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McKinsey has multiple consulting verticals, including mechanical engineering, design, employing real professionals for actual work in addition to their traditional business consulting and advising.

I think this comment was just a popularist repetition of discourse from social media. In other words it's a "tiktok ahh take".

It's pretty quick! 30 days. I agree it's bad. Hardly comparable to indentured service.

This is more or less an uninformed vibes-based response.

1. Few workers report a 996 work schedule at Meta or other Mag7 companies. This work schedule is reported by smaller AI startups and Chinese and Indian tech firms.

2. H1B and many other sponsored visas are transferrable. I have had several colleagues get laid off or interview for other jobs and get hired elsewhere. The L visa is non-transferable, though it represents a minority of visa sponsorships in the US.

3. You directly ignored my data about workers at Meta out-earning other workers in the Bay Area. My foreign colleagues earned the same as I did at virtually every stage of my career.

In general macroeconomics, yes, the introduction of foreign workers results in wages getting pulled down. This "lump of labor" only has temporary impacts. The overall outcome is an increase in the market for engineers, as immigrants go on to found companies. NVIDIA, the world's most valuable company, is one of these.

I will never understand the framing of visa-sponsored workers at Facebook as indentured servants. These are incredibly highly-paid jobs, easily in the top 5% of earners in the United States even for fairly junior roles. Even in California, these folks are in the top quintile of earners. These are people who could earn a third as much in India, Canada, or the Netherlands, and still be living exceptionally well. They have exercised more agency than the vast majority of Americans or even Bay Area residents.

That said, expecting individual engineers to understand the greater context of building an online addiction machine is probably too much. The product managers and data scientists surface concerns and executives decide. And executives should be held criminally responsible in the event of gross negligence.

Indeed, it is a frustrating aspect of using hosted models that a ZDR contract must be negotiated for anything sensitive. There are all sorts of tradeoffs.

It's an unsubstantiated leap to assume intent. You didn't read the linked article. The US keywords didn't degrade model performance.

You're shifting the topic and hoping we won't realize it.

Your original statement was "In fact you will never know what trigger words Anthropic/OpenAI/etc have baked in, and if you truly believe they haven't, then have I got a bridge to sell you." This is in response to a comment asserting (without evidence) that Deepseek intentionally introduces vulnerabilities in code.

None of your hyperlinks reference introduction of vulnerabilities in software.

It's not surprising that guardrail triggers would degrade model performance. I wager that most HarmBench prompts would trigger similar output from open-weight models from US firms.

The link you cited postulates it is accidental.

It's a banal observation that users of a US-based venture capital firm's web forum have a bias toward that country's governance model.

What is the value in making an unfalsifiable assertion?

My comment? Please review the username of the comment in question.

If you feel a given comment is not within community guidelines you are free to flag it. I do not believe that we agree about the substantive value of noting an article was written with the heavy assistance of an LLM. I usually look at comments prior to reading an article; it's an effective time-saving measure.

I do not accept your attempt to make a blanket ban on noting an article was LLM-written.

It's not a shallow dismissal. Writing quality is core to the value of an article.

It's likely that but for LLMs, the article would not have been written. I'm glad it was written. It's also true that it's unpleasant to read LLM-written prose for those of us who have to read it all day for work.

My assumption is that every LLM-written article would just not have been written otherwise. That is a net good. It's also true that it's grating to read LLM-written prose.

Am I utterly mistaken or was LLM-written prose more tolerable when it was GPT-4o and Opus 3.x writing it?

> How do you know the hashed value stored in the database is the same hashed value the user submitted?

Please explain how authentication would occur without a comparison between the user's submission and a value stored at creation/update of the passphrase.

what are the winning Powerball numbers next week, future knower?