Yes! Gibson recognized they were getting cut out of the vintage market and started making not only the reissues (RIs), but also the limited edition copy-of-famous-person's-guitar. What gets me is that Reissues these days are priced so close to vintage instruments. It's so hard to justify the purchase.
ADHD-haver here. I do the same thing but with music. I created a playlist of albums I've heard hundreds of times. The songs are in album order and when I play the list I play from the start of an album somewhere in that list.
It keeps that part of my brain occupied, but not focus, while I work on the task at hand.
I go through really weird phases with music. Music is a huge part of my life, sometimes I play piano, guitar, produce.
There's points I'll realize I've gone 6mo+ without opening spotify except for when I'm driving. Just months and months of the news or youtube as background and no music.
Oh man, thousands of up votes for a Led Zeppelin reference. This mirrors my experience as a musician. Learning to play gave me the confidence to go into different scenarios and recognize that I had to tolerate being bad first and then I would get it. It's a journey. It's a sacrifice. Strangely, it never felt like a sacrifice at the time.
i helped build this! it's not what i do anymore, and i don't want to go into too much detail, but the TL;DR is that, yes, just walk out (JWO) really does use machine learning models to identify which products customers are picking.
the non-obvious challenges of working in this space are that you have to deal with real world constraints that you just don't have to think about in 100% cloud based software. hardware goes down! internet connections go out! electricity goes out! how much processing can you do in store vs out of store?
that's just the tech in the store. what about humans? humans are now in your programming state moving shit around. in-store associates miss-stock items. kids do kid shit. people don't place things back exactly where they found them.
Then you have interesting distributed problems: how do you handle late data? what should be a massively parallel problem is really a graph of interactions that have to be resolved in just the right order so you can generate an accurate receipt.
and you know what's crazy? the vast majority of the time it works! exactly how they say it does: with machine learning models.
Hire for fire feels like an urban myth. We do a lot of work to find you, interview you, hire you, and train you. Managing someone out is also a lot of work.
That being said a company as big as Amazon will always have edge cases.
The myth I heard was:
Manager has 10 employees who are absolute rock-star engineers. They love their team, work great together, and deliver amazing results.
This manager obviously doesn't want to hurt this awesome team or lose any members, but Amazon wants them to churn out the bad engineers (which this team may not have).
So instead of finding faults where they don't exist, our manager hires 2 engineers with little to no chance of working out in the team long term, give them some busy work, puts them on a PIP, then eventually fires them, only to soon replace them with two new victims.
It sucks to be a victim, and it sucks to knowingly do that as the manager, but it does work out great for the team and the manager - so I think it could happen (maybe not super common, but it isn't unrealistic in my mind).
That's the problem with applying a curve as a rule. In a large org it's probably true across the board. But there will be outlier teams. How does an org handle those?
You can critique Amazon for basically saying "don't worry about it" so managers may invent plans like hire-to-fire to game the system and overall someone's gonna get screwed on that team, but it's a tough problem to solve - otherwise, what's to stop managers from all simply claiming "no, my team's a special case"? Introduce special cases and it'll just be gamed through that mechanism.
I'm a firm believer that if you want to avoid things like that you have to avoid large organizations. A large organization is highly incentivized to be bureaucratic so to minimize the effects of unexpected losses and to keep the money machine running.
>otherwise, what's to stop managers from all simply claiming "no, my team's a special case"? Introduce special cases and it'll just be gamed through that mechanism.
You lost me. Why should we want to stop managers from saying that?
You got the myth part right: having a single team with 10 rock-star engineers.
1. Amazon isn't so special that even they can control the distribution curve to only have rockstars,
2. This is too big for a single team in the first place, let alone 10 rockstars,
3. You don't want any rockstars, let alone only rockstars on your teams,
4. Managing low performers is a magnitude more work than solid performers; no
manager would do this to themselves on purpose. It would be easier to cut their 2 least rockin' stars.
I hate that some people say rockstars and mean ‘really great developers that write beautiful working well documented code quickly and work great as part of a team’.
And other people say rockstars and mean ‘assholes that churn out new features really fast with incomprehensible code and then leave others to maintain their monstrosity as they move on to the next thing”.
I assume Amazon is large enough to have a team somewhere with 6-10 of the ‘good’ version, and also a team somewhere with 6-10 of the assholes.
> Managing low performers is a magnitude more work than solid performers; no manager would do this to themselves on purpose. It would be easier to cut their 2 least rockin' stars.
Then what do you do a year (and a half for Amazon) later for the next cycle?
One of the many problems with stack rank cull N% of your employees every year is that "every year" part. At whatever level it's mindlessly applied, if the company wants to keep it at the same head count you by definition have a steady churn of hires, which I'll grant you won't always be good, and fires.
> Hire for fire feels like an urban myth. We do a lot of work to find you, interview you, hire you, and train you
Your unspoken assumption here is that recruiters, HR and managers have perfectly aligned incentives. It is trivial to find instances when this is not the case - e.g. a high-performance team being forced to fire their "least effective" member[s]- this relies on the theory that talent is uniformly distributed across Amazon.
Amazon manager here: I just did a mental count of our URAs while I have been at Amazon. More than 3/4 are new hires fired in less than a year.
Hire-to-fire is neither a conspiracy nor a conscious tactic. It's the natural consequence of what we managers are put into.
If HR wants you to URA someone out, who would you rather lose? The experienced SDE who is productive and is responsible for projects you don't want delays in; or the new hire who's still trying to learn company tools.
i think this is too pessimistic. via FBA they've also enabled thousands (hundreds of thousands?) of small businesses and a cottage industry of others that have formed around them.
Not sure what the J was for. Internally it’s been IHM since I joined. “Inventory Health Management” is a backronym. I won’t spill the - albeit boring - beans on where IHM actually comes from.
Disagree, because the issue here is where the filter is. As others have noted that a condenser mic has an internal preamp, it is most useful to filter inside the mic before amplification to preserve S/N ratio. I suppose you could do that with software in the mic, but that seems like a lot of effort for maybe a worse result.
Further down the audio path it eventually makes sense to digitize, but if you didn't have the HPF in the mic your noise floor will be worse.
Yes! Gibson recognized they were getting cut out of the vintage market and started making not only the reissues (RIs), but also the limited edition copy-of-famous-person's-guitar. What gets me is that Reissues these days are priced so close to vintage instruments. It's so hard to justify the purchase.
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