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Hoi Lam

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The 4 steps of Android Machine Learningdroidcon EMEA 20202020-10-08
Covers concrete, runnable paths: start with the people + AI guidebook for design, use ML Kit for on‑device APIs or pair on‑device object detection with Cloud…
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Myths and Reality of Android Machine LearningDroidcon Vietnam 20192019-08-01
Argues that modern Android runs practical on‑device ML using NNAPI and ML Kit and shows live demos: object detection feeding product search, on‑device…
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What’s new in Android machine learningGoogle I/O 20192019-05-07
Android announces concrete on-device ML pieces: Android runs on 2.5 billion devices and exposes the Neural Networks API for GPU/DSP/NPU acceleration; measured…
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Best practices in using the Android EmulatorGoogle I/O 20192019-05-07
Android Emulator claims near-device speed (benchmarks show it slightly outperforms a Pixel 2 XL) by running x86 guests with CPU hypervisors (HAXM, Windows…
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Myths and Reality of Android Machine LearningAndroid Makers 20192019-04-23
Practical claims and demos dominate: a Pixel 3 runs live on-device inference for face contours while a Nexus 5X hits about five–ten fps; ML Kit delivers…
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Live Coding: Adding Machine Learning to Android Things in 10 Minsdroidcon Berlin 20182018-06-25
Live-codes Firebase ML Kit into an Android Things camera pipeline: capture bitmap, wrap as FirebaseVisionImage, call VisionLabelDetector with a 50% confidence…
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Bootstrapping Multiplatform Development and Android WearAndroid Makers 20182018-04-23
Starts with an Android Wear post‑Baselworld update that claims new APIs and power tweaks cut background wakeups and improve standby life, then shows concrete…
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Developing for Android Wear 2.0Android Makers 20172017-04-10
In this session, Hoi will explore the past, the present and the future of Android Wear. Come and find out the new developer features in Android Wear 2.0 and…
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