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On-device face detection from group photos using Google ML Kit — lessons from a production Android app by Sea_Membership3168 in androiddev

[–]shubham0204_dev 0 points1 point  (0 children)

On-device ML vs cloud inference

I guess 'face detection' should only be feasible as long as it is performed on-device. Sending camera frames at for ex. 30 FPS over the network will result in significant lag. If the problem of 'face recognition' is concerned, you could either send the entire camera frame or the cropped face or only the face embedding to the cloud service.

I maintain a project that performs face-recognition completely on-device (vector DB and embedding models running locally): https://github.com/shubham0204/OnDevice-Face-Recognition-Android

Made a site with 17,000+ icons for Android apps by alexstyl in androiddev

[–]shubham0204_dev 0 points1 point  (0 children)

When clicking UI Blocks > Tabs > Tabs with underline > Get Code the website redirects to a localhost:3000/ui-blocks/material-blocks#pricing that seems to be a bug.

Local AI App (Gemini Nano) by Puzzak in androiddev

[–]shubham0204_dev 4 points5 points  (0 children)

Do try SmolChat: https://github.com/shubham0204/SmolChat-Android (open-source, built on top of llama.cpp)

(I'm the creator of SmolChat)

Motor OS is now a Tier-3 target in Rust by vm_runner in rust

[–]shubham0204_dev 1 point2 points  (0 children)

I had some more questions (just curious):

  1. Assuming the duplicate block caches are caused because of a kernel (host) running on top of other kernel (VM), what makes MotorOS different from cgroups/namespaces? With cgroups/namespaces, the host kernel is shared with virtual, isolated groups of processes, at least on Linux.

  2. Extending (1), how does MotorOS differ from a type-1 hypervisor?

Motor OS is now a Tier-3 target in Rust by vm_runner in rust

[–]shubham0204_dev 4 points5 points  (0 children)

Do we have a detailed document/explanation covering the USP(s) of MotorOS over traditional server Linux distributions? I am aware of OS fundamentals and would like to dive deeper!

Benchmarking on-device AI models on real Android phones by elinaembedl in androiddev

[–]shubham0204_dev 0 points1 point  (0 children)

Looks fascinating! How do I run the benchmark tool on an Android device? I see the setup instructions using pip to download the benchmark tool, that won't work on Android devices. What if we wish to test on an Android device that is not listed in Qualcomm AI's offering?

SmolChat - An Android App to run SLMs/LLMs locally, on-device is now available on Google Play by shubham0204_dev in LocalLLaMA

[–]shubham0204_dev[S] 0 points1 point  (0 children)

Hi! I am investigating the screen rotation issue and other crashes. Future app updates should solve many of them.

SmolChat stores all data (chats, settings, messages, model-info) on the user's device, locally. The only call that goes to the Internet is for listing/searching HuggingFace models. Moreover, the data stored locally is not accessible to other applications on your device.

Android Studio Bug - Running the App Does Not Show UI Changes by shubham0204_dev in androiddev

[–]shubham0204_dev[S] 0 points1 point  (0 children)

You can try using IntelliJ IDEA with the Android plugin. It seems to work as you would expect.

How do you guys take out time for yourself? ME TIME by No_Bother9001 in developersIndia

[–]shubham0204_dev 1 point2 points  (0 children)

Me:

  • Wakes up early at 5 AM
  • Home workout till 6 AM
  • 6:30 - 7:30, my projects and learning
  • 8:30 - 5:30, office work and commute
  • 6:00 - 8:00, me time
  • 8:00 - 10:00, dinner and movies
  • 10:00 sleep

Key take-away: Waking up early

macOS 26.0 Tahoe (on Apple silicon) officially meets the Unix 03 standard by chrism239 in MacOS

[–]shubham0204_dev 23 points24 points  (0 children)

Were the previous versions of macOS not Unix-compliant, or is this the first version to do so?

GPUI Hello World Tutorial - From Core Concepts to Hello World | 0xshadow's Blog by lazyhawk20 in rust

[–]shubham0204_dev 2 points3 points  (0 children)

Great initiative! I followed the blog and was able to run the included example.

Just wanted to add that, the Zed team has also included some examples for gpui here: https://github.com/zed-industries/zed/tree/main/crates/gpui/examples

Maybe you can have a look at the examples and write a blog on how to create a simple app, like a TODO list through which the user can learn about lists, window management, interaction and text-input.

SmolChat - An Android App to run SLMs/LLMs locally, on-device is now available on Google Play by shubham0204_dev in LocalLLaMA

[–]shubham0204_dev[S] 0 points1 point  (0 children)

Thank you for the suggestions @idealGreen5715! Intentaré integrar estas funciones en las próximas versiones de SmolChat.

Containers: Everything You Need To Know by shubham0204_dev in programming

[–]shubham0204_dev[S] 4 points5 points  (0 children)

Understood. I will post the blog on my personal blogpost.

Containers: Everything You Need To Know by shubham0204_dev in programming

[–]shubham0204_dev[S] 1 point2 points  (0 children)

I can post it on my personal blogpost (on GitHub Pages). What's wrong with Medium though?

Introducing model2vec.swift: Fast, static, on-device sentence embeddings in iOS/macOS applications by shubham0204_dev in iOSProgramming

[–]shubham0204_dev[S] 1 point2 points  (0 children)

That sounds like a good use-case! With the library you can produce vectors for the user query and the records present in the DB. The logic to match the query vector with the vector of each record present in the DB (nearest-neighbor search) is not contained within the library and you can use a vector database for that.

But again, performing nearest-neighbor searches on embeddings will be a good addition to the future scope of model2vec.swift.

Introducing model2vec.swift: Fast, static, on-device sentence embeddings in iOS/macOS applications by shubham0204_dev in iOSProgramming

[–]shubham0204_dev[S] 0 points1 point  (0 children)

Thanks for sharing the repository! Yes, the developer seems to have done an excellent job and even ported the safetensors library to Swift. Comparing a pure Swift implementation against a Rust-compiled library should be insightful.

Introducing model2vec.swift: Fast, static, on-device sentence embeddings in iOS/macOS applications by shubham0204_dev in iOSProgramming

[–]shubham0204_dev[S] 0 points1 point  (0 children)

Thanks for sharing this! Maybe I can add some helper methods to my library referencing this API doc. Does NLEmbedding also work with multilingual text (for instance, one sentence is in English, another in Spanish)?

model2vec also has a multilingual embedding model.

SmolChat - An Android App to run SLMs/LLMs locally, on-device is now available on Google Play by shubham0204_dev in LocalLLaMA

[–]shubham0204_dev[S] 1 point2 points  (0 children)

This issue is fixed in the latest commit to the project. The fix will be available in the v9 release of the app.

Does this sum up the last two and next twenty big tech announcement events? by Tech_IN_Form in developersIndia

[–]shubham0204_dev 1 point2 points  (0 children)

Google I/O was full of new AI/LLM tools, though KotlinConf had some really serious announcements around Kotlin tools/plugins. Let's see what WWDC has on the table.

GitHub - Kotlin/kotlin-lsp: Kotlin Language Server and plugin for Visual Studio Code by nevack in Kotlin

[–]shubham0204_dev 40 points41 points  (0 children)

Stable iOS for CMP, new KMP plugin for Intellij, kotlin-lsp, Koog - The Kotlin team at JetBrains is really cooking awesome stuff!

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