Don't be so sure of that.
If your PIN just happens to start with 00, it is fairly trivial to jury-rig a common 4-digit hacking device to crack your 6-digit PIN.
193 karma · joined February 14, 2012
At this point, eclipsing the story of "the cool game that never shipped" with an actual game is a very high bar indeed.
See https://www.levels.fyi/comp.html?track=Software%20Engineer&r...
It feels like an obvious oversight that there is not some company-wide Wiki to organize all of these docs. Since we are talking about Amazon/AWS, this has to be intentional. Can you speculate on why this gap exists?
Sadly the post skips over the format of these docs - is there a good resource for examples/templates of the different doc types (with comments?)?
Also, how are these documents shared and made discoverable internally? Do they refer to each other?
[0] https://meta.wikimedia.org/wiki/Wikimedia_Foundation_salarie...
> COO, Scott Gelb [...], as a comedy bit, [...] has repeatedly touched subordinates’ balls or butt or farted in their faces. [...] his punishment—two months of unpaid leave and training. [1]
From OP's interview with CTO Mike Seavers:
> Every time we sat down to go through the past quarter and plan the next one at Riot Games, we came up with a leadership theme for the quarter. For example, we weren’t going to make decisions for others for a month. This put all of us on the same page, and we got everyone to think about it and talk about it. When my direct report came to me asking, “Can I do this thing?” It was easy for me to say, “I’m not going to answer that question. You know the theme of the quarter, so you need to at least think it through before I give you an opinion.”
At least they are consistent.
[1] https://kotaku.com/top-riot-executive-suspended-without-pay-...
In other words, if I click "send" on my resignation email to my employer, but later argue in court that I totally didn't mean to actually resign, but only to check if my email program works, I may have a challenging case.
Interviews are much more of an art than science and asking good questions is hard. In general, they should be open-ended and get people out of their comfort zone to avoid canned answers. At the same time it's an interview, so you will want to leave on a positive note.
My advice would be to think of what is important to you at work. Then research about the company (maybe also by talking to current/past employees). In the interview, carefully probe for any red flags to confirm your suspicions. Personally, I'd go for things like work/life balance, WFH and career progression due to Covid, but that's very much up to you.
For example, what usually has to happen for a dev to trigger a rollback? Or how do they handle stateful changes such as database schema changes?
I can highly recommend anyone to read about the process of medical emergency triage in general. It drastically reduces the knowledge needed to solve complex situations and gives you something to hold on to when things get hot. Seeing these stressful problems reduced to if-else flows was very inspirational for me for designing ways to tackle urgent issues in other areas of life, e.g. tech support, service requests or HR.
It can be easier to have custom subdomains running separate instances, since this will limit how outages/upgrades/security affect customers. You also can intentionally keep a customer on an old version, which can be a bug or a feature.
But it can also be easier to have tenants, since you can update all users at the same time and you will pay less overall for infrastructure.
Having done both, I personally prefer tenants since it's easier to write, support and scale. But if you're B2B, you should carefully investigate the other option.
This product is undoubtedly the P in PaaS, but there is no service behind it. If your company uses this as an alternative to a real Heroku/AWS/xyz PaaS, you must have engineers at hand for 24/7 ops, scaling servers and fixing bugs. In my opinion, this is quite risky for anything running in production and should not survive a cost-benefit analysis.
The site looks great.
That said, companies that are fully remote (e.g. Gitlab [2]) tend to actually adjust your wage for having similar purchasing power wherever you choose to live. This then encourages the company to hire from inexpensive countries, which has it's own pros and cons.
[1] https://www.forbes.com/sites/abdullahimuhammed/2019/05/21/he...
[2] https://about.gitlab.com/handbook/people-operations/global-c...
On an unrelated note, incredibly shady things are currently being done by US corporations in regards to the 5GHz unlicensed spectrum being used for commercial LTE [1]. This is obviously a very slippery slope and would need strong regulation from the FCC. However, the FCC just approved it for live use in February (Pai got into office in January).
[1] https://en.wikipedia.org/wiki/LTE_in_unlicensed_spectrum
Is there a behind-the-scenes somewhere? Is this regex magic alone?
> Finally, while generally matching the skill level of controllers from neuro-evolution/deep learning, the genetic programming solutions evolved here are several orders of magnitude simpler, resulting in real-time operation at a fraction of the cost.
> Moreover, TPG solutions are particularly elegant, thus supporting real-time operation without specialized hardware
This is the key takeaway and yet another reminder to not make deep learning the hammer for all your fuzzy problems.
It's an important political gesture that Nadella goes in this direction. Since they also added a linux subsystem into the latest Windows release[4], I get the impression that he wants to leave the cloud to linux and try to position Windows as a user-facing client. This is a difficult decision to make, but it makes sense. Microsoft without Ballmer is seeing its position in the Corporate world as it is and I hope we will continue to see more openness as a result.
[1] http://www.slashgear.com/hp-pays-500000-for-linux-foundation...
[2] https://www.microsoft.com/en-us/Investor/earnings/FY-2016-Q4...
[3] https://en.wikipedia.org/wiki/Embrace,_extend_and_extinguish
That Facebook talk publicly about this issue (naming it a software bug) either means some lawyer business is already happening in the background, or the difference between what they promised and delivered is so obvious that it is just a question of time. This article is bad for Facebook's image as an advertisement platform and there is no reason to publish something like this, other than liability.
That said, Facebook has good lawyers and will obviously make it exceptionally hard for customers to prove Facebook is at fault. Additionally, their terms of service for the self-serve ads[1] is filled with blurry statements such as "we are not responsible for [...] technological issues [...] that may affect the cost of running ads", which will make legal battles lengthy and boring.
One of the key features of golang is concurrency. Your code is single-threaded, even though hill-climbing and annealing (and also all kinds of image operations) could be highly parallelized. Maybe that's something rewarding to look into at some point?
If you ever find the time, can you outline your strategy for your choosing a convergence algorithm? How did your experiments go for choosing the parameters (you called them maxAge, maxTemp, etc.) for those? Why did you currently end up choosing hill climbing over annealing, here: https://github.com/fogleman/primitive/blob/master/primitive/...
It's a ~$50 USB dongle, opensource and available for shipping. Anecdotally, I personally used it for an RF project that need uniform randomness and exhausted /dev/random on the target hardware. It worked fine, if a bit slow for my very specific usecase.
That said, if you want to go even cheaper, seriously consider if you can just stick with /dev/urandom. See http://www.2uo.de/myths-about-urandom/ for an interesting read on why that might just work.
Even a human brain has to train for ~4-5 months to become interested in shapes (https://en.wikipedia.org/wiki/Infant_visual_development). Once the human brain has been trained for these basic shapes for a while, it is able to quickly break down a new class (i.e. a cat) and recognize similar patterns in other images. This is something that is very similar to the way that training a deep NN works.
Also don't forget that the current NN are being trained mainly for photos, not moving images. A brain may recognize a cat by its tail-wagging or fur movements, which is a dimension that is completely missing from still images.
Also check out this similar post and discussion: https://news.ycombinator.com/item?id=9247851