308 karma · joined November 18, 2019
I think a key thing to remember when assessing your own liability is fair use is a defense, not an automatic guaranteed right for blanket uses.
Leaking spoilers of unpublished works can definitely cause market harm, and serves no wider good for the market the same way educational material would.
I wouldn't like to be on the receiving side of this lawsuit. At the very least it's going to be expensive to defend against.
https://apnews.com/article/anthropic-copyright-authors-settl...
Also, I just purchased LazyVim For Ambitious Developers. I've used the online edition a number of times in recent months. Thanks for your work!
- switch to software rasterization for small triangles. This required a good heuristic to choose between whether to follow the hardware or software path for rasterization. It also needed newer shader stages that are earlier in the geometry pipeline. These are hardware features that came with shader models 5&6.
- using deferred materials which drastically improves their ability to do batched rendering.
It's actually the result of decades of hardware, software and research advancements.
The 2 solutions posted in recent days seem heavily focused on just the continuous lod without the rest of the nanite system as a whole.
Also yes, there were also challenges around the sheer amount of memory for such dense meshes and their patches. The latest nvme streaming tech makes that a little easier, along with quantizing the vertices which can dramatically lower memory usage at the expense of some vertex position precision.
- continuous lod as this library does
- software rasterization for small single pixel triangles which reduces quad overdraw
- deferred materials (only material IDs and some geometry properties are written in the geometry pass to the gbuffers, which things like normal maps, base colour, roughness maps, etc being applied later with a single draw call per material)
- efficient instancing and batching of meshes and their mesh patches to allow arrows of objects to scale well as object count grows
- (edit, added later as I forgot) various streaming and compression techniques to efficiently stream/load at runtime and reduce runtime memory usage and bandwidth like vertex quantization etc.
https://mspoweruser.com/google-claims-edge-slowing-empty-div...
These claims aren't isolated. I think it's a bad look for Google to repeatedly make mistakes when they are currently under multiple investigations for monopolistic behavior.
The software allows the platform to automatically align to north and working on accounting for imperfect leveling (such as placing it on a slanted surface) through software and accelerometers.
Next challenges I want to solve in software is focus detection and then automatic image stack and post processing.
Primary goals of the project is a deep dive into robotics and electronics, along with brushing up on webdev which I don't touch too frequently being in the gamedev world. Also allowing me to explore things like digital signal processing.
I'm keeping a bit of a running blog here. [0]
[0] https://gdcorner.notion.site/Stargaze-Telescope-Build-Log-6f...
There's plenty of metrics to support the fact that Threads is a successful launch.
On the play store it's #2 in the charts ahead of ChatGPT, behind Temu.
Perhaps you need to rethink your definition of success and failure. It's objectively a successful platform launch.
So it seems it's an annoyance rather than a killer. A revised chip would be nice though.
I also heard the advice of "point the microphone at the source, not the source at the microphone", so you kind of speak at a 45 degree past the microphone which definitely helped with pops.
If you ever get around to another one, would love a similar level of guide into a subtle EQ tune to improve sibilance etc.
Great work!
https://www.infoworld.com/article/2338862/python-moves-to-re...
I don't see how it's a valid defence at all.
Think back to the weeks before the Ukrainian invasion. It's kinda hard to hide it.
I'd also advise it for anyone getting into ML or LLMs, the intuition it can help you build up around the linear algebra stuff like vectors and matrices is very helpful for understanding what's going on in ML.
And good call on NileRed and NileBlue. Great channels to see more chemistry than you should!
After that it's just inertia, it's the head of the pack because it's the head of the pack and people already use it.
To convince people to change generally you can't just offer the same or similar performance and features, it has to be a worthwhile reward for the user to bother. This change which just might be crippling enough for adblockers may be enough to get people to switch.