462 karma · joined March 1, 2014
I'm curious how much the recent AI 3D modeling trend (Astra post-trained to use Blender) would have impacted this.
World Labs' entire tech stack becomes potentially obsolete when anyone can prompt GPT/Claude to create a simulation-ready 3D model from a photograph.
So it's easier to just release those models as open source and make it official, since someone would inevitably hack the weights out anyway.
Looking more closely though, this looks a lot like the Google "AI Cookie" from 2017, which also used Bayesian Optimization: https://blog.google/innovation-and-ai/technology/research/ma...
https://github.com/ARPAHLS/skillware/blob/main/skills/optimi...
We had access to all of the symbolic algebra tools and were even expected to use them regularly for both courses. It was great!
I'm not sure how well this would extend to introductory courses though, especially if the standardized tests still expect integration by hand.
* Expected errors - Checked Exceptions
* Unexpected errors - Unchecked Exceptions
Idiomatic Java also makes heavy use of asserts, e.g. using the Guava Preconditions library.
We've seen time and again that various trends in ML turn out to have actually been dead-ends.
A few examples: https://arxiv.org/abs/2102.06356 https://arxiv.org/abs/1905.03678
That said, I've also seen plenty of competitive drama in FAANG research labs, so this story is not hard to believe. More senior engineers often will use their seniority to power-grab control of projects. It sounds like Google execs did the right thing in the end.
The key idea is to break code into "chunks" that each do one thing.
Then, if you have to add a new feature, it goes into another chunk, instead of editing/modifying existing code.
The same logic applies to system design at different scales, whether fine-scale OOP or coarser-scale (micro)service architecture. The ideal size of an individual "chunk" is somewhat subjective & debatable, of course.
It's like Haskell-style immutable data structures, but applied to writing the code, itself.
The same criticisms for microservices (claims that it adds complexity, or too many pieces) are also seen for OOP.
Curiously, while folks sometimes complain about breaking up a system into smaller microservices or smaller classes, nobody every complains about being asked to break up an essay into paragraphs.
This talk gives a great overview of why boolean flags (rather, if-statements) can be a code smell: https://www.youtube.com/watch?v=4F72VULWFvc
OP's blogpost advocates for data-oriented design (e.g. Entity Component Systems) as a mechanism for avoiding this, whereas the talk I've linked advocates for OOP. Both mechanisms are equally valid (imho) and are inline with widely-adopted industry practices for software architecture.
There happens to be a Wikipedia page on "Midpoint circle algorithm": https://en.wikipedia.org/wiki/Midpoint_circle_algorithm
The page claims, "Bresenham's circle algorithm is derived from the midpoint circle algorithm."
The author of this blog post even made it clear, at the end of their article, that... "many explanations of midpoint algorithm use the final, optimized version. But I added several unoptimized steps."
I think there's a lot of value in a blogpost that demonstrates how someone could re-derive a widely-used algorithm from scratch.
If this happens, you've already lost. Software development has long lead-times. By the time there is significant customer attrition, bending the curve will be immensely difficult.
Good engineering strategy requires over-reacting to the right signals, and trends in the broader ecosystem are a wonderful source of signals. Large tech companies know this, and there's a reason why they'll quickly throw billion-dollar budgets behind exploratory efforts in response to competitors.
That said, it certainly depends on the industry. Some sectors are more fast-paced and competitive than others.
Probably explains why the "Open date" & "Final date" are just 30 days apart.
So, apparently it can work. I don't don't how much Google's internal Module incarnation differs (if at all) from what was ultimately published in the standard, but I'd expect it to be similar.
The article discusses a problem of resolving dependencies between compiling different c++ files. I'm no expert, but I think this dependency graph is implicitly baked into the build system, with tool-assisted user-written bazel rules.
In 3D, the same can be done with morton codes (or a 3D hilbert curve) to build an implicit octree. Some raytracing systems use this for fast BVH construction.
In either case, this approach differs from mipmaps in that the underlying data can be sparse, and is simply stored in a sorted array.
They've also already been building their own network chips for some time. So, given the scale of their datacenters, I think it's entirely reasonable that they'd outpace nvidia.
They're not perfect, but I also made the switch from vim to CLion and never looked back. With a half-decent plugin for editing text, there's not much value in using a more minimalist vim setup IMHO.
https://arstechnica.com/gadgets/2019/07/facetime-feature-in-...
Singletons can be declared once, and then provided to various systems that need it, with read-only access.
In fact, they're more flexible than that: one can declare multiple nested "scopes" that each have their own initialization phase. For example, a web server could have one scope for process-wide singletons, and another for request-scoped "singletons".
The only thing missing is that these DI systems are for java, which doesn't have the const-correctness you'd ideally want. I'm not aware of any equivalent (and widely-used) systems for languages like c++ or Rust.
(Yes, I can feel hundreds of HN readers rolling their eyes as they read this, given the bad rep. DI systems have, but they're widely popular among FANG companies for a reason.)
Take a few advanced, specialized CS classes by your 3rd year. These often have large end-of-semester projects that can be fairly open ended.
These final projects are a great way differentiate yourself from the thousands of other CS grads looking for jobs.
Sure, you could get an 'A' in class by doing the bare minimum for a project. Alternatively, you could go beyond course requirements and have something to show off for potential employers, even if just another resume item to use as a conversation-starter. If you're doing the project anyway, going an extra 10% over the top is relatively easy, especially compared to trying to land a meaningful contribution to an open-source project or building a separate portfolio project from scratch.
Etsy can also be quite fast.