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Axelera Team
SpannerAxelera Team
posted in The Axelera Forum
👋 Say Hello – Introduce Yourself to the Axelera AI Community

Welcome to the Axelera AI Community – we’re so glad you’re here.This is a space for everyone from hardware engineers and AI devs to makers, enthusiasts, onlookers and partners, so don’t be shy. Whether you’re working with AI every day or just getting started, we’d love to know more about you.To get things going, let’s have a big round of hellos:Who you are and what you’re working on Your experience or interest in the AI/edge AI world What you’re hoping to learn, share or achieve in this communityCan’t wait to get to know you all, and to build something great together.Now – who’s going first? 👇

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Cadet
Steven Hunsche
Axelera Team
Steven HunscheAxelera Team
published in LLMs, NLP, Neural Networks
Llama 3.2B Chatbot Demo on Metis® - Fully Offline

I just built a quick demo showing the Llama 3.2B chatbot running on our Metis® platform, totally offline. This model packs 3 billion parameters and runs smoothly on both a standard Lenovo P360 with our PCIe card and even on an Arduino-based dev board (Portenta X8).We hit 6+ tokens/sec with a single core – which means real-time chat. Perfect for smart customer support bot, digital concierge systems, any edge AI assistant application really, all running fully on-device. No cloud needed.Check out the video and let me know what you think. Any projects you can think of where you could use a self-contained, power-efficient, offline AI chatbot like this?

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lorenzo.lamberti
Cadet
shashi.chilappagari
Ensign
shashi.chilappagariEnsign
posted in The Axelera Forum
DeGirum PySDK 0.18.0 with support for Axelera Runtime 1.3.3

We are happy to announce the release of our latest PySDK (version 0.18.0) that supports Axelera runtime 1.3.3. See our docs: Overview | DeGirum Docs for more details. Examples and user guides coming soon.

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shashi.chilappagari
Ensign
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Axelera Team
SpannerAxelera Team
posted in The Axelera Forum
Orange Pi 6 Plus on the horizon?

I suppose it’s inevitable that there’ll always be a new model in the works, but hushed conversations about the Orange Pi 6 Plus are starting to surface…Considering how well the Orange Pi 5 Plus has (rather unexpectedly) performed in low-cost edge AI applications, it’s hard not to feel some small pang of excitement around the next version!https://www.reddit.com/r/OrangePI/comments/1mbd5zc/the_upcoming_orangepi_6_plus/We need to put one in the hands of ​@Victor Labian and ​@Steven Hunsche! 

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Axelera Team
shashi.chilappagari
Ensign
shashi.chilappagariEnsign
posted in The Axelera Forum
Axelera is Now Live on DeGirum AI Hub

We're excited to announce that Axelera is now integrated with DeGirum AI Hub—a platform that lets you run edge AI models directly in your browser without any setup or installations.🔍 What You Can DoExplore a wide range of ready-to-use AI models for real-time inference across various use cases: 🧑 Face Detection – detect and track faces in video streams ✋ Hand Detection – enable gesture recognition and interaction 🔥 Fire and Smoke Detection – build early warning systems 🚘 License Plate Detection – power smart parking and traffic analytics 🚗 Car Detection – monitor traffic flow, parking spaces, and more All of these can now be tested instantly using Axelera hardware, straight from your browser.🖥 Try it NowGo to DeGirum AI Hub, select an Axelera-powered model, and start experimenting! Whether you're building a smart city application or an AI-based industrial monitor, AI Hub with Axelera makes prototyping frictionless.

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shashi.chilappagari
Ensign
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Cadet
Bill.EichenCadet
asked in The Axelera Forum
Hello

Hi Axelera inferences and compiler available https://hub.degirum.com

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Axelera Team
Steven Hunsche
Axelera Team
Steven HunscheAxelera Team
posted in The Axelera Forum
Running Edge AI on Orange Pi 5 Plus with Metis

