The ACM Recommender Systems conference is one of the leading venues in the field. You might check out what papers were accepted for the 2024 and 2025 conferences:
Readit Newsibgeek commented on Ask HN: What are the recommender systems papers from 2024-2025? · Posted by u/haensi
This seems like a great way to group semantically-related statements, reduce variable leakage, and reduce the potential to silently introduce additional dependencies on variables. Seems lighter weight (especially from a cognitive load perspective) than lambdas. Appropriate for when there is a single user of the block -- avoids polluting the namespace with additional functions. Can be easily turned into a separate function once there are multiple users.
ibgeek commented on The universal weight subspace hypothesis arxiv.org/abs/2512.05117... · Posted by u/lukeplato
They are analyzing models trained on classification tasks. At the end of the day, classification is about (a) engineering features that separate the classes and (b) finding a way to represent the boundary. It's not surprising to me that they would find these models can be described using a small number of dimensions and that they would observe similar structure across classification problems. The number of dimensions needed is basically a function of the number of classes. Embeddings in 1 dimension can linearly separate 2 classes, 2 dimensions can linearly separate 4 classes, 3 dimensions can linearly separate 8 classes, etc.
ibgeek commented on MinIO is now in maintenance-mode github.com/minio/minio/co... · Posted by u/hajtom
Time to fork and bring back removed features. :). An advantage of it being AGPL licensed.
It looks like they have modern options that run Linux now; it’s no longer the realm of 8-bit Atmel MCUs.
I’m not sure what the value proposition is overall, though. The IDE, perhaps? I never particularly saw the draw, but it clearly met the needs of some real market niche.
Maybe two different things here: SBCs that run Linux versus microcontrollers (MCUs).
MCUs are lower power, have less overhead, and can perform hard real-time tasks. Most of what Arduino focuses on are MCUs. The equivalent is the Raspberry Pi Pico.
In my experience, the key thing is the library ecosystem for the C++ runtime environment. There are a large number of Arduino and third-party high-level libraries provided through their package management system that make it really easy to use sensors and other hardware without needing to write intermediate level code that uses SPI or I2C. And it all integrates and works together. The Pico C/C++ SDK is lower level and doesn’t have a good library / package management story, so you have to read vendor data sheets to figure out how to communicate with hardware and then write your own libraries.
It’s much more common for less experienced users to use MicroPython. It has a package management and library ecosystem. But it’s also harder to write anything of any complexity that fits within the small RAM available without calling gc.collect() in every other line.
ibgeek commented on Feature Extraction with KNN davpinto.github.io/fastkn... · Posted by u/RicoElectrico
I'm not sure if I'm understanding correctly, but it reminds me of the kernel trick. The distances between the training samples and a target sample are computed, the distances are scaled through a kernel function, and the scaled distances are used as features.
ibgeek commented on Show HN: DBOS Java – Postgres-Backed Durable Workflows github.com/dbos-inc/dbos-... · Posted by u/KraftyOne
I really wish you guys would change the name since the product has moved so far away from the goals and concepts in the original publication. :). I love the product and what you are doing -- it's definitely needed and valuable.
ibgeek commented on Bcachefs Goes to "Externally Maintained" lwn.net/Articles/1035736/... · Posted by u/ksec
The sad part, that despite the years of the development BTRS never reached the parity with ZFS. And yesterday's news "Josef Bacik who is a long-time Btrfs developer and active co-maintainer alongside David Sterba is leaving Meta. Additionally, he's also stepping back from Linux kernel development as his primary job." see https://www.phoronix.com/news/Josef-Bacik-Leaves-Meta
There is no 'modern' ZFS-like fs in Linux nowadays.
This isn’t BTRFS
ibgeek commented on Ask HN: What are the biggest PITAs about managing VMs and containers? · Posted by u/ohjeez
Systemd, k8s, Helm, and Terraform model service dependencies.
Quadlet is the podman recommended way to do podman with systemd instead of k8s.
Podman supports kubes of containers and pods of containers;
man podman-container
man podman-generate-kube
man podman-kube
man podman-pod
Podman Desktop can create a local k8s (kubernetes) cluster with any of kind, minikube, or openshift local. k3d and rancher also support creating one-node k8s clusters with minimal RAM requirements for cluster services.
kubectl is the utility for interacting with k8s clusters.
k8s Ingress API configures DNS and Load Balancing (and SSL certs) for the configured pods of containers.
E.g. Traefik and Caddy can also configure the load balancer web server(s) and request or generate certs given access to a docker socket to read the labels on the running containers to determine which DNS domains point to which containers.
Container labels can be specified in the Dockerfile/Containerfile, and/or a docker-compose.yml/compose.yml, and/or in k8s yaml.
Compose supports specifying a number of servers; `docker compose up web=3`.
Terraform makes consistent.
Compose does not support rolling or red/green deployment strategies. Does compose support HA high-availability deployments? If not, justify investing in a compose yaml based setup instead of k8s yaml.
Quadlet is the way to do podman containers without k8s; with just systemd for now.
Thanks! I’ll take a look at quadlet.
I find that I tend to package one-off tasks as containers as well. For example, create database tables and users. Compose supports these sort of things. Ansible actually makes it easy to use and block on container tasks that you don’t detach.
I’m not interested in running kubernetes, even locally.
But by including the GC/runtime it went into a category with C# and Java which are much better options if you're fine with shipping a runtime and GC. Eventually Go showed up to crowd out this space even further.
Meanwhile in the C/C++ replacement camp there was nothing credible until Rust showed up, and nowadays I think Zig is what D wanted to be with more momentum behind it.
Still kind of salty about the directions they took because we could have had a viable C++ alternative way earlier - I remember getting excited about the language a lifetime ago :D
1. Very load overhead calling of native libraries. Wrapping native libraries from Java using JNI requires quite a bit of complex code, configuring the build system, and the overhead of the calls. So, most projects only use libraries written in a JVM-language -- the integration is not nearly as widespread as seen in the Python world. The Foreign Function and Memory (FFM) API is supposed to make this a lot easier and faster. We'll see if projects start to integrate native libraries more frequently. My understanding is that foreign function calls in Go are also expensive.
2. Doesn't require a VM. Java and C# require a VM. D (like Go) generate native binaries.
As such, D is a really great choice when you need to write glue code around native libraries. D makes it easy, the calls are low overhead, and there isn't much need for data marshaling and un-marshaling because the data type representations are consistent. D has lower cognitive overhead, more guardrails (which are useful when quickly prototyping code), and a faster / more convenient compile-debug loop, especially wrt to C++ templates versus D generics.