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Category: economics – Page 2

Elon Musk: The Economy Will Be 10x the Size in 10 Years | #239

Recorded live at https://www.abundance360.com/

Peter H. Diamandis, MD, is the Founder of XPRIZE, Singularity University, ZeroG, and A360.

Elon Musk is the cofounder and CEO of Tesla, cofounder of SpaceX, and xAI.

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My companies:

Apply to Dave’s and my new fund: https://qr.diamandis.com/linkventures… to Blitzy to book a free demo and start building today: https://qr.diamandis.com/blitzy _ Read the Solve Everything Paper: https://solveeverything.org/ Get notified once we go live during Abundance360: https://www.abundance360.com/livestream Get access to metatrends 10+ years before anyone else: https://qr.diamandis.com/metatrends Connect with Peter: X: https://qr.diamandis.com/twitter Instagram: https://qr.diamandis.com/instagram Listen to MOONSHOTS: Apple: https://qr.diamandis.com/applepodcast Spotify: https://qr.diamandis.com/spotifypodcast – *Recorded live on March 11th, 2026 *The views expressed by me and all guests are personal opinions and do not constitute Financial, Medical, or Legal advice.

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New model measures economic risks solar storms pose to US power grid

In 1967, a solar storm nearly triggered World War III by jamming early-warning radar systems in the United States, causing U.S. leaders to think the Soviet Union was responsible. Though society averted catastrophe thanks to timely information from solar forecasters, the threat from space weather remains real.

Solar, or geomagnetic, storms form as the sun expels plasma and magnetic fields from its corona during coronal mass ejections. After traversing space and encountering Earth’s magnetic field, the energy can interact with conducting materials such as the crust or ocean and induce geoelectric fields. The currents destabilize electrical transmission as they flow through extrahigh-voltage transformers that regulate voltage in the grid.

Yet despite their potential for havoc, geomagnetic storms are an underquantified threat. Existing socioeconomic assessments of space weather are often siloed by discipline and overlook the relationship between geophysical drivers and the function of the power grid.

Tim Cook Steps Down: The Man Who Made Apple a $3 TRILLION Empire

Tim Cook is stepping down after 11 consequential years as CEO of Apple, one of the most innovative companies in the world. Following founder and visionary creator Steve Jobs, Cook was the right person for the job as Apple organized and consolidated Jobs’s brilliant insights in product development, then scaled them — and the company — across the globe.

Born in a small town in Alabama, Cook attended Auburn University and Duke University. He worked at IBM before being recruited by Jobs to join Apple in Silicon Valley, where he put his operational talents to work. As CEO, under Cook’s leadership, Apple became the most valuable publicly traded company in the world, growing into a multi-trillion-dollar enterprise while expanding its services revenue stream. Under his leadership, functionality was enhanced across Apple products, the integrity of its ecosystem was maintained, and multiple manufacturing bases were added to its supply chain. Along the way, Apple became an economic powerhouse.

Tim Cook will continue to impact the company as executive chairman. John Ternus will become the new CEO.

The New Urgency of Protecting Critical Infrastructure

Dear Readers, The latest of the Security & Tech Insights newsletter covers the domain of protecting critical infrastructure and its urgency.

Protecting critical infrastructure is not optional—it is a strategic imperative for national security, economic stability, and public safety. The grid, water, transportation, space, and other sectors are deeply interconnected and interdependent, with their failure or disruption having cascading effects across multiple domains. And the threat landscape is evolving rapidly. Legacy operational technologies and industrial control systems, once isolated, are now connected to IT networks, the internet, and the Internet of Things, creating exponentially more entry points for attackers.

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.

Simulations reveal asymmetric diffusion of magnetic skyrmions through an off-center gate

Diffusion is a fundamental natural phenomenon that can be observed across a wide range of length and time scales. It plays a key role in many fields, including physics, biology and economics. In particular, asymmetric or directional diffusion of particle systems has attracted growing interest for practical applications, including the development of unconventional artificial intelligence (AI) hardware, where it could enable nonlinear, geometry-controlled information processing.

Magnetic skyrmions are topological spin textures that can behave as particle-like objects with chiral dynamics. Recent reports have shown that even tiny thermal fluctuations can drive effective diffusion of skyrmions in ultrathin magnetic films and layered heterostructures. Some experiments have also revealed a topology-dependent sideways, wall-guided motion known as the Brownian gyromotion of skyrmions when they interact in a confined space.

Magnetic skyrmions can also exhibit exotic dynamic behaviors that cannot be reproduced by common particles. Their diffusive properties have immense potential in novel information-processing applications. However, these properties, especially in structured environments, remain largely unexplored.

Why Doesn’t the Federation Use Replicators to Become Infinitely Rich?

If the Federation can replicate food, clothing, furniture, spare parts, and even medical supplies, then why doesn’t it simply use replicators to become infinitely rich?

The answer is much more interesting than simply saying “money doesn’t matter in Star Trek.”

Replicators don’t create infinite wealth — they create abundance.

Once almost anyone can produce a particular object on demand, that object stops being scarce. And when scarcity disappears, so does much of its economic value.

But replicators can’t eliminate every kind of scarcity.

You can’t replicate land. You can’t replicate a historic location. You can’t instantly replicate decades of human experience, expertise, creativity, reputation, or time.

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