I've put together a quick walkthrough of how to set up the Voyager SDK with a Metis M.2 card on the Orange Pi 5 Plus, and wanted to share the full process with you all. This has turned out to be a fantastic low-cost dev setup to start experimenting with edge AI using our Metis platform.Here’s what we cover:Installing the Metis M.2 card Setting up the Orange Pi with the proper OS image Installing the Voyager SDK (using SSH, so you can do it headless) Running a Yolov8L demo with live inferenceEverything is done using standard tools like Balena Etcher, SSH, and a few terminal commands. Whether you’re building a prototype or just exploring Metis on embedded platforms, this setup is a great place to start on a device that's cheap, powerful, and very easy to use.Got questions or ran into snags? Let me know! These resources should help, too:📚 Setup guide reference: https://support.axelera.ai/hc/en-us/articles/27059519168146-Bring-up-Voyager-SDK-in-Orange-Pi-5-Plus📦 Source & SDK: https:/

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Axelera Team
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Axelera Team
SpannerAxelera Team
posted in The Axelera Forum
Code block colour change

Just FYI, I’ve been tinkering with the platform design a bit, as I always felt like the code block text input burned your retinas out, being such a big block of white against the dark theme 😆I’ve mimicked GitHub's colour pallette for it, but we can tweak it further if anyone has a preference. (Or if you spot anywhere that’s now messed up because of the CSS changes, let me know),As you were!

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Axelera Team
gurumeditation
Ensign
gurumeditationEnsign
posted in AI Trends and Innovations
AI agents raising money for charity

TechCrunch piece about a nonprofit that had GPT and Claude models run a fundraising op on their own—no human help except setup. The AIs picked a charity (Helen Keller Intl), made docs, set up socials, emailed people, and ended up raising $257 in a week!Can’t tell if this is good or bad...https://techcrunch.com/2025/04/08/a-nonprofit-is-using-ai-agents-to-raise-money-for-charity/ 

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Axelera Team
SpannerAxelera Team
asked in LLMs, NLP, Neural Networks
Which models are you using with Metis? Or want to use.

I’m interested in hearing from everyone here about which models you’re successfully using with your Metis device and Voyager SDK, and which ones you’d like to see being officially supported.This could be really useful info in terms of prioritisation when it comes to adding more support in the model zoo.

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Axelera Team
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Cadet
Sai_NikhilCadet
posted in The Axelera Forum
Export YOLOv8s Detections to JSON with Timestamps in Voyager SDK

I’m using Axelera’s Voyager SDK to run a YOLOv8s object-detection pipeline on video files, and I need to capture every detection into a JSON array for downstream processing. For each detected object, I want to record: frame_index: the zero-based frame number timestamp: the frame’s PTS in seconds bbox: [x1, y1, x2, y2] coordinates class_id: numeric COCO class index class_name: readable label (e.g. “person”) score: detection confidence What’s the cleanest way to hook into the Voyager inference loop, pull out the ObjectDetectionMeta (task name “detections”), convert its boxes, scores, class_ids, and labels into native Python types, attach the FrameResult.src_timestamp, and dump the results into a single JSON file? Example snippets or pointers to the relevant SDK APIs would be greatly appreciated.

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Axelera Team
S
Cadet
saitejajampulaCadet
asked in The Axelera Forum
Anyone Tried Running Axelera with ROS 2? Facing video_infer Output Issue

Hi Axelera Community,Has anyone here successfully run the Axelera Voyager SDK with ROS 2? I’m currently working on integrating the video_infer node with ROS 2 and would really appreciate hearing from anyone who has tried this setup.My Setup: Hardware: Aetina board SDK Version: voyager-sdk v1.2.5 ROS 2: Humble (on Ubuntu 22.04) Python: 3.10 (using a virtual environment) Model Used: yolov5s-v7-coco Inference Server:python3 inference_server.py yolov5s-v7-coco none --port 50051 --no-display ROS 2 Node:ros2 run axelera_infer video_infer What’s Working: The inference server starts successfully and shows: Server started, listening on 50051 INFO : Using device metis-0:1:0 The ROS2 node launches and shows: [INFO] [video_infer_node]: Starting video inference node... [INFO] [video_infer_node]: Sending inference request... [INFO] [video_infer_node]: StreamInfer started successfully No errors are thrown on either side. Problem: The stream only seems to run a few frames: Stream Playing

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Axelera Team
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Axelera Team
SpannerAxelera Team
posted in The Axelera Forum
Anyone else tried running AI on an Orange Pi 5 Plus?

