Revealing the Algorithm Genie: The Astounding Promise of AI
AUSTIN – November 8, 2024 – Machine learning (ML) and artificial intelligence (AI) technologists from around the globe packed a standing-room only ballroom this morning, transfixed by Jepson Taylor’s keynote address kicking off Day 2 of in-person sessions at the ML Ops World – Gen AI Summit 2024.
Taylor, Former Chief AI Strategist at DataRobot & Dataiku and founder of VEOX Inc. – took center stage and shared anecdotes about deeply personal parts of his life journey while weaving a mind-bending narrative about the power and potential of AI.
Delivering a talk entitled, “Unleashing the Algorithm Genie: AI as the Ultimate Inventor” – Taylor engaged the audience with a visual demonstration of how AI can exponentially augment each practitioner’s ability to imagine and invent – and specifically, to generate advanced, high-quality algorithms. Intertwined with the AI and the math, Taylor shared his intricately true-to-life AI portraits and delved into powerful anecdotes from his journey – including referencing a period of time when he chose to be homeless in the snowy hills of Utah as a college student – continuously challenging himself to incrementally more difficult living conditions.
Taylor is a popular speaker in the AI space, having been invited to give AI talks to companies like Space X, Red Bull, Goldman Sachs, Amazon, and various branches of the U.S. government. His applied career has covered semiconductor, quant finance, HR analytics, deep-learning startup, and AI platform companies. He co-founded and sold his deep-learning company Zeff.ai to DataRobot in 2020 and later joined Dataiku as Chief AI Strategist. He is currently launching a new AI company focused on the next generation of AI called VEOX Inc.
His keynote landed powerfully and was filled with personal insights, humor, and deep reflections on the pace and nature of change in AI and innovation.
He opened by describing his passion for invention and innovation, noting the rapid acceleration of advancements in AI. He describes his "chaotic" presentation style, emphasizing his intention to blend storytelling, science, and personal anecdotes to make key concepts memorable. He divided his talk into four main themes: decisions, intelligence, innovation, and adaptation.
Decisions: Do I have the muscle memory to execute?
Taylor began with a discussion of decision-making, exploring how the human brain handles choices and adapts to challenges. Reflecting on his experiences snowboarding down a steep mountain, he used the anecdote as a metaphor for navigating high-stakes decisions and “facing down fear.” He illustrated this through the brain’s interaction between the amygdala, which "thinks we’re going to die," and the neocortex, which, while aware of mortality, doesn't believe death is imminent. He highlighted the role of muscle memory in decision-making, explaining that complex skills, whether driving or surgery, cannot be learned by simply watching — they require practice and experience.
He emphasized that life and career paths are often “a random walk,” with decisions sometimes driven by unpredictable opportunities rather than clear-cut plans. He shared a humorous anecdote about his early programming journey, including how he failed as a PhD student because his motivation at the time was video games – and how he lived in a tent in the snow during college, garnering the nickname, “Homeless Ben.” His aim at the time was simple: to not pay rent. But he used the experience as a way to continually improve, daring himself to increasingly difficult living conditions.
Intelligence: The acquisition of knowledge to be used for future decisions
In his discussion on intelligence, Taylor offered a unique perspective on what it means to be “smart” and how intelligence develops over time. He defined intelligence as "the acquisition of knowledge to be used for future decisions," pointing out that intelligence isn’t merely about innate ability, but the compounding effect of shared human experiences. He contrasted the intelligence of different species, noting that while a butterfly may react to immediate threats, humans are uniquely capable of transferring knowledge across generations — allowing us to build on each other’s learning, as seen in complex achievements like space exploration. Taylor illustrated this with a striking thought experiment: “Are you smarter today than you were yesterday?” Time, he argued, does not guarantee growth in intelligence. Instead, he emphasized that advancing intelligence requires stepping out of one’s comfort zone, actively seeking new ideas, and “colliding” with other people to spark innovation. This collision of ideas and perspectives, he concluded, is essential for fostering the creativity needed to tackle future challenges and adapt to a rapidly changing world.
Innovation: Mining for Gold
Moving on to innovation, Taylor compared it to "mining for gold," with discoveries often emerging through a combination of luck and persistence. He reflected on his graduate research, where a computer algorithm delivered a breakthrough by finding a mathematical insight he hadn’t anticipated.
“Am I smart, or am I lucky?” he pondered, attributing the success to the machine’s relentless testing capacity. He pointed out the inherent limitations of human ideation, noting:
“Humans can't come up with a thousand ideas on the spot—at most, we have three or five. But AI can try millions of ideas and vet them instantly.”
