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How SpaceX and XAI Will Build Moonbase Alpha and Mass Drivers

SpaceX, in collaboration with xAI, plans to build a lunar base called Moonbase Alpha using advanced technologies such as mass drivers, solar power, and Starship, aiming to make human activity on the moon visible, affordable, and sustainable ##

## Questions to inspire discussion.

Launch Infrastructure Economics.

🚀 Q: What launch costs could SpaceX’s moon infrastructure achieve? A: Mature SpaceX moon operations could reduce costs to $10/kg to orbit and $50/kg to moon surface, enabling $5,000 moon trips for people under 100kg (comparable to expensive cruise pricing), as mentioned by Elon Musk.

⚡ Q: How could lunar mass drivers scale satellite deployment? A: Lunar mass drivers using magnetic rails at 5,600 mph could launch 10 billion tons of satellites annually with 2 terawatts of power, based on 2023 San Jose State study updating 1960s-70s mass driver literature.

Starship Capabilities.

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Optimus Surgeons in 3 Years | MOONSHOTS

Optimus robots, with their rapidly advancing capabilities in AI and dexterity, are poised to revolutionize the field of surgery, potentially surpassing human surgeons in precision and accessibility within a few years and making traditional surgical expertise and even medical school obsolete.

## Questions to inspire discussion.

Healthcare Access & Economics.

đŸ„ Q: How will Optimus robots change healthcare costs and accessibility?

A: Optimus surgeon robots will operate at costs limited to capital expenditure and electricity, enabling deployment in rural villages and developing countries like Zimbabwe and throughout Africa, demonetizing and decentralizing access to medical care that will exceed what presidents currently receive.

Technology Timeline & Capabilities.

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Claude Opus 4.6 vs GPT 5.3 Codex: Which is better for programming? | Peter Steinberger

Claude Opus 4.6 and GPT 5.3 Codex, two AI models, have different strengths and interaction styles, highlighting the trade-offs between elegance, reliability, and efficiency in their performance ##

## Questions to inspire discussion.

Model Selection Strategy.

🎯 Q: Which AI model should I choose for different programming tasks?

A: Use Opus for interactive roleplay and quick command following with trial-and-error workflows, while Codex excels at delivering elegant solutions when given proper context and reads more code by default.

🔄 Q: How long does it take to effectively switch between AI models?

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AI captures particle accelerator behavior to optimize machine performance

Keeping high-power particle accelerators at peak performance requires advanced and precise control systems. For example, the primary research machine at the U.S. Department of Energy’s Thomas Jefferson National Accelerator Facility features hundreds of fine-tuned components that accelerate electrons to 99.999% the speed of light.

The electrons get this boost from radiofrequency waves within a series of resonant structures known as cavities, which become superconducting at temperatures colder than deep space.

These cavities form the backbone of Jefferson Lab’s Continuous Electron Beam Accelerator Facility (CEBAF), a unique DOE Office of Science user facility supporting the research of more than 1,650 nuclear physicists from around the globe. CEBAF also holds the distinction of being the world’s first large-scale installation and application of this superconducting radiofrequency (SRF) technology.

Creating CAR-T Cells Using Current Alzheimer’s Antibodies

A team of researchers has biologically engineered T cells with currently available Alzheimer’s drugs in order to directly attack the characteristic amyloid plaques of Alzheimer’s disease.

Building on the current paradigm

Most Alzheimer’s treatments used in the clinic are-mabs, monoclonal antibodies that are designed to attack the amyloid beta plaques that accumulate in the brains of people with Alzheimer’s. However, while they have been found to have enough meaningful benefits in clinical trials to be approved by the FDA, they are not a cure, and some analyses question their effectiveness [1].

Lateral habenula and periaqueductal gray neurons signal reward prediction error and continuity of reward expectancy to drive reward-seeking behavior

Lee and Hikosaka show how animals overcome challenges and ultimately achieve goals. They find that LHb and PAG neurons encode prediction errors and the continuity of reward expectancy, with tonic PAG activity sustaining reward expectancy despite prediction errors.

Organic molecule stores solar energy for years, then releases it as heat on demand

When the sun goes down, solar panels stop working. This is the fundamental hurdle of renewable energy: how to save the sun’s power for a rainy day—or a cold night. Chemists at UC Santa Barbara have developed a solution that doesn’t require bulky batteries or electrical grids. In a paper published in the journal Science, Associate Professor Grace Han and her team detail a new material that captures sunlight, stores it within chemical bonds and releases it as heat on demand.

The material, a modified organic molecule called pyrimidone, is the latest advancement in molecular solar thermal (MOST) energy storage.

“The concept is reusable and recyclable,” said Han Nguyen, a doctoral student in the Han Group and the paper’s lead author.

Graham Priest: Dialetheism & the Limits of Classical Logic

For 2,500 years, Western thought has treated contradiction as catastrophic.

From Aristotle’s law of non-contradiction to modern formal systems, logic has operated under one sacred assumption: a statement cannot be both true and false.

But what if that assumption is wrong?

In my latest Singularity. FM conversation, I sit down with Graham Priest — one of the world’s leading philosophers of logic and the foremost defender of *dialetheism* — the view that some contradictions are true.

We explore:

‱ Why the liar paradox still unsettles logicians ‱ How paraconsistent logic blocks “explosion” ‱ Whether classical logic is incomplete rather than universal ‱ What Buddhist philosophy understood about contradiction centuries ago ‱ And whether AI systems may require non-classical logics to model human reasoning.

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