Have you seen that ​@Victor Labian’s successfully brought up the Voyager SDK on the Orange Pi 5 Plus with a Metis M.2 module? It took a bit of work—Ubuntu flashing, driver rebuilds, and tweaking the PCIe device tree—but it’s running, and it’s fast. 😃This setup is seriously impressive for something so compact and affordable. Inference runs smoothly, and with some tuning, it could potentially be running advanced models like YOLOv8 without trouble.It’s just an experiment and a test at this point. No big plans around the Orange Pi, but it looks like a really promising start.If you’re experimenting with AI on SBCs—or thinking about it—I’d love to hear what you’re working on. Orange Pi, Raspberry Pi, custom boards, anything edge. 👍 

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Axelera Team
jonask-ai
Axelera Team
jonask-aiAxelera Team
posted in The Axelera Forum
🎥 Your First Inference on Metis with Voyager SDK: Step-by-Step Video Guide

Hey everyone,Excited to share a brand-new video I put together for anyone getting started with the Metis card and Voyager SDK. Whether you're setting up your eval kit or just curious about how inference works on Metis, this walkthrough is for you.🛠️ What’s inside:Setting up your environment and verifying camera input Running YOLOv5s-v7-COCO on a live camera stream Using download_prebuilt for faster setup Running inference on media files and datasets Benchmarking performance Measuring accuracy with mAP and more📺 You can find this tutorial, and more, on our YouTube ChannelThis guide is based on SDK version 1.2.5 and follows the official Quick Start Guide, but with some extra tips and tricks to get you up and running even faster.💬 Have you tried running inference on Metis yet?Drop your thoughts, questions, or your own setup experiences in the comments, I'd love to hear how it's going for you or help troubleshoot if you're stuck!See you there,Jonas 

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jonask-ai
Axelera Team
A
Anonymous
posted in The Axelera Forum
Which demos would best showcase the strengths of our product?

We frequently attend trade shows and aim to stand out from the competition. Showcasing compelling demos is a key strategy to achieve this. Which demos would most effectively highlight the unique strengths of our product?

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Cherryland120
Cadet
jonask-ai
Axelera Team
jonask-aiAxelera Team
published in The Axelera Forum
Getting Started with Voyager® SDK – A Quick IntroductionTutorial

Hi everyone,I’ve just published a quick walkthrough of the Voyager® SDK, our all-in-one platform for building and deploying AI applications at the edge. If you’re working on computer vision tasks or just curious about what makes Metis and Voyager such a powerful combo, this video is for you.In it, we’ll cover the basics:🔹 What Voyager SDK is and how it simplifies AI development🔹 How to use the Model Zoo or bring your own model🔹 Performance, quantization, pipelines, and real-time inference🔹 A peek at cascading models and what’s possible with our quad-core Metis AIPUWhether you’re building a demo, proof of concept, or production deployment, this will help you get started with confidence. Let me know what you think!Looking forward to seeing what you build with it!

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jonask-ai
Axelera Team
F
Ensign
floritEnsign
posted in LLMs, NLP, Neural Networks
Outsource the Learning process of an LLM from system to Metis

how let run a LLM learning process driven by system ram and cpu model outsource to metis device?or better say how to load 4,7GB into metis m.2 with 1GB

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F
Ensign
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Axelera Team
SpannerAxelera Team
posted in AI Trends and Innovations
Have you seen any projects combining CNC and AI?

About 40m of 2020 aluminium profile just arrived for the CNC machine I’m building! I suddenly feel like this might be a bigger job than I initially planned…Anyway, that’s for another day. What’s crossed my mind now is whether anyone’s seen any projects that combine CNC with vision AI? I’m thinking it’d be cool if I could combine the two, since I’m building one machine anyway.Predictive maintenance, maybe? Although this is a homemade machine, so that’s not a huge issue.Perhaps positioning and alignment could be something AI could get involved with? That could potentially be useful and reduce waste. Any other ideas of existing projects anyone’s seen in this area? 

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Axelera Team
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Cadet
Semih_Cadet
posted in The Axelera Forum
Legal Issues and Axelera

Hi everyone,I am Semih. I am a PhD researcher at University of Tuebingen on Open Source and AI. I am trying to understand Axelera’s hardware and in future I am planning to research legal and regulatory issues related to AI hardware, role of open source hardware, licensing contracts, regulatory compliance especially with Cyber Resilience Act, GDPR and AI Act. I was wondering if anyone is conducting a similar research or are there any pain points or interesting discussions under these themes?Thanks in advance

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Cadet
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Axelera Team
SpannerAxelera Team
asked in LLMs, NLP, Neural Networks
May the Source (Code) be With You!

