If only this Dockerfile were real. It would greatly help app developers and publishers:

FROM apple/mac-os-slim:latest ...

Please, Apple, please let your developers use more virtualization or containerization.

An over-simplified approach that would be interesting to explore:

1. Given a collection of logical arguments, figure out how to assign a hash to each argument.

2. Build a Merkle tree representing the argument's hashes, nesting according to first principles.

3. If an argument is challenged successfully, the argument's hash changes, rendering descendent argument hashes invalid.

Possible fallacies in the post's argument

Slippery Slope: The argument may overstate the direct line from investment in AI to catastrophic outcomes like global financial depression or war over resources.

Appeal to Fear: Highlighting extreme potential risks (e.g., worldwide depression, war over resources) without acknowledging the possible mitigations or the improbability of worst-case scenarios could play on irrational fears.

False Dichotomy: The argument presents the situation as an either/or scenario—investing $7 trillion in AI versus addressing global needs like hunger and education—without considering that investment in technology can also lead to economic growth and solutions for these issues.

Straw Man: The argument might misrepresent Sam Altman's or AI proponents' positions, implying they disregard any potential negative outcomes or alternative uses for the funds, which may not be accurate.

Overgeneralization: Using specific instances of negative outcomes related to AI to argue against a massive investment in AI could ignore the diversity of AI applications and their potential benefits.

Steel-manned deductive argument

Premise 1: The consumption of energy and natural resources required for AI infrastructure, particularly if it continues to grow, is massive and potentially unsustainable.

Premise 2: The economic investment of $7 trillion into AI by Sam Altman is significantly higher than the funds allocated to essential global needs like education and hunger, indicating a misallocation of financial resources.

Premise 3: The financial risk of investing $7 trillion into AI is enormous, with potential repercussions including a global financial depression that could surpass previous economic crises.

Premise 4: The development of AI at the scale proposed threatens to infringe upon intellectual property rights, harming artists, musicians, writers, and other creators.

Premise 5: Negative externalities, such as misinformation, cybercrimes, and the exacerbation of global resource conflicts, are not being adequately addressed by AI developers like OpenAI.

Premise 6: The rush to invest in AI before understanding the specific technological needs and proving real use cases is premature and risks significant financial and societal setbacks.

Conclusion: Investing $7 trillion into AI as proposed by Sam Altman is a reckless expansion that overlooks significant environmental, economic, and societal risks, and should be reconsidered until the technology is proven to be safe, effective, and beneficial on a net basis.

Grats on the launch!

Would be very interested to see this working with GCP Cloud Run.

Thanks! It's on the roadmap :)

A good test of LLMs:

> Give me a list of 5 words having 5 syllables each

Mistral 8x7B and GPT 4 both choke on this frequently.

"I don't play craps. I'm a dice engineer!" - prompt engineers, satirically

I assume you're talking about mDAU.

This is what Twitter says, essentially:

"We used internal data to produce a judgement-driven estimate that something is X, but we could be wrong, and it could be higher than X".

How is something so heavily caveated a lie?

Not only is the trial schedule not changed, but Chancellor McCormick also made it clear she had little patience for expansive discovery for the whistleblower points. She is only allowing targeted, incremental discovery for these new additions to the case. If Musk starts making sweeping document requests based on this, she's going to be quite unhappy.

Yes, Musk won the point of including the Mudge disclosures, but he has to prove them with little to no discovery on a breakneck timeline. That's a hand tied behind his back. I see this as a win for Twitter overall.

Musk has the burden of proof to show fraud or MAE (material adverse effect).

For fraud, he needs to prove scienter as well as reliance. High bar, and undermined by his own tweets and podcast appearances.

For MAE, it requires Musk to show Twitter caused deep, lasting, permanent damage to the business. It's an even higher bar than the fraud route.

Not looking like Musk is going to succeed, even with this latest termination.

The trial is supposed to be finished in a week on October. You can by November calls at the $50 strike price for $0.60. So… easy money?

yes.

Premise 1: Showing ads to bots is generally not good for business.

Premise 2: Showing ads to humans is generally good for business.

Premise 3: A cohort can be created to hold humans (called mDAU).

Premise 4: Only show ads to the mDAU cohort.

Therefore, it is reasonable that increasing the number of humans in mDAU is better for business, because it means more humans are viewing ads. Assuming for sake of argument that the cohort process works well to exclude the bots, increasing mDAU is good for business and should be incentivized.