I think its time to propose a constitional amendment in all possible states to tax companies who use AI at the expense of human work.

If its innovative, no tax, if it replaces human work, huge tax!

How do we start? What organizations can take this on?

I guess for starters this could go viral...

Laptops should have a heating mode that uses the CPU/GPU to keep the laptop warm when you're carrying it outdoors in the winter, even with the lid closed.

The problem is that when you bring a cold laptop into a warm building, moisture from the indoor air can condense on its cold surfaces, potentially damaging the electronics.

For example, if it's 22°C indoors with 50% relative humidity, condensation can form on surfaces below approximately 11°C.

A winter heating mode could use the CPU/GPU to maintain the laptop above a minimum temperature, perhaps 15°C, while monitoring temperatures and battery consumption.

Since modern laptops already have temperature sensors, powerful processors, and batteries, much of the necessary hardware is already there.

The result would be a laptop you could carry around in freezing weather and immediately use when you get indoors, without worrying about condensation water damage.

Starship launches are extremely loud and can disturb nearby wildlife, potentially causing hearing damage or other injuries.

What if SpaceX trained crows to recognize a signal indicating an imminent launch and then warn other animals to move away?

Crows are intelligent, can learn from one another, and communicate danger through alarm calls. Other bird species, and even some mammals, can recognize and respond to these warnings.

The idea would be to train a group of crows to respond to a prelaunch signal by making alarm calls and flying away from the rocket. Their warnings could spread through the local wildlife population, encouraging other animals to leave the area.

The animals wouldn't necessarily need complicated instructions about where to go. They could simply move away from the enormous, visible rocket.

Unlike warning sirens or preliminary engine firings, this approach wouldn't require generating extremely loud sounds over a large area. Instead, it would take advantage of existing communication networks among animals.

Of course, it would need to be tested to see whether other animals actually move away rather than hide or investigate the warnings. Introducing additional crows could also disrupt the local ecosystem, so using birds already native to the area would be preferable.

Perhaps we could train intelligent animals to serve as intermediaries, allowing humans to warn entire ecosystems about impending dangers.

P.S. They could go underwater during the launch to avoid hearing damage.

Understanding an AI-generated mathematical proof may soon be like trying to understand the assembly code produced by an optimizing C compiler. It's technically possible, but why spend time doing it when better tools can do the work for you?

Instead of having mathematicians spend weeks or months checking AI-generated proofs and trying to extract insights from them, we should publish these proofs with formal verification in Lean.

Each paper would contain an English writeup and a corresponding Lean formalization. Lean would verify the formal proof, while future generations of increasingly powerful AIs would:

• Check that the English statements accurately correspond to their Lean formalizations.
• Find mistakes or discrepancies that earlier AIs missed.
• Simplify the arguments and discover more elegant proofs.
• Extract mathematical insights from the proofs and explain them to human mathematicians in simple English.
• Generalize the results and discover connections to other areas of mathematics.

The papers could be continuously improved as stronger AIs become available, while preserving earlier versions.

Given how quickly AI capabilities are improving, a mathematician might spend six months understanding a complicated proof that an AI released a year later could explain clearly in minutes.

Why not leave that work to future AIs?

Human mathematicians could focus on identifying interesting mathematical questions, exploring applications, and developing new research directions. They could still benefit from the insights contained in AI-generated proofs without having to decipher the proofs themselves.

The goal should be to advance mathematics and make its proof insights automatically accessible to humans via ever more powerful AIs.

macOS already supports light and dark variants of app icons. Why not use them to make apps easier to find in the Dock?

Apple could add an "Alternating Icons" option that automatically displays Dock icons in a light-dark-light-dark pattern.

This would be especially useful in Light Mode, where alternating between light and dark icons could make adjacent apps easier to distinguish and individual apps faster to locate.

You could arrange your apps in whatever order you prefer, and macOS would automatically choose the light or dark variant of each icon based on its position. Rearranging apps would automatically update their appearances to preserve the pattern.

If the contrast between adjacent icons is too strong, macOS could also use its existing icon tinting capabilities to soften the difference while preserving enough contrast to distinguish neighboring icons.

Apps without both variants could simply use their existing icons.

I'm less sure whether this would work as well in Dark Mode, so perhaps the option could be limited to Light Mode.

The idea is to make the Dock easier to navigate without sacrificing the freedom to arrange apps however you like.

Like, haven't we studied plants enough to understand how they grow and use that to create solid carbon out of the air to possibly create material that we can work with?

I've started using ChatGPT's scheduled reminders to monitor the SSD health of my MacBook Pro. It's a simple way to track SSD wear over time and potentially catch applications causing excessive disk writes.

On macOS, install smartmontools using Homebrew:

brew install smartmontools

Then retrieve your SSD statistics with:

smartctl -a /dev/disk0

Ask ChatGPT:

Remind me daily to submit my SSD SMART report. Compare it with previous readings, calculate how much data was written since the last report, estimate daily and annual write rates, and flag unusual activity or changes in SSD health.

The most important statistics are Data Units Written, Percentage Used, Available Spare, and Media and Data Integrity Errors.

If write activity seems excessive, you can also include disk-write totals for individual processes from Activity Monitor → Disk to help identify possible causes.

I'd recommend daily checks when investigating a problem and weekly checks for routine monitoring.

Modern SSDs generally have substantial endurance, so there's no need to obsess over every gigabyte written. But this seems like a useful application of ChatGPT's scheduled reminders for preventive computer maintenance.