I've used Elixir since 2015 and in fact learned it first. I still think "Programming Erlang" is a much better book than any other for actually learning Erlang and BEAM/OTP principles. Erlang as a language is simpler, leaving more time and energy for learning the actual important bits about OTP.
First, this is narrowly about federal income tax. SpaceX presumably pays plenty of other taxes.
Second, using the projected profits in the article, SpaceX will have exhausted its NOL pool by the end of this year, and so will pay billions in federal income tax next year.
But more important: the whole point of these tax cuts and programs is to let businesses use losses today so they can create value — and tax revenue — tomorrow. Of course, if you take a snapshot after part 1 but before part 2, it will always look like “X gets Y from government and gives nothing back”.
Payroll tax is paid by the employees, not the company.
As for property tax, didn’t SpaceX move to its remote Texas location (“Starbase”) specifically to avoid taxes and regulations and to run its own company town.
It doesn't matter as much as you think. I believe this is in part due to how assertive most Elixir code tends to be. [1] These assertions not only aid the LSP and can cause compiler warnings/errors, they also help LLMs just like types do.
Still, every release now contains new type system features. Next up is full type inference. [2] After that will be typed structs.
This is a good way of framing that we don't understand human creativity. And that we can't hope to build it until we do.
i.e. AGI is a philosophical problem, not a scaling problem.
Though we understand them little, we know the default mode network and sleep play key roles. That is likely because they aid some universal property of AGI. Concepts we don't understand like motivation, curiosity, and qualia are likely part of the picture too. Evolution is far too efficient for these to be mere side effects.
(And of course LLMs have none of these properties.)
When a human solves a problem, their search space is not random - just like a chess grandmaster's search space of moves is not random.
How our brains are so efficient when problem solving while also able to generate novelty is a mystery.
Your unique advantage is you know Vitess super well. Your unique disadvantage is you know Vitess super well! Second system syndrome is real. Using as much Vitess as possible could help you guard against it.
This is so cool. A key benefit is that it's not embedding the C Lua runtime and compiler, but rather implements Lua in the host language (Elixir/Erlang).
When sandboxing user code in another runtime, you need to serialize the data to and from that runtime. That comes with a performance penalty.
So, for example, if you sandbox code in WASM, you need to pick a transport data format, like JSON. You need to serialize Elixir data structures into JSON, send it to WASM, and then deserialize the result. For a high-performance data pipeline, this adds up!
But if your sandbox is in the host language, no serialization/de-serialization is required. You can execute the sandboxed language in microseconds.
