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Philips Kokoh Prasetyo
Lives in singapore
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Philips Kokoh Prasetyo

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Here is a talk I gave at Stanford last week on the things I wish I could have gotten into my TED talk but didn't have space for.

https://www.youtube.com/watch?v=wtCBCa7DiHo
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You need to be asking questions to which you don’t know the answer but such that if you did know the answer, you’d change the way you operate. If you already know the answer, or if you are testing an insignificant detail that doesn’t matter, you’ll just be wasting time and money. http://buff.ly/1SIMqzk 
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Distributed computing feature added in TensorFlow
 
In order to continually improve the Machine Learning models used in Google products, it's crucial that the training process be as fast as possible. One way to do this is to run #TensorFlow  across hundreds of machines. Ever since we released TensorFlow as an open-source project, distributed training support has been one of the most requested features. Now the wait is over.
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AI2 CEO Oren Etzioni envisions an artificial intelligence ‘utopia’

Imagine a future where life’s most boring or dangerous tasks are handled by machines. Time otherwise spent commuting, scheduling appointments, sifting through mail, could be devoted to human passions instead. That’s the best-case scenario for noted computer scientist Oren Etzioni, CEO of the Seattle-based Allen Institute for Artificial Intelligence, also known as “AI2,” founded by Microsoft co-founder Paul Allen.
Imagine a future where life's most boring or dangerous tasks are handled by machines. Time otherwise spent commuting, scheduling appointments, sifting thro
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An emoji is worth a thousand words

Google Photos puts your memories at your ☝tips and lets you 🔍 and find your photos instantly. But sometimes, you're 🔍 ing  in a hurry: while boarding the 🚋 , carrying lots of 🛍 , or trying to find a perfect photo to match your joke's 👊line. When it’s crunch 🕰 , 🔍 ing with a full word just doesn't ✂ it. That's why we're introducing: #SearchWithEmojis

Whether you're looking for pics of your pet dog (🐶) or your hot dog (🌭). Your 🚲  rides under the 🌞 or the 🌟s you gazed under the 🌙. The 🐚 you found at the 🏖 or you favorite 🍐 of 👟s…

Finding your pics is a ☮️ of 🎂. 

📸🔎😋,
Google Photos
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Philips Kokoh Prasetyo

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Bug fix release of #Elasticsearch 2.3.2
Today we are pleased to announce the bug fix release of Elasticsearch 2.3.2 based on Lucene 5.5.0. Users who are affected by the issues mentioned in the release notes are advised to upgrade. This release is already available on Elastic Cloud, our Elasticsearch-as-a-service platform.
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Great advice for aspiring researchers in computer science (and most other fields).
I'm almost done reviewing papers for another conference, so you know what that means -- time to blog. I am starting to realize that trying to educate individual authors through my witty and often scathing paper reviews may no...
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Useful #Elasticsearch cheat sheet in times of trouble
Instead of going through Elasticsearch’s documentation yet another time or looking at random Stack Overflow answers, just save this in your favorites!
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"Amazon Web Services faces strong competition today from the likes of Google and Microsoft, but it's still far ahead of US rivals. Measuring by total compute capacity in use, AWS is 10 times bigger than 14 other infrastructure-as-a-service providers combined"
Amazon Web Services, now 10 years old, dominates US cloud computing market.
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hahaha
 
We're excited to introduce the self driving bicycle. #selfdrivingbike

Check out the video here - https://goo.gl/hZo4I0
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Assembling the pieces to deploy machine learning systems

Getting machine learning systems to really work requires excellent machine learning models and algorithms, but also often requires lots of good systems work to surround the core machine learning models/algorithms to make them useful as components in larger systems.  We've been building up these pieces and open-sourcing them to make it easier for everyone to use machine learning in their products and applications.

A while ago, I posted (post: https://plus.google.com/+JeffDean/posts/6okdnD1MHmX) about the open-sourcing of TensorFlow Serving, an open source package developed at Google that complements the core TensorFlow system.  TensorFlow Serving makes it easy to take models that have been trained with TensorFlow and move them into a system for serving inference requests on those models (and simplifying messy issues like updating models in the live serving system as they are updated through continuous training, etc.).

This blog post by the TensorFlow Serving team at Google shows how to use TensorFlow, TensorFlow Serving, and Kubernetes (another project open-sourced by Google) to deploy a pre-trained Inception-v3 image classification model using TensorFlow Serving, running in Kubernetes containers, and using Kubernetes' ability to dynamically scale the number of replicas up and down as load changes.

Full tutorial link from the bottom of the blog post:
  https://tensorflow.github.io/serving/serving_inception

Class(ification) is starting!
In 2011, Google developed an internal deep learning infrastructure called DistBelief, which allowed Googlers to build ever larger neural networks and scale training to thousands of cores. Late last year, Google introduced Ten...
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Have them in circles
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data mining mania, likes machine learning and natural language processing
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singapore
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taipei, taiwan - surabaya - tainan, taiwan