high_derivative

Does substack allow (paid) anonymous writing? I could not immediately find how this works from the faq. Will they protect their writers?

Ahhh: 1. We must censor terror propaganda and child abuse to avoid harm & because it's the law

2. We must censor stormfront and the far right because it's the right thing to do

3. We must censor covid misinformation because it could kill people

4. We must selectively censor news reporting for political candidates we are aligned with because it's probably false.

---- we are here now

5. We must remove all news critical of our position .

6. We must actively force people to be re-educated to avoid harm.

7. We must exterminate dangerous elements.

The mental gymnastics used to justify this kind of censorship are frightening. Most news is full of inaccuracies and outright lies, from all sources.

I am extremely pessimistic for ML ops startup like this. At the end of the day, cloud service providers have too much of an incentive to provide these tools for free as a cloud value add.

The other thing is that stitching together other open source tools like this is simply not enough value. Who will be incentivised to buy?

Saying this as FAANG ML org person where I see the push to open source ops tooling like this.

' who want to make this a "thing" '

Clearly it is a thing, why pretend otherwise? If this were some extremely small minority, it would not have such widespread cultural influence now. It is a thing.

It's most likely inspired by XLA (Accelerated Linear Algebra) - same creator(s).

Regarding management, it's a bootstrapping issue: The main requirement for an engineering management position is management experience. The easiest way to get it is to stay at one place for 3-4 years. The move based on that experience.

So I only looked at the website and docs as this is a something I have interest in. I'd be mainly interested in knowing how much results are already semantically structured. Example: FDA approval, earnings report filings, ...would I have to do this on top or will you provide fine-grained categories?

'have practically zero politics' tingles my bs-meter. How would you know how your employees feel about this? There is always politics. Of course not for the ones who cannot be promoted further, but for everyone else. My boss not acknowledging the existence of politics would be a red flag to me.

'should be incapable of joining the software profession based on their genetics'

He absolutely did no such thing and this is an incredibly disingenuous representation. You can still argue he should be fired without this.

I find codes of conduct meaningless. They will go on in very general terms about 'hate speech' which is just synonymous with 'anything that anyone feels offended by' now.

I would argue that code of conducts were a symptom of the start of the problem.

The strategy of the grievance class:

- Propose a code of conduct which surely nobody can disagree with, it's great to have rules and be nice to each other.

- Design the code of conduct so any perceived offence falls under it

- Wield it as a tool to push out any dissenters

I never understand why people are _so_ desperate to save a few bucks when risking their life savings versus using a professional tool if they desire to trade options (say, interactive brokers).

You save fees and then get screwed when Robinhood is down on expiration day.

Not sure what this metaphor adds, especially because it's inaccurate.

A short put does does not have unlimited downside as the value of the underlying can only go to zero. A short call has unlimited downside as the value of the underlying can go arbitrarily high.

I hope the irony is not lost on you when you ask me to leave this platform for disagreeing with you.

To me, it seems like a combination of childish-authoritarian beliefs that the world will change for the better once, and only once, you stop anyone from saying anything controversial at all. Once nobody is able to disagree, bad things won't exist any more.

Easter egg:

https://github.com/corona-warn-app/cwa-app-android/blob/mast...

object RiskLevelConstants { const val UNKNOWN_RISK_INITIAL = 0 const val NO_CALCULATION_POSSIBLE_TRACING_OFF = 1 const val LOW_LEVEL_RISK = 2 const val INCREASED_RISK = 3 const val UNKNOWN_RISK_OUTDATED_RESULTS = 4 const val UNDETERMINED = 9001 }

The undetermined risk level is over 9000?

I wonder how much it helped the creative flow to not know it was an allegedly unsolvable problem. No fear to fail, no stress, not the feeling something complex might be needed because everything simple was already tried.

You know who likes standups?

Program managers, project managers, and useless middle-managers. What do they have in common? They get to exercise power and justify their existence through calling extra meetings like new project-specific standups.

Who hates standups? Everyone else, basically.

Really makes you think..

No, that's your political interpretation of it. You __choose__ to read it that way because then his punishment can be justified.