May 4th is almost upon us, so naturally we’re thinking about AI… in space. More specifically: the AI and droid legends of the Star Wars universe.From multilingual protocol units to rogue assassin bots with surprising moral compasses, Star Wars has given us some of the most iconic (and occasionally chaotic) artificial intelligences in sci-fi.So here’s the question...

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Axelera Team
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Axelera Team
SpannerAxelera Team
posted in AI Trends and Innovations
What Real-Time 8K Inference Looks Like

Check out our own ​@jonask-ai showing real-time, high-precision 8K object detection demo at Embedded World. An Aetina box, four Metis cards, and a whole lot of tile-based inference.What’s cool is it runs YOLOv8l across 380 overlapping tiles per second—no downscaling—at just 57% compute. And it’s not a one-off: same setup anyone can build with Voyager SDK + a YAML file.Noice!You can find out a bit more about this in ​@Doug’s blog post, too.

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Axelera Team
S
Ensign
saravananEnsign
asked in The Axelera Forum
Deploying lane dection model (yolopv2.onnx) on metis M2

Hello,I am currently working on lane detection model (YOLOv2) which is in .pt format I have converted to ONNX format.Here are the terminal responses I have got..root@aetina:/voyager-sdk# cd YOLOPv2root@aetina:/voyager-sdk/YOLOPv2# lsLICENSE    data     demo2.py        models            runs   yolopv2-envREADME.md  demo.py  export-onnx.py  requirements.txt  utilsroot@aetina:/voyager-sdk/YOLOPv2# cd modelsroot@aetina:/voyager-sdk/YOLOPv2/models# ls__pycache__  common.py  experimental.py  yolopv2.onnx  yolopv2.ptroot@aetina:/voyager-sdk/YOLOPv2/models# I am having the ONNX format of the model so now I want to deploy the model onto Metis M2. When I am trying to compile the yolopv2.onnx model but i am encountering this issue.root@aetina:/voyager-sdk# /voyager-sdk/bin/voyager-compile models/yolopv2.onnx --output-dir build/yolopv2 --input-shape "1,3,640,640"bash: /voyager-sdk/bin/voyager-compile: No such file or directoryI request to guide me to successfully deploy the model.Note; I am using

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Ensign
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Axelera Team
SpannerAxelera Team
posted in LLMs, NLP, Neural Networks
Built-In AI or Subscription-Based?

This new survey suggests people (Apple fans, that is) are very open to the idea of paying a subscription for “Apple Intelligence” features. Which raises the question as to whether AI tools are going to become just another line on your monthly bill.We’ve moved quickly from “AI is cool” to “you might need it just to keep up.” And if it’s locked behind paywalls? That could become a problem once it’s a necessity rather than a nice-to-have.Curious what you all think – will AI be a must-have, or a paid perk for you?https://www.macrumors.com/2025/04/22/apple-intelligence-payment-survey/

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Axelera Team
Axelera CMX
Axelera Team
Axelera CMXAxelera Team
posted in The Axelera Forum
We have our first Ensigns! 🥇🥈🥉 Report to the bridge! 📯

This is a quick shoutout out to ​@ChinmayMulgund and ​@oguz for becoming the first members of Axelera AI’s community to earn the rank of Ensign! And practially at the same time (close enough that I can’t tell who got there first).Every activity on the community earns you points, and helps you climb the ranks. The opening rank is a Cadet, which you receive after your first action on the community. But it takes effort to climb the ranks, so a big congratulations to our first two Ensigns for getting there so quickly!Who’s going to be the first Lieutenant, I wonder? 

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Axelera CMX
Axelera Team
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Axelera Team
SpannerAxelera Team
posted in AI Trends and Innovations
Hugging Face is getting in on the robotics game

Gugging face just snapped up a humanoid robotics startup (Pollen Robotics, the folks behind Reachy 2). Open source robots are officially happening. Imagine a robot that serves coffee and critiques your model training while it’s doing it. I’d buy that!In all seriousness, it does actually feel like a big moment for open robotics.https://techcrunch.com/2025/04/14/hugging-face-buys-a-humanoid-robotics-startup/ 

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Axelera Team

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