35歲了,轉去谷歌做人工智慧靠譜嗎?
35歲了,轉去谷歌做人工智慧靠譜嗎?
原創: Cottbuser 灣區人工智慧 1周前
作者:Cottbuser 會多國語言的海歸
公眾號:灣區人工智慧
微博:灣區人工智慧
知乎:灣區人工智慧
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一線人工智慧工程師獨立兼職運營
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每個程式設計師都有一個谷歌夢,看看這位電工是如何逆襲,爭取谷歌的工作機會。
其實他的大學7年都是在研究電,只有博士才開始搞了5年計算機。人生浪費幾年,走點彎路,很正常,只要意識到錯了,及時修改路線都沒有問題。把時間拉長了,回頭看,修改路線的決定肯定是對的。不能一直在錯誤的電工專業浪費青春。
這個臺灣人牛逼之處在於能夠克服傳統思維的阻力,去實現心中的夢想,做自己想做的事情。主要成果就是兩個專利,幾篇論文。一個語義分割模型讓我認識了他。從我認識的幾十個臺灣人來看,他很臺灣。
博士畢業都35歲的樣子
碩士畢業兩年後才去讀博士
本科畢業兩年才去美國讀碩士
你工作兩年後還能拿起書本嗎?你結婚,生娃後還有勇氣繼續去全職讀書嗎?30歲了才打算改行去實現程式設計夢想(或者突然醒悟到這是網際網路的時代,碼農的天下,不會程式設計未來就是文盲),這個勇氣你有嗎?放棄一切,從零開始,你願意承擔相應的沉沒成本嗎?隨著潮流,跟著糊里糊塗結婚生子,你快樂嗎?你孩子快樂嗎?
此刻,我領悟到了一句話《你的心有多大,你擁有的世界就有多大》,開放的思想,衝破環境思維的束縛,敢於面對因為不合群而獲得周遭質疑的勇氣,高度自律的能力,和超強的執行力,是成為萬人景仰的大牛的基本功。
這位大牛35歲才去谷歌當程式設計師,國內喊著30歲就被企業拋棄了,確實不太合理。其實,不是大齡程式設計師被拋棄,是年齡和能力不匹配才會被拋棄。
大牛頭像,下面看簡歷吧
Liang-Chieh (Jay) Chen- Home Page
Liang-Chieh Chen臺灣人,香港人,他們是不會大陸的拼音的,看看他們名字的拼音,還有街道名稱,大學名稱,反正我看不懂 Email: lcchen at cs dot ucla dot edu |
About me我是誰
Since February 2016, I have been working at Google, Los Angeles.在谷歌工作
I finished my Ph.D. in Computer Science at UCLA under the supervision of Alan L. Yuille in November 2015.
My research interests include Computer Vision, Graphical Models, and Machine Learning.
News最新動態
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An implementation and checkpoint for the best Dense Prediction Cell trained on Cityscapes have been released, which attains 82.7% on the test set.
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DeepLabv3 checkpoints with MobileNet-v2 depth-multiplier=0.5 (pretrained on COCO and PASCAL VOC 2012) have been released, which targets at faster inference speed.
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DeepLabv3+ was featured on Computer Vision News.
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One paper (neural architecture search for dense image prediction) is accepted to NIPS 2018.
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Two papers (DeepLabv3+ and PersonLab) are accepted to ECCV 2018.
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Check out our latest work, PesonLab, on joint person instance segmentation and pose estimation.
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Google AI blog about DeepLabv3+ open source.
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Our DeepLabv3+ implementation in TensorFlow is publicly available now!
Education教育背景
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Ph.D., Computer Science, University of California- Los Angeles, September 2010 - November 2015美國加州大學洛杉磯分校博士,電腦科學專業
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M.S., Electrical Engineering: Systems, University of Michigan- Ann Arbor, September 2006 - June 2008美國密歇根大學安娜堡分校電氣工程專業
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Major: Signal Processing, Minor: Communication
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B.S., Electronics Engineering, National Chiao-Tung University, Taiwan, September 2000 - June 2004臺灣國立交通大學電子系本科(你能看出來是交通大學嗎)反正我是靠度娘才翻譯出來的
Papers論文
Searching for Efficient Multi-Scale Architectures for Dense Image Prediction |
PersonLab: Person Pose Estimation and Instance Segmentation with a Bottom-Up, Part-Based, Geometric Embedding Model |
Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation |
MobileNetV2: Inverted Residuals and Linear Bottlenecks |
MaskLab: Instance Segmentation by Refining Object Detection with Semantic and Direction Features |
The Devil is in the Decoder |
Rethinking Atrous Convolution for Semantic Image Segmentation |
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs |
Zoom Better to See Clearer: Human Part Segmentation with Auto Zoom Net |
Semantic Image Segmentation with Task-Specific Edge Detection Using CNNs and a Discriminatively Trained Domain Transform |
Attention to Scale: Scale-aware Semantic Image Segmentation |
ABC-CNN: An Attention Based Convolutional Neural Network for Visual Question Answering |
Weakly- and Semi-Supervised Learning of a Deep Convolutional Network for Semantic Image Segmentation |
Learning Deep Structured Models (oral) |
Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs |
Beat the MTurkers: Automatic Image Labeling from Weak 3D Supervision |
Modeling Image Patches with a Generic Dictionary of Mini-Epitomes |
Learning a Dictionary of Shape Epitomes with Applications to Image Labeling |
US Patents
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Systems and Methods for Data Page Management of NAND Flash Memory Arrange- ments, November 2008
Liang-Chieh Chen and Xueshi Yang -
Multi-Mode Encoding for Data Compression, February 2009
Liang-Chieh Chen and Xueshi Yang
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