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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?

Reminds me of when The Powers That Be forced me to connect to websites with HTTPS. Then they stopped supporting Internet Explorer 5. What were they trying to hide?

I do not think there is adequate reason to believe that FIDO Alliance members are supporters of Project 2025.

Impossible. Because iPhones randomly force you to enter your iCloud password, often at the worst possible time. Such a user would have already been prevented from signing in to their own iMessage on a random Tuesday afternoon.

One of the most frustrating issues with Apple's UX.

Virtually every authority on passkeys is going to have an industry connection. Just like how most climate change authorities receive funding to do climate research, how SEC investigators typically have backgrounds in banking, open source military analysts are veterans, etc.

It's not because people are bought by the powers that be, it's the way the world works. People enter the fields they have expertise in.

The next paragraph states that Yubikeys are a registered authenticator. Yubikeys are platform-agnostic.

That's not accurate. If that were true, then a hacker stealing password hashes would enable them to instantly log in, without cracking them. Rainbow tables and dictionary attacks exist for a reason.

Pass-the-hash has been tried in NTLMv1 and thankfully that was the end of that failed experiment.

Modern password authentication is performed by the client sending a plaintext password encapsulated within a symmetrically-encrypted tunnel. On the Web that's with TLS. The server then uses bcrypt or another scheme to hash the password (along with the stored salt) and compared that resulting hash with the value in the table.

The kind of bug that can be fixed by overwriting instructions with NOPs is trivial. The OP isn't trying to invalidate Microsoft's SDLC & QA. They just wanted a solution.

The company I work at pays a similar distribution to the H1B salaries offered by Anthropic: https://www.levels.fyi/h1b/?q=anthropic .

> I can guarantee you that there are enough US citizen/resident programmers to meet your hiring goals.

You can't make that guarantee. These companies spend lots of money to hire immigration lawyers to sponsor visas and process H1B -> Perm processes. The market would absolutely reward a participant who could bypass this headache and hire only people who do not require visa sponsorship. But the counterfactual has been tried. Many startups do not sponsor visas and they get outcompeted frequently.

I was glad it was in place when I was impacted by a layoff. It was the difference between severance and none.

I agree. The externality of layoffs gets partially transferred to the company and they're required to provide 3 months of salary for each impacted employee. It appears to work better for American companies AND workers. Both earn far more than their European peers who don't experience comparable layoff frequency.

me: observes something

you: where's your evidence?

If you need evidence, look at https://www.levels.fyi/h1b/?q=anthropic . Anthropic seems to need to sponsor visas for their workforce as well. Just like every other large US company.

It's demonstrably not. NVidia, Anthropic, OpenAI, Jane Street, the National Basketball League, Bridgewater, Apple, etc, all sponsor visas so they can recruit the best. Raising pay for basketball players doesn't reward exclusion of global talent.

I used to be optimistic that we could train displaced coal miners to code. This was tried in the 2010s and did not work. There is a distribution of aptitude in different subjects.

Imagine how much effort it would take to train a league of Google engineers to be NFL players. It's far better to use a recruiting pipeline of people who self-select for the role and have achieved rounds of selection for their talent.

You haven't shared your recommendation. What is it?

I hire new grads and experienced engineers, roughly half of who require visa sponsorship.