Around 2003, I was excited by how easy it'd become to get information. You could read the literature without walking to 4 different libraries, could read about local politics from experts, etc.
Today, it's even easier! But this hasn't really changed the public discourse.
Covid-19 is another example of this.
In January, anyone could've gone on pubmed, spent 3 hours, found out masks are effective without special training, 6 ft. rule insufficient indoors, air travel is risky, etc. (reading previous studies on SARS, coronaviruses).
And yet, the info most people have seems to be 4-N months behind what laypeople with 3 hours+pubmed knew in January.
The thing I wouldn't have guessed in 2003 is that informative indie bloggers would be rendered irrelevant by "social" algorithms that funnel people to clickbait.
I bought one of these in January and have been wearing when appropriate since then (when indoors with "strangers", etc.).
On thing I've observed is that people will give me a look and then move away from me, often towards somebody with no mask!
I find this to be pretty funny since somebody who wears a half-mask respirator at, e.g., the DMV, seems much less likely to have covid, not only because they're less likely to get infected under the same circumstances, they're likely to have less exposure independent of PPE.
How much less likely? Well, per the above, you can read the literature, but if you want an anecdote:
I wore a P100 in my apartment when I lived with somebody with covid and appear to have not gotten covid (no symptoms, negative antibody test after appropriate timeframe).
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I feel like this is true for lots of kinds of conversations and not just tech interviews.
People are correctly pointing out that, if you dig into the logic of basically anything, it falls apart, but that's also generally true of actual humans, even experts.
is ridiculous, but have you tried asking an expert coach on almost any topic why you should do X?
E.g., try listening to one of the top paddling coaches in the world explain *why* (the what is good, the why is nonsense)
Why do you let the boat "run" between strokes? The explanation is because the boat is moving at top speed when you remove the paddle from the water, so putting the paddle back in slows you down.
But of course this is backwards. The boat decelerates when you're not pulling,
What are examples of items/categories where you're really getting your money's worth at the high end, not necessarily in terms of utility, but in terms of the difficulty of producing the item more cheaply?
I find the contrast between these vs. "brand" items fascinating.
An example of a category that doesn't qualify but where some items qualify would be high-end fashion, where you're quite often mostly paying for the brand (e.g., an expensive Theory shirt) but there are plenty of items where you're paying for the item (e.g., a $5k Kiton suit).
An example of a category would be high-performance cars (with the notable exception of a few very niche brands like Ferrari, which are famous for having very high margins).
Even if you look at brands that laypeople consider to be "brand" purchases, like BMW,
Lots of people in my mentions saying things like "Elon is cleaning house! Lazy bums are getting what they deserve!", as if Twitter employees are getting a much deserved comeuppance.
Since people don't seem to understand what the bums at are getting, here's a short primer:
If you look at the people most responsible for Twitter's state, leadership, they had golden parachutes worth tens of millions of dollars
We can debate whether or not they deserve the money, but if you think someone is a lazy bum, cursing them to receive a $10M+ payout seems odd
If we're talking about engineers, Twitter has historically underpaid long-tenured employees relative to BigCo market rate.
The median raise the staff+ people I'm talking to are getting in their new offers is six figures.
One of the things that I think is sad about the decimation of Twitter eng is that Twitter was doing a lot of interesting (and high ROI) engineering work that, at younger companies, is mostly outsourced to "the cloud" or open source projects
The now gutted HWENG group was so good at designing low power servers that, in a meeting with Intel folks, discussing reference designs vs. what Twitter was doing, the Intel folks couldn't believe the power envelope Twitter achieved.
Twitter was operating long before gRPC existed, so they built Finagle. kostyukov.net/posts/finagle-… has some nice explanations and there's been a lot of innovation in Finagle since then.
Twitter still gets a lot of mileage out of owning its RPC layer
Nice thread about the misconception that major tech companies run systems that can run without intervention because they're automated
The example comes from Google, which is more automated compared than most major companies (MS, etc.), but still quite manual in an absolute sense t.co/diqwJ3RHZH
One thing that's been interesting about recent events is seeing how people imagine big companies operate, e.g., people saying that Twitter is uniquely bad for not having a good cold boot procedure.
Multiple $1T companies didn't or don't have a real cold boot procedure.
One of them is one of the most respected eng orgs on the planet and SREs there wonder if it would take weeks to come back up or months.
As someone who thinks a lot about risks, this isn't how I want the world to be, but it is how the world actually is.
An interesting thing about this claim is that not only is the implication wrong, Twitter probably has better evidence of its wrongness than any other company in its size class could have.
There are very few companies that have a better distributed tracing setup w.r.t. getting actionable insights on the backend and the ones that have a better setup are much larger (Google, FB, etc.)
Twitter client tracing also punches above its weight.
Of course, the key people who did that work left or got laid off, but it's clear from the data that, if you're looking at why Twitter is so slow in, e.g., India, Uganda, etc., esp. on slow devices, tail latency comes from the network due to unreasonably large payloads + client.