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#esp32 #homeassistant #voiceassistant #tensorflowlite #tensorflow

Optimizing neural networks using TensorFlow Lite, quantizing model weights, and deploying low-latency AI directly on mobile and embedded hardware. Galgotias University empowers developers to push intelligence to the edge! 📱🧠
#GalgotiasUniversity #EdgeAI #TensorFlowLite #MachineLearning

Run #MobileNetV3 on the Forlinx OKMX8MP-C (i.MX8M Plus)!
Using NXP’s eIQ Portal, we trained, quantized & deployed a handwritten digit recognition model with #TensorFlowLite — proving efficient #EdgeAI on industrial ARM platforms.
www.forlinx.net/industrial-n...

#ForlinxEmbedded #AIoT #NXP

16) So did they get 100 000 USD or "approximately $1.2 million"?
Probably a microcontroller that runs TensorFlowLite or similar planned for. DrOd!n uses TensorRT/ONNX/TFLite etc with some tweaks.

🆕 TFLite GPU Delegate Crashes on Jetson: XNNPACK Fix

#EdgeAI #TinyML #TensorFlowLite #Jetson
https://tildalice.io/tflite-gpu-delegate-jetson-xnnpack-fix/

🆕 TFLite Inference Fails on Android: 5 ONNX Mobile Fixes

#EdgeAI #TinyML #ONNXRuntime #TensorFlowLite
https://tildalice.io/tflite-inference-fails-android-onnx-mobile-fixes/

🆕 TFLite vs ONNX Mobile: 5 ARM Devices, 12ms Gap

#EdgeAI #TinyML #TensorFlowLite #ONNXRuntime
https://tildalice.io/tflite-vs-onnx-mobile-arm-inference-benchmark/

🆕 TensorFlow Lite vs PyTorch Mobile: Cortex-A Latency Test

#EdgeAI #TinyML #TensorFlowLite #PyTorchMobile
https://tildalice.io/tensorflow-lite-vs-pytorch-mobile-cortex-a-latency/

🆕 ONNX Runtime vs TFLite Android: 3x Speed Benchmark

#EdgeAI #TinyML #ONNXRuntime #TensorFlowLite
https://tildalice.io/onnx-runtime-vs-tflite-android-benchmark/

📢 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺 𝘂𝘀𝗲𝗿 𝗲𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 𝘄𝗶𝘁𝗵 𝗽𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝘃𝗲 𝗔𝗜: 𝘁𝗵𝗲 𝗳𝘂𝘁𝘂𝗿𝗲 𝗼𝗳 𝗺𝗼𝗯𝗶𝗹𝗲 𝗮𝗽𝗽𝘀 💫 🚀

• 𝗧𝗲𝗻𝘀𝗼𝗿𝗙𝗹𝗼𝘄 𝗟𝗶𝘁𝗲
• 𝗖𝗼𝗿𝗲 𝗠𝗟
• 𝗢𝗡𝗡𝗫 𝗥𝘂𝗻𝘁𝗶𝗺𝗲 𝗠𝗼𝗯𝗶𝗹𝗲
• 𝗙𝗶𝗿𝗲𝗯𝗮𝘀𝗲 𝗠𝗟 𝗞𝗶𝘁
• 𝗣𝘆𝗧𝗼𝗿𝗰𝗵 𝗠𝗼𝗯𝗶𝗹𝗲

mobivery.com/en/transform...

#IA #MachineLearning #AppsMóviles #TensorFlowLite #CoreML #ONNX #PyTorch #FirebaseMLKit #Android #iOS

そしてここにきてtensorflowLiteが活きるとは。雛形はできたがモデルのダウンロードは認証があるのでワンボタンでダウンロードとはいかない。とりあえず今日はここまでにしよう。しかし本当に端末だけで音楽が生成できるのだろうか。効果音モデルなんかも使えちゃったら幅が拡がりすぎて多くのアプリが全部ひっくり返るっていうか。端末だけで動くってのが次のトレンドのひとつになる、と思う。