2,111 karma · joined August 3, 2012
They threw the book at him. He was charged and faced a maximum of 50 years in prison.
OpenAI committed very similar crimes on a much larger scale, yet the most they will see is civil litigation.
Insiders have called it the largest theft of labor ever in history[1].
In the USA, corporations enjoy constitutional protections, the right to free speech etc, yet they are rarely if ever charged with crimes. For examples, see how the courts handle:
* large scale systematic wage theft by corporations vs petty theft by an individual,
* negligence infecting a 10k Americans with HIV by selling known-to-be-contaminated blood products (Bayer)
1. https://arstechnica.com/tech-policy/2026/09/microsoft-exec-c...
Imagining a mode where the agent is very transparent about its direction and process, and I can passively interject at any time to steer the outcome, without having to wait my turn or hard-interrupt.
She stayed in the race for Super Tuesday in 2020 rather than consolidating the progressive vote for Sanders.
Right before, her campaign accepted millions in funding from billionaires after promising not to. Her comment was roughly, as soon as others stop taking billionaire money, I will stop.
So perhaps you are a constituent part of the larger consciousness, and you feel your part of it (e.g. your roles and relationships in society)
Only the US sees this as a competition, new space race, Cold War, etc.
The way these “AI is too powerful now” articles read about Mythos, Fable, GLM, etc is completely incongruent with my experience using them. It feels like they are all trying to position themselves to influence government policy.
Claude will, without prompting, break the implementation into 6 phases, and write AI slop “code as English” specs for each phase, each one with glaring errors and unintelligible terse jargon. It will review them all several times with major findings every time and tons of design churn…
Then it will implement a total heap of garbage over many hours of many agents, despite it working in “lanes” and in parallel, and with regular input needed.
Just thousands and thousands of lines of junk, which auto review then plays whack-a-mole to polish and fix. All the while it is able to see the errors and edge cases, yet fails to see the key architectural blunders that led to them in the first place.
I’ve had to fully rethink my approach to LLM tasks like this. For example, for library-esque modules, I have found that isolating the problem outside of the codebase is one useful approach. Something about the lack of noise. It can land on a cleaner solution that can be retrofitted.
I also find that asking it to implement end to end in one fell swoop with a very high level plan actually saves time and creates a cleaner result.
I have found that WG client management is as simple as a couple scripts and a TSV file to match pubkeys to users.
Anyhow, cool project and I like the overall concept of respecting existing config.
This is why I made ParaSpace (https://paraspace.dev/)
With ParaSpace I can use a real terminal and my normal tooling to develop locally on fast booting isolated containers. I even get to bring my own dotfiles.
For example #1, the idea of a central codebase + many deploys was not always the way folks did things lol.
The (2025) date must not be correct…
It’s clear as day. I’ve also noticed this behavior on Sundays, not just US workday hours.
Sometimes the summaries feel totally alien to the task or code.
No gender, cases, tenses, conjugation, articles, word order inversion, etc. It's remarkable.
Mandarin has it's own complexities but grammar wise, it feels more optimized or simpler.
It's sometimes challenging to get a Rust program to compile... but if you do, it's probably going to work.
- Suggest a better approach that makes the AI say, “That’s much simpler. And you’re right. My original plan was over-engineered.”
However, powerful interest groups like ad companies that profit from your attention (which hysterically virtually powers the Internet today) were able to stop it from happening.
It was debated way back in 2009 when the GDPR was being developed. Iirc the argument was that browsers accept cookies by default so users do not get a fair consent moment. This is obviously easily fixed by regulation requiring browsers to ask users once.
Seems extremely backwards that we chose to forever darken the entire Web browsing experience just so users can "benefit" from a per-site option to let Google profit from them, with virtually zero payoff for the end user (ad relevance?).
P.S. If ad revenue is an essential pillar of Internet survival and fruition, the clear alternative seems to be sharing a fraction of that revenue with the tracked consumer.
Pretty evident as they kicked it off with self-imposed limits (“0days on every OS”) etc, OpenAI didn’t get the same treatment, and the ban was conveniently lifted as soon as they needed to compete.