Taylor shared examples of how generative AI has transformed creativity, even in fields traditionally seen as human domains like visual arts. He contrasted the high cost and time associated with human-produced visuals seven years ago with the near-instant, cost-effective results achievable with today’s generative AI.
"Everyone’s an artist; they just don’t know it yet,” he said, urging attendees to experiment with creative AI tools like Midjourney.
One of the most compelling parts of Taylor’s talk was his description of an imagined AI-generated competition for the best headshot. He explained how adaptation plays a vital role in such contests, with AI developing hyper-realistic images, down to details like micro hairs on a nose or reflections in an eye. AI’s capacity for “emergence,” a spontaneous formation of complex, life-like patterns, represents a revolutionary step in creative fields.
Adaptation: Mining for Gold with a Tool that “Boils the Ocean of Possibilities” For You
Taylor concluded by emphasizing adaptation as the ultimate key to success. He highlighted the need for AI systems to be adaptable to different contexts and requirements. For example, he described his development of an AI “hacker” that autonomously tests and breaks his company’s security protocols, then learns to avoid making the same mistakes in future runs. This self-learning mechanism, or “adaptive system,” has broad implications for fields like cybersecurity.
Taylor also addressed the transformative effect of AI in software development, asserting that there may soon be no “sacred” part of the engineering workflow immune to automation. He explained that within his company’s internal development, agents can handle entire projects, performing refinement, modularization, and even making their own agents to improve project efficiency. This represents a profound shift in how engineering is done.
“You don’t need an engineer to define the structure anymore; AI can boil the ocean of possibilities for you,” he said.
He discussed the role of inspiration in driving innovation. Humans can create algorithms inspired by natural phenomena, such as pheromone trails left by ants. However, AI now holds the potential to push beyond this human capability by generating truly novel concepts that defy typical human thought processes.
In his closing remarks, Taylor encouraged attendees to embrace AI tools and experiment with their capabilities.
“If you’re not spending at least an hour a day with tools like OpenAI and Anthropic,” he urged, “you’re missing out on a complete game changer.”
His excitement for the future of AI was palpable as he outlined a vision of a world where human creativity and intelligence are augmented by machines. He offered a glimpse of a future where knowledge is more accessible, learning more engaging, and innovation knowing no bounds.
AUSTIN – November 8, 2024 – Machine learning (ML) and artificial intelligence (AI) technologists from around the globe packed a standing-room only ballroom this morning, transfixed by Jepson Taylor’s keynote address kicking off Day 2 of in-person sessions at the ML Ops World – Gen AI Summit 2024.
Taylor, Former Chief AI Strategist at DataRobot & Dataiku and founder of VEOX Inc. – took center stage and shared anecdotes about deeply personal parts of his life journey while weaving a mind-bending narrative about the power and potential of AI.
Delivering a talk entitled, “Unleashing the Algorithm Genie: AI as the Ultimate Inventor” – Taylor engaged the audience with a visual demonstration of how AI can exponentially augment each practitioner’s ability to imagine and invent – and specifically, to generate advanced, high-quality algorithms. Intertwined with the AI and the math, Taylor shared his intricately true-to-life AI portraits and delved into powerful anecdotes from his journey – including referencing a period of time when he chose to be homeless in the snowy hills of Utah as a college student – continuously challenging himself to incrementally more difficult living conditions.
Taylor is a popular speaker in the AI space, having been invited to give AI talks to companies like Space X, Red Bull, Goldman Sachs, Amazon, and various branches of the U.S. government. His applied career has covered semiconductor, quant finance, HR analytics, deep-learning startup, and AI platform companies. He co-founded and sold his deep-learning company Zeff.ai to DataRobot in 2020 and later joined Dataiku as Chief AI Strategist. He is currently launching a new AI company focused on the next generation of AI called VEOX Inc.
His keynote landed powerfully and was filled with personal insights, humor, and deep reflections on the pace and nature of change in AI and innovation.
He opened by describing his passion for invention and innovation, noting the rapid acceleration of advancements in AI. He describes his "chaotic" presentation style, emphasizing his intention to blend storytelling, science, and personal anecdotes to make key concepts memorable. He divided his talk into four main themes: decisions, intelligence, innovation, and adaptation.
Decisions: Do I have the muscle memory to execute?
