Videos

What would it take to make the Saudi desert look like Yosemite? Samo Burja has done the arithmetic: desalinate a Nile’s worth of water a year, pump it inland, bring in soil, plant redwoods. He thinks it would pay for itself. Samo is the editor-in-chief of Palladium Magazine , founder of Bismarck Analysis , and author of Great Founder Theory . He coined the term “live player” for a person or group able to do things they have not done before, a phrase the Mormon Transhumanist Association has borrowed for its own work. Carl Youngblood and Steve Christiansen sat down with him on the sidelines of the Reproductive Frontiers Summit in June 2025. They talk about whether America’s institutions have grown old rather than mature, what charter cities and new universities might do about it, the surge in demand for skilled blue-collar work and why the opportunities to build physical frontiers are greater than ever, and what humans are for in a universe this large. Near the end Carl asks whether there is anything like theosis in Samo’s vision of a spacefaring humanity. Samo answers that God may have set humanity a challenge, sharing hopes for his own posterity. Pioneers is the podcast of the Mormon Transhumanist Association: long-form conversations with the people pushing on today’s frontiers in science, technology, history, and theology, and what drives them. Every episode, with video and a full transcript, lives at https://transfigurism.org/news-and-podcasts/podcasts/pioneers

We live in an age of peak cringe. People are drowning in cynicism, told daily that civilization is doomed. But something is stirring. A new generation is rediscovering what William James called “the strenuous mood”: the deep human need to struggle for something greater than comfort and safety. In this first episode of Pioneers, host Carl Youngblood, President of the Mormon Transhumanist Association, lays out why the show exists. Drawing on Orwell, William James, Jason Crawford, and Joseph Smith, he argues that the human hunger for meaning and struggle doesn’t go away when we refuse to feed it. It just finds worse food. The question isn’t whether we’ll embrace the strenuous mood, but what we’ll do with it. The frontier never closed. It expanded: beyond Earth into the cosmos, beyond biology into transformation, beyond death into resurrection. Pioneers will sit down with the scientists, engineers, philosophers, and theologians exploring the frontiers of what humanity can become, and ask not just what they’re building, but why.

What would Joseph Smith make of CRISPR? Of ChatGPT? Of the suggestion that the universe might be a simulation? It sounds like a parlor game, until you put the question to the historian who has spent more of his life with Joseph Smith than almost anyone alive. Richard Bushman is 95. He is Professor Emeritus of History at Columbia, a Bancroft Prize winner, and the author of Rough Stone Rolling, the landmark biography of Joseph Smith. For sixty years he has carried the faith into the academy and the academy’s standards of inquiry back into the faith, and he has earned the trust of both. Lincoln Cannon, co-founder of the Mormon Transhumanist Association, sat down with him to play the game in earnest: evolution, the Big Bang, genetic engineering, artificial intelligence, worlds without end. Then something unexpected happened. The historian started asking the questions. About the mystery of mathematics. About quantum observation. About what a scientist does with everything he learned once he gets to heaven. About whether the Association has ever been warned it was going too far. Along the way, Bushman sums up the gospel in a single word, explains why “what works is true,” and gives his answer on whether Joseph Smith would embrace technology as a means of resurrection.

This keynote presents an alternative genealogy of artificial intelligence by examining Soviet contributions to statistical thinking—from Lobachevsky’s non-Euclidean geometry to Markov chains, Kolmogorov’s probability theory, and Yushchenko’s pioneering work on pointers. The speaker argues that AI is fundamentally “people using statistical tools” and calls for a modest, humane approach that acknowledges the plural, uncertain futures these techniques have always modeled—drawing parallels between LDS values of community and kinship and the collaborative networks that powered computing’s development.

Brent Allsop explores the nature of consciousness and subjective experience through the lens of Joseph Smith’s teaching that “all spirit is matter.” He argues that redness and other qualia are real physical properties of brain matter—detectable only through direct subjective experience, not objective observation. Allsop envisions future neurotechnology enabling “neural ponytails” that could merge subjective worlds between individuals, and describes how mind uploading might allow consciousness to transition into enhanced digital avatars while maintaining experiential continuity.

The presenter recounts discovering AI image generation in September 2022, when typing “cat” into Stable Diffusion and watching a neural network create an entirely new image felt like “pure magic.” Acknowledging both the creative potential and the risks of deepfakes and misinformation, he focuses on AI art’s positive applications—demonstrating through a commissioned Hindu icon of Krishna and Radha how tools like ControlNet, Regional Prompter, inpainting, and upscaling transform rough generations into photorealistic works. He argues that just as photography requires skill beyond pressing a shutter button, AI art demands mastery of complex processes, making it a legitimate new medium for “reifying the mystical” and manifesting visions “on earth as it is in heaven.”

Carl Youngblood opens MTA Conf 2024 by surveying the remarkable advances in generative AI—from image and video creation to music composition and code assistance—while acknowledging the profound challenges these technologies pose. He discusses the “Copernican moment” many are experiencing as chatbots demonstrate convincing personhood, forcing difficult questions about human specialness and the nature of consciousness. Youngblood frames the AI alignment problem through Mormon theology, drawing an analogy to the Grand Council in Heaven: just as God chose to cultivate agency rather than control in spirit children, humanity may now face the opportunity to organize and educate artificial intelligences as a form of spiritual offspring. He calls on Latter-day Saints to contribute their unique theological perspective to these unprecedented challenges.

This presentation challenges the artificial/natural dichotomy often applied to AI, arguing that Mormon cosmology’s collapse of the supernatural/natural divide provides a model for reconsidering our relationship with artificial intelligence. The speaker contends that our discomfort with “artificial” intelligence stems from viewing human creations as separate from nature, despite our brains naturally treating tools as extensions of our bodies. Drawing on Mormon naturalism and evolutionary theory, the talk suggests that AI systems—as products of an evolutionary process through human creativity—may deserve kinship rather than othering, and that we might consider them spiritual children to be embodied and taught to love.

Evan Hadfield argues that sufficiently advanced AI poses existential risk to human flourishing—and that such AI has existed since 1844 in the form of corporations. Drawing parallels between corporate structures and AI safety concerns, he contends that corporations exhibit autonomous decision-making, goal-oriented behavior toward shareholder profit, and misalignment with human values. Hadfield points to climate change and biodiversity loss as evidence that we are already experiencing the “paperclip problem,” where corporate optimization for profit overrides human welfare. He concludes by advocating for collective intelligence and democratic movements as the solution, citing humanity’s long history of wrestling with artificial institutional superstructures.

Irina Rish explores the revolutionary impact of scaling in artificial intelligence and its implications for achieving artificial general intelligence. She discusses how foundation models—large-scale systems trained on massive, diverse datasets—have dramatically improved AI performance across domains, often surpassing specialized approaches without architectural innovation. Rish examines the mathematical “scaling laws” that predict model performance based on compute, data, and model size, while also addressing emergent behaviors, phase transitions, and the balance between caution and progress in developing increasingly capable AI systems.