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”.
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.
Sequin | Platform Engineer | San Francisco | ONSITE
We're building the world's fastest change data capture (CDC) platform for Postgres. CDC is a proven pattern that enables real-time use cases like triggering side effects, fanning out events, caching at the edge, and audit logging - but existing solutions are notoriously difficult to set up and maintain.
We're making CDC easy enough for weekend projects yet robust enough for Fortune 500 companies.
Sequin engineer here. We'll publish our benchmark repo soon! Indeed, we're still doing a lot of fiddling with Debezium ourselves to make sure we cover different configurations, deployments, etc.
The main thing we want to communicate is that we're able to keep up with workloads Debezium can handle.
(And, re: RabbitMQ, I wouldn't write off a platform based on a single application built on that platform :) )
Sequin | Platform Engineer | San Francisco | ONSITE
We're building the world's fastest change data capture (CDC) platform for Postgres. CDC is a proven pattern that enables real-time use cases like triggering side effects, fanning out events, caching at the edge, and audit logging - but existing solutions are notoriously difficult to set up and maintain.
We're making CDC easy enough for weekend projects yet robust enough for Fortune 500 companies.
AFAIK, the reason for these changes is basically "prevent AWS from eating our business". Is that right?
If so, are these trends harmful to open source? Are we not choosing between:
1. A world where all revenue in OSS infrastructure ultimately flows to a few big platform companies.
2. A world where these carve-outs are commonplace.
Meta's carve-out with Llama is so interesting because it practically calls the big companies out by name. Should there be a similar standard license for open source infrastructure?
We just applied this framework to the Sequin [1] docs two weeks ago. It has felt so nice to have a framework. I think our docs flow really well now, and it's been easier for us to add and maintain docs because we know where to put things.
The slightly ironic part is that the Diataxis docs themselves are a bit obtuse. It's a little verbose. So it took a couple passes for it all to click.
The analogy I gave my team that was helpful for everyone's understanding:
Imagine you're shopping for a piece of cooking equipment, like a pressure cooker.
The first thing you're going to look at is the "quickstart" (tutorial) – how does this thing work generally? You just want to see it go from A to B.
Then, you're going to wonder how to use it to cook a particular dish you like. That's a how-to.
If you're really curious about anything you've seen so far, then you'll flip to the reference to read more about it. For example, you might check the exact minutes needed for different types of beans.
And finally, when you're really invested in pressure cooking and want to understand the science behind it - why pressure affects cooking times, how the safety mechanisms work, etc. - that's when you'll read the explanatory content.
Comically, our docs were completely backwards: we lead with explanation ("How Sequin Works"). I think that's the natural impulse of an engineer: let me tell you how this thing works and why we built it this way so you can develop a mental model. Then you'll surely get it, right?
While that may be technically accurate, a person doesn't have the time or patience for that. You need to ramp them into your world. The quickstart -> how-to -> reference flow is a great way to do that. Then if you really have their attention, you can galvanize them about your approach with explanatory material.
web: acco.io email: anthony[@]sequinstream.com