Taylor began with a discussion of decision-making, exploring how the human brain handles choices and adapts to challenges. Reflecting on his experiences snowboarding down a steep mountain, he used the anecdote as a metaphor for navigating high-stakes decisions and “facing down fear.” He illustrated this through the brain’s interaction between the amygdala, which "thinks we’re going to die," and the neocortex, which, while aware of mortality, doesn't believe death is imminent. He highlighted the role of muscle memory in decision-making, explaining that complex skills, whether driving or surgery, cannot be learned by simply watching — they require practice and experience.
He emphasized that life and career paths are often “a random walk,” with decisions sometimes driven by unpredictable opportunities rather than clear-cut plans. He shared a humorous anecdote about his early programming journey, including how he failed as a PhD student because his motivation at the time was video games – and how he lived in a tent in the snow during college, garnering the nickname, “Homeless Ben.” His aim at the time was simple: to not pay rent. But he used the experience as a way to continually improve, daring himself to increasingly difficult living conditions.
Intelligence: The acquisition of knowledge to be used for future decisions
In his discussion on intelligence, Taylor offered a unique perspective on what it means to be “smart” and how intelligence develops over time. He defined intelligence as "the acquisition of knowledge to be used for future decisions," pointing out that intelligence isn’t merely about innate ability, but the compounding effect of shared human experiences. He contrasted the intelligence of different species, noting that while a butterfly may react to immediate threats, humans are uniquely capable of transferring knowledge across generations — allowing us to build on each other’s learning, as seen in complex achievements like space exploration. Taylor illustrated this with a striking thought experiment: “Are you smarter today than you were yesterday?” Time, he argued, does not guarantee growth in intelligence. Instead, he emphasized that advancing intelligence requires stepping out of one’s comfort zone, actively seeking new ideas, and “colliding” with other people to spark innovation. This collision of ideas and perspectives, he concluded, is essential for fostering the creativity needed to tackle future challenges and adapt to a rapidly changing world.
Innovation: Mining for Gold
Moving on to innovation, Taylor compared it to "mining for gold," with discoveries often emerging through a combination of luck and persistence. He reflected on his graduate research, where a computer algorithm delivered a breakthrough by finding a mathematical insight he hadn’t anticipated.
“Am I smart, or am I lucky?” he pondered, attributing the success to the machine’s relentless testing capacity. He pointed out the inherent limitations of human ideation, noting:
“Humans can't come up with a thousand ideas on the spot—at most, we have three or five. But AI can try millions of ideas and vet them instantly.”
Taylor shared examples of how generative AI has transformed creativity, even in fields traditionally seen as human domains like visual arts. He contrasted the high cost and time associated with human-produced visuals seven years ago with the near-instant, cost-effective results achievable with today’s generative AI.
"Everyone’s an artist; they just don’t know it yet,” he said, urging attendees to experiment with creative AI tools like Midjourney.
One of the most compelling parts of Taylor’s talk was his description of an imagined AI-generated competition for the best headshot. He explained how adaptation plays a vital role in such contests, with AI developing hyper-realistic images, down to details like micro hairs on a nose or reflections in an eye. AI’s capacity for “emergence,” a spontaneous formation of complex, life-like patterns, represents a revolutionary step in creative fields.
Adaptation: Mining for Gold with a Tool that “Boils the Ocean of Possibilities” For You
Taylor concluded by emphasizing adaptation as the ultimate key to success. He highlighted the need for AI systems to be adaptable to different contexts and requirements. For example, he described his development of an AI “hacker” that autonomously tests and breaks his company’s security protocols, then learns to avoid making the same mistakes in future runs. This self-learning mechanism, or “adaptive system,” has broad implications for fields like cybersecurity.
Taylor also addressed the transformative effect of AI in software development, asserting that there may soon be no “sacred” part of the engineering workflow immune to automation. He explained that within his company’s internal development, agents can handle entire projects, performing refinement, modularization, and even making their own agents to improve project efficiency. This represents a profound shift in how engineering is done.
“You don’t need an engineer to define the structure anymore; AI can boil the ocean of possibilities for you,” he said.
He discussed the role of inspiration in driving innovation. Humans can create algorithms inspired by natural phenomena, such as pheromone trails left by ants. However, AI now holds the potential to push beyond this human capability by generating truly novel concepts that defy typical human thought processes.
In his closing remarks, Taylor encouraged attendees to embrace AI tools and experiment with their capabilities.
“If you’re not spending at least an hour a day with tools like OpenAI and Anthropic,” he urged, “you’re missing out on a complete game changer.”
His excitement for the future of AI was palpable as he outlined a vision of a world where human creativity and intelligence are augmented by machines. He offered a glimpse of a future where knowledge is more accessible, learning more engaging, and innovation knowing no bounds.
