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boristsr

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Notes on DeepSeek 1 month ago

It's absolutely mind boggling to see claims of model distillation being theft, a class of attack, and all sorts of claims all the while Meta is in court for copyright violation, anthropic has had to settle a case with authors. With distillation "attacks" at least they paid API fees.

I think it depends on the depth of the summary, and the purpose. You can do quite an indepth analysis as part of educational material for example, which is one of the tests of fair use.

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Leaking spoilers of unpublished works can definitely cause market harm, and serves no wider good for the market the same way educational material would.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.

I understand your thoughts. I've had similar motivation problems about blogging since the release of ChatGPT. Feels like you are writing for a machine rather than readers. Definitely seen a decline in readers since December 2023 on older articles that previously had steady traffic for years.

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!

Excellent deep dive and explanation of the process of tracking down and fixing it. Thanks for sharing it, it was a fun read. Will definitely keep this in mind next time I fire up farcry for some nostalgia!

Nanite is a lot more than just a continuous lod system. The challenges they needed to solve were above and beyond that. Continuous lod systems have been used for literal decades in things like terrain. The challenges for continuous lod for general static meshes are around silhouette preservation, UV preservation and so on. One of nanites insights was that a lot of the issues around trying to solve automatic mesh decimation without major mesh deformation/poor results just disappear when you are dealing with triangles that are just a few pixels (as little as single pixel triangles) in size. The problem with small triangles is a problem called quad overdraw, where graphics cards rasterize triangles in blocks of 2x2 pixels, so you end up over drawing pixels many times over which is very wasteful. So the solutions they came up with in particular were:

- 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.

Nanite does a few things:

- 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.

I've been working on an automatic sky tracking telescope over the past few months. I'm a few weeks behind on blogging but making solid progress. V1 is nearing completion. Then I want to rework some of the electronics to design and get a custom PCB printed. Also the physical design needs a complete redesign to make it more sturdy for long exposures and solve some wiring pains.

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...

I'm not sure how that's entirely relevant. Success of another platform doesn't imply failure of another platform. It's also relatively common for different regions of the world to settle into different social media networks and messaging systems. See: Whatsapp vs iMessage, VKontakte, WeChat, telegram and so on.

There's plenty of metrics to support the fact that Threads is a successful launch.

It's actually wildly successful and most companies would kill to have a social media platform with that level of success.

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.

I'd personally be worried publishing this due to potentially also being classified as gaining unauthorized access to a computer system. It may temporarily be a publically accessible and poorly secured API, but that doesn't mean it's intended for public consumption when you have poked around the app to work out the API and then bypassing payment mechanisms.

According the Lady Ada from Adafruit relatively few will run into it, but if you are affected it can be worked around by adding an extra resistor for the affected pins into your circuit.

So it seems it's an annoyance rather than a killer. A revised chip would be nice though.

Good article! When I was first learning to produce some tutorials I knew sound was an important aspect but it was quite a lot to learn. This level of depth was good. I especially struggled with the advice of "just use your ears".

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!

The used market is really good now from a buyers perspective. I'm working on a few projects and wanted a few extra pi's. Managed to grab a few used ones from people that have sidelined their projects. Good condition. Basically paid retail price but also got 7inch touch screens with each pi for free.

The sheer logistics of a large scale mobilization means that its obvious weeks and even months in advance. Moving troops, equipment and ammunition to staging areas etc. Even just preparing transports shows up.

Think back to the weeks before the Ukrainian invasion. It's kinda hard to hide it.

I've been hearing peak oil is happening "next year" for at least 20 years. There's plenty of reasons to clean up our energy supply, but this is the weakest of all the reasons.

Reminds me of my experience learning microcontrollers last year. You strip away many of the layers of abstraction and remember just how fast computers truly are and how much work they can do every second.

This is still my go-to math book for game dev. Excellent writing style.

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.

I think this comment misses just how big of a leap chrome was over the competition for at least 5 years. The speed and stability improvements were light-years ahead. It was finally able to break the IE6 stranglehold and quickly overtook Firefox's adoption rate.

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.

I'm definitely the opposite, however I definitely use version control differently and less rigidly in personal projects. I commit more, care less about making the "perfect" commit, and making one change per commit. It's a lot more freeform in my personal projects precisely so it doesn't get in the way and take the fun out of the project.