Our universe emerged when spacetime’s building blocks “crystallized” into being, according to a controversial theory.
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Adam Becker on More Everything Forever and Tech’s Future Myths
Last summer I sat down with Adam Becker and asked him to name the most confident story in tech.
He picked the one nobody in Silicon Valley is allowed to question: that godlike #AI, digital immortality, and space empires are simply where history is headed. Not a hope. A destination.
Becker has a PhD in astrophysics and fifteen years as a science journalist. In his book More Everything Forever, he takes that story apart and shows where it actually came from: misread science fiction, fringe mailing lists, and a very old colonial logic about who deserves the future. From there it walked straight into university labs, congressional hearings, and your feed.
His line from our conversation stayed with me: Silicon Valley has confused science fiction with science, and science with branding.
The stakes are not academic. While we debate the welfare of trillions of hypothetical posthuman minds, the actual world runs on war, climate collapse, widening inequality, and a shared reality coming apart. Becker calls the grand visions a distraction. I asked him whether a civilization can function without a myth of the future at all.
I do not agree with everything Adam argues, and that is exactly why this one is worth your time. Watch it and tell me who you think is right about the #Singularity.
Proprietary AI Model Proves Data Moat Beats Compute Moat
Thomson Reuters spent $40 million over two years building Thomson, its first proprietary AI model, but the final training run cost just $450,000 because it started from an open-weight base rather than building from scratch. Thomson underperforms general-purpose frontier models on open-web tasks but beats them on tasks using Thomson Reuters’ own proprietary content. The lesson for any company sitting on decades of specialized data: the moat was never the model.
A proprietary AI model just gave companies outside the frontier AI labs a real, numbers-backed reason to stop assuming they need billions to compete. Thomson Reuters launched Thomson, its first proprietary large language model, on August 24, 2026, after investing $40 million in talent and compute over two years, according to SiliconANGLE’s coverage of the launch. The company said economies from starting with an open-weight base model reduced the cost of the final training run to roughly $450,000, a fraction of what frontier labs spend building models from the ground up.
Thomson’s own benchmark results are the most useful part of this story, because they don’t oversell the model. On general web-only test sets, Thomson performed respectably but wasn’t the leader, according to LawNext’s reporting on the launch. On tests built around Thomson Reuters’ own Westlaw, Practical Law, and Checkpoint content, it outscored both comparison frontier models. A proprietary AI model trained on content nobody else can license doesn’t need to win everywhere. It only needs to win on the specific tasks that content makes possible.
Milky Way’s own gravity can mimic dark matter clues, stellar stream simulations suggest
Most of the stars in our Milky Way galaxy sit neatly on a flat plane. But the space around our galaxy is much more chaotic. Rogue bands of stars called “stellar streams” orbit the Milky Way much like planets in our solar system orbit the sun.
Astronomers have long been fascinated by the possibility that stellar streams could indirectly reveal the presence of dark matter, that mysterious theorized substance that doesn’t interact with light or normal matter—except via gravity. However, a new University of Washington study casts doubt on a leading theory linking dark matter and stellar streams and raises new questions about both galactic phenomena.
“Dark matter makes up most of the mass in the universe and forms the scaffolding that galaxies grow on, but we still don’t know what it is,” said co-author Nora Shipp, a UW assistant professor of astronomy. “The Milky Way is one of the best laboratories we have for figuring that out, and stellar streams are one of the sharpest tools inside it.”
Light particles reveal critical scaling in a two-dimensional photon gas
A team of researchers from the University of Bonn, Heidelberg University and the National Autonomous University of Mexico has studied the critical behavior of light particles (photons) close to a phase transition. This critical scaling behavior, which sees thermodynamic quantities grow extremely large or diverge shortly prior to Bose-Einstein condensation, had never before been seen in photon gases until the researchers successfully secured precisely this proof.
In the research published in the journal Science Advances, the team measured the spatial correlations of a nearly non-interacting 2D photon gas trapped in a mirror box at the moment of condensation, determining the critical exponent—a quantity describing the rapid increase in the correlation length as the temperature changes near the phase transition.
The physics of kiiking, Estonia’s extreme sport of swinging
When an athlete swings upside down atop a 7-meter (23-foot) pendulum, it may seem like a feat of strength, courage or technique. A new study suggests it is something more fundamental: a striking demonstration of how intelligence emerges from the interaction of brain, body and environment.
In a paper published in the Journal of Nonlinear Science, Harvard researchers use mathematics, physics and control theory to analyze kiiking, an extreme sport invented in Estonia in which athletes pump a giant swing until they complete a full rotation.
At one level, the problem appears straightforward. The athlete repeatedly stands and squats to inject energy into the swing. Yet this simple action inspires a question that reaches far beyond sport, touching neuroscience, robotics, biology and human performance: How does an organism learn to exploit the dynamics of its environment to achieve a goal?
Geomimicry offers a new framework for engineering sustainable materials
When engineers look to nature for inspiration, they often turn to living systems. The flight of birds has influenced aircraft design, gecko feet inspired new adhesives and lotus leaves led to the development of self-cleaning surfaces.
Researchers at the University of Pennsylvania now argue that engineers should look somewhere else in nature as well: the ground beneath their feet.
In a perspective paper published in Physical Review E, the team introduces geomimicry, a framework that asks how soils, sediments and other Earth-mediated materials have been shaped over geologic time and how those processes can inspire the next generation of sustainable materials.