Because you cannot deliver experimental physics breakthroughs or hardware with teams of two deciding every week what they feel like doing.

Have you ever thought about how much work it takes to deliver hardware? How many teams and processes and planning there are involved from physics level to software stack to deliver something usable? It's insane. And normal processor hardware is something people have experience with. For a physics experiment, virtually everything is custom made and you only have budget for a few fixes or trials on each component. There is just not much room for slack.

System design is not a typical part of a research interview.

Yes, they do. The rule of thumb is: The higher the level you are hired, the more wiggle room is there. A random PhD grad will need to pass the normal coding screens which are carried out by SWEs who do not know anything about the candidate.

Last q depends on the FAANG org, everything exists. MS research is very pure, Amazon/Apple very applied, everything in between.

(FAANG researcher):

The first few tech rounds tend to be the same.

Then there is a set of research interviews and usually a research job talk.

The main observation is that hiring researchers, after passing basic tech rounds, is much more about taste and how people subjectively rate someone's research. It's insanely competitive, but in a sense it is also easier than pure SWE because there are not as many whiteboard hurdles to pass. You just can't really leetcode your way into the role, without a good track record with really interesting research most teams will not be interested.

This is not my reading at all.

If you have ever spent time in a FAANG research org - it can be incredibly frustrating to see so much lack of focus. Everybody does what they want. This is not an issue for most e.g. ML research (my org) because there is so much money to go around, and researchers will leave if they are too constrained.

For hardware/critical projects or customer retention, this is very much an issue. Just look at how the TF ecosystem developed API wise.

There can literally be a project with enormous importance for an ecosystem where multiple teams under one VP do the same thing slightly differently. VPs do nothing and have no opinion on the details. Internal and external users get frustrated because there is no clarity.

If you do a project where you have resources for just one shot in a given timespan, this simply won't cut it.

Rather ironic considering the NYT again and again gave platform to people arguing for Title IX and complaining about De Vos trying to reign it in. Lives ruined. But a woman being falsely accused? That's international-news worthy.

This is not a good idea and definitely not worth the money.

If you want to pass a quiz-style interview (I interview for a FAANG ML research lab), you are much likely better served writing down the concepts yourself in a concise way. If you never wrote them down somewhere, you are not forced to actually digest the content. Cards you didn't write yourself will fool yourself into believing you understand something if you can repeat the words.

This may be unpopular but I have zero empathy for Airbnb hosts losing out on money. They were happy to make a profit while socialising the costs of their guests to their neighbourhoods. Now society wants some of that cost back, and they complain.

I have never and will not use Airbnb.

>And to oir luck the testing infrastructure in Germany is much better than in nearly every other nation (which also means the numbers are closer to reality than e.g. in Italy or the US)

I am baffled as to why you would think this?

"It's not “free speech” when it's an attempt to shout others down so that they have no voice. It's something else entirely."

Indeed.

Sorry for the snark, but I recommend narrowing the area of interest.

In particular, looking at one of the fired employee's Twitter, even in October, they were publicly bashing their employer, calling them evil, etc. pp [0]

[0] https://twitter.com/Tri_Becca90/status/1187460338784055296

It really does come off as if they are using unionizing as a veil for their political activism.

Shitting all over your employer on social media tends to be symptomatic for a certain character style who was long welcomed at Google, and probably felt empowered to take it further and further, to a point of actively damaging the company's interest. It takes someone pretty tone-deaf to do that and not expect to be fired.

This is a pet peeve of mine as well. A lot of undergrads are not really looking around any more. Universities offer their first data science courses in year one. Undergrads mapping out their paths towards becoming research scientists with dollar signs in their eyes.

I think this is not wise career bet at all. There will always be spots for a select few 'pure ML' grads, but at the post phd level the really good jobs are getting pretty thin unless you come from the right adviser + right school + right publication track.

On the other hand, if you add a secondary useful skill, like having a really good understanding of distributed systems, or networking, or databases, or embedded systems, or being 'just' a solid overall software engineer, you (i) have something to fall back on if ML dreams do not work out, and (ii) have an edge by being just the right fit for specific teams, while also still competing in the general pool.

I think there will be a rude awakening on this in 3-4 years for many.