Markus Junginger

Find a GitBook successor · Issue #7 · objectbox/objectbox-docs We have 5 doc sites and custom domains, which is not compatible with the new GitBook pricing. GitBook had its quirks, often had some bugs and is not the fastest. So the new pricing seems the final ...

github.com/objectbox/ob...

A unforeseen advantage of using AI agents is that now I have plenty of time to close unused browser tabs while waiting for results. 👍

Has the VSCode C/C++ Extension been blocked? · Issue #2976 · getcursor/cursor While coding just now I got this msg: The C/C++ extension may be used only with Microsoft Visual Studio, Visual Studio for Mac, Visual Studio Code, Azure DevOps, Team Foundation Server, and success...

Looks like Microsoft is starting to pull its extensions from AI editors like Cursor and Windsurf?
github.com/getcursor/cu...

Daniel Lockyer on X: "Meta recently made a 1 character change to their codebase which saves the equivalent of ~15,000 servers in capacity per year 🤯 https://t.co/pGZ1JjCwLc" / X Meta recently made a 1 character change to their codebase which saves the equivalent of ~15,000 servers in capacity per year 🤯 https://t.co/pGZ1JjCwLc

🤕 Typical C++ performance pitfall:
by-value instead of reference. 🤷 #cpp

x.com/DanielLockye...

Java is the best way to develop C++!
Latest evidence: NullPointerException 😁

Super-interesting move: instead of GPUs with lots of RAM, NVIDIA announces a mini computer concept with 128 GB unified RAM able to run 200b models.
nvidianews.nvidia.com/news/nvidia-...

Wasn't Llama 3.0 extremely sensitive to quantization? Quality went down horribly iirc. Ollama defaults not to the best quality. Check against fp16.

Yeah, checked my notes: cosine runs around 55% slower than dot product. Not so much difference between Euclidean and dot product though on x86. However on my ARM device, Euclidean was ~ 30% slower than dot product. Fun stuff...

So your intention to rule out Euclidean completely? Some datasets require it... Otherwise, sure, for cosine / dot product, the only drawback will be loosing a bit of precision. Not sure if users would expect to get back the same values they stored in your use case.

Is this a special use case? For non-normalized you cannot know the maximum values and thus you can only normalize per vector. This makes distance functions other than cosine more expensive as these need to be de-normalized. Which piece am I missing?

Rollback? Cancel? 😰

Tomorrow, I'm giving a AI presentation and this is my favorite slide. For fun, I asked ChatGPT and Claude if they get the reference of the third picture. ChatGPT was quite off, Claude got close. But without the audio track, it may be hard for humans too, I suppose...

🤯 indeed

I really like the polygon bear - is it hand made?

Just for fun, I ran it on a 16 core CPU... Haha. 😄

I really like that @jetbrains.com now allows to integrate local AI. Now, I just need the hardware for it... 🙃

Does this work on a Raspberry Pi 5? Would be an interesting addition to our CI runners...
www.microsoft.com/en-us/softwa...

Uh, it's like the first time I rolled back an IntelliJ update. #java
www.reddit.com/r/java/comme...