegian computer scientists who together revolutionized the field of programming with their creation of the Simula programming language, which is widely recognized as the first object-oriented programming (OOP) language. Their work laid the foundation for the development of modern programming paradigms, influencing the design of languages like Smalltalk, C++, Java, and many others. --- Both Nygaard and Dahl had academic backgrounds in mathematics and physics, which naturally led them to the emerging field of computer science. They worked together at the Norwegian Computing Center (Norsk Regnesentral, NR) in Oslo, where their collaboration began in the early 1960s. During their time at NR, the two developed Simula, which was initially designed to simulate complex systems such as traffic flow and other real-world phenomena. Simula was groundbreaking for several reasons, most notably for introducing object-oriented principles that are now fundamental to modern programming. It was the first language to feature classes and objects, enabling developers to model real-world entities in a more intuitive and reusable way. This laid the groundwork for the later development of OOP, which emphasizes abstraction, modularity, and the reuse of code. While Simula was initially created for simulation purposes, its design was revolutionary and would later influence the structure of many other programming languages. Although Simula was not immediately widely adopted, its impact grew over time, particularly as the object-oriented paradigm gained popularity in the 1980s and 1990s. The contributions of Nygaard and Dahl became increasingly recognized, culminating in their receiving the Turing Award in 2001. In addition to their work on Simula, Nygaard and Dahl made important contributions to the broader field of computer science, particularly in the areas of simulation, system design, and software engineering. Both were involved in applying computer science to real-world problems, working on projects in fields such as transportation, logistics, and complex system simulations. Nygaard was particularly passionate about the conceptual frameworks that underpin computational thinking, while Dahl focused on system development and software engineering. They both remained influential figures in academia and the computer science community, mentoring the next generation of computer scientists and software engineers. --- Kristen Nygaard and Ole-Johan Dahl's work on Simula revolutionized computer science by introducing object-oriented programming principles. Their contributions laid the foundation for many modern programming languages and methodologies, shaping how we approach software development with a focus on modularity, abstraction, and code reusability. Their legacy continues to influence the field today.

Dennis Ritchie: The Unsung Hero of Modern Computing. -------------------------------------------------------------- Dennis Ritchie, a towering figure in the history of computing, invented the C programming language and co-developed the Unix operating system. His contributions laid the foundation for much of modern software development. Tragically, Ritchie passed away on October 12, 2011, just days after the death of Steve Jobs, which overshadowed his passing in the public eye. The Legacy of Dennis Ritchie Dennis Ritchie’s work has had a profound and lasting impact on the field of computer science. In the early 1970s, Ritchie created the C programming language at Bell Labs. C introduced powerful features that allowed for efficient low-level memory manipulation while maintaining high-level programming constructs. This balance made C incredibly versatile and influential, leading to its widespread adoption in system software, applications, and even the development of other programming languages like C++, C#, and Java. Ritchie, along with Ken Thompson, also co-developed the Unix operating system. Unix's design philosophy of simplicity, portability, and modularity has profoundly influenced many modern operating systems, including Linux and the various BSD variants. The Unix operating system and the C language are often credited with having a symbiotic relationship; C was used to write Unix, and Unix's development spurred the growth and refinement of C. A Quiet Giant in the Shadows Despite his monumental contributions, Dennis Ritchie was not a household name. His death went largely unnoticed by the mainstream media, overshadowed by the outpouring of grief and media coverage surrounding Steve Jobs, who passed away on October 5, 2011. Jobs, the co-founder of Apple Inc., was celebrated globally as a visionary and marketing genius who revolutionized consumer technology with products like the iPhone, iPad, and MacBook. While Jobs’ impact on consumer technology and culture is undeniable, Ritchie's contributions were foundational to the very fabric of the digital world we live in today. The C language and Unix operating system are integral to virtually every piece of software and system architecture that underpins our digital infrastructure. Remembering Dennis Ritchie It's important to recognize and celebrate the achievements of Dennis Ritchie, who, through his quiet genius, gave the world tools that have enabled generations of developers to build the technology we rely on daily. His work has had a ripple effect, influencing countless technologies and innovations. In honoring Dennis Ritchie, we remember a man whose brilliance and dedication laid the groundwork for the digital age. His legacy lives on in the millions of lines of code written in C, the operating systems that drive our servers, and the many programmers who continue to learn from and build upon his pioneering work.