Agreed. I vaguely remember another HN link that said Apple tried a competing-team approach to building a better siri, but it fell apart due to internal politics reasons?
In your example, the amino acids order is sufficient to directly model the result: the sequence of amino acids can directly generate the protein, which is either valid or invalid. All variables are provided within the data.
In the original example, we are testing weather using the previous day’s weather. We may be able to model using whatever correlation exists between the data. This is not the same as accurately predicting results, if the real-world weather function is determined by the weather of surrounding locations, time of year, and moon phase. If our model does not have this data, and it is essential to model the result, how can you accurately model?
In other words: “Garbage in, garbage out”. Good luck modeling an n-th degree polynomial function, given a fraction of the variables to train on.
So sign your UUIDs and combine them into “$UUID:$HASH” strings for the same benefit. Or a more structured JWT-like payload that still verifies auth against the DB (as opposed to carrying authorization within the token).
No need to reinvision the rest of the auth flow if you just want to add hashing to reduce DB load.
If anything, an obfuscated microservice-based application is easier to understand than a monolithic version: network data transfer is easier for observers to understand than memory modification.
> An ambassador service can be thought of as an out-of-process proxy that is co-located with the client.
> This pattern can be useful for offloading common client connectivity tasks such as monitoring, logging, routing, security (such as TLS), and resiliency patterns in a language agnostic way. It is often used with legacy applications, or other applications that are difficult to modify, in order to extend their networking capabilities. It can also enable a specialized team to implement those features.
Not surprised this is a Microsoft page, given their legacy of long lifetime support for their software products.
It’s not for microservices, but rather for software maintenance of systems that other vendors would consider past EOL.
This number includes taxes, benefits, etc, not just raw salary.
Notably Signal employees do not get equity, so the salary must be higher to remain competitive.
Signal is probably the hardest class of product to build. Name an optimization/distributed systems problem, they probably have it. And quite literally, a Signal bug could jeopardize an activist/journalist’s life.
So for a <$200k salary and no equity, how many world-class engineers do you think you could hire?
I simply wouldn’t trust the product, if it had mediocre engineers.
“Google gave the second-place bidder a built-in handicap to make their offer more competitive” is the tamest way of phrasing it, given that the “handicap”’s only effect is to cost the first-place bidder more money.
It never helps the second-place bidder. I’d argue “handicap” is deceitful.