Work Log

Last update: 2017.01.06 This post lists all non-trivial changes for the terraAI (a.k.a., TAI) project in the latest-first order, so by inspecting the top of this log you can find out what got changed since your last visit. You can then navigate to the target area using the links provided here. This is necessary because »

Image Operations with cGAN

In this report we explore the possibility of using cGAN (Conditional Generative Adversarial Networks) for performing automatic graphic operations on the photographs or videos of human faces, similar to those typically done manually using a software tool such as Photoshop or After Effects, by learning from examples. Motivation A good part of my research in Machine Learning has to »

Monocular Depth Perception with cGAN

Is it possible to train a cGAN (Conditional Generative Adversarial Networks) model for monocular depth perception? If the answer is yes, then it would mean that we have a way to allow an artificial system to acquire some basic concept about distance in the physical world, learning from only flat images, starting with nothing. The type of training proposed »

Generate Photo-realistic image from sketch using cGAN

In this report we study the possibility of building the neural model of human faces using cGAN. In my last experiment Generate Photo-realistic Avatars with DCGAN I showed that it is possible to use DCGAN (Deep Convolutional Generative Adversarial Networks), the non-conditional variation of GAN, to synthesize photo-realistic animated facial expressions using a model trained from limited number of »

Generate Photo-realistic Avatars with DCGAN

In this report we explore the feasibility of using DCGAN (Deep Convolutional Generative Adversarial Networks) to generate the neural model of a specific person from limited amount of images or videos, with the aim of creating a controllable avatar with photo-realistic animated expressions out of such a neural model. Here DCGAN holds the promise that the neural model created »

Image interpolation, extrapolation, and generation

Introduction Our ultimate goal is to generate 3D models out of textual or verbal commands. Here we tackle (for now) the simpler problem of generate 2D images, before moving on the more complex problem of dealing with 3D models. There have been some recent research that are relevant to the generation of 2D images that can also handle lighting, »

Machine Learning on Google Cloud and AWS/EC2, Hands-on

Here we look at running computing-intensive machine learning jobs using Google Cloud Platform (GCP) with TensorFlow, and also doing the same on AWS/EC2 GPU instances, from the perspective of cost effeciency, training time, and operational issues. This investigation is part of my effort in the open-source project terraAI, which requires a great deal of computing power for Machine »

Hands-on with TensorFlow on GCP

Following is my experience with the Google Cloud Platform (GCP). I am already familiar with Amazon's Elastic Compute Cloud (EC2), so this investigation will help me decide which platform better suits what I needed for my own terraAI project. The following was recorded in the October of 2016. Since GCP and TensorFlow are likely to evolve quickly, I expected »

Word2vec and IPA

Word2vec is an invaluable tool for finding hidden structure in a text corpus. It is essential for the TAI's IPA project, but we will also need to add some refinements over the standard Word2vec in order to meet our needs. This post is part of the TAI thread, which explores how to design and implement the terraAI (a.k. »

Ghost blog enhancements

This post is about the various enhancements that I have added to the Ghost system for this blog. This is a follow-up on the other post regarding how to convert a Ghost blog into a static website. This blog in itself is mainly for the purpose a certain AI project that I am working on. All of the enhancements »

Holodeck - Knowledge Representation - part 2

This is part 2 of the Holodeck series, focusing on issues related to knowledge representation (KR). This is a followup on the first post Crowd-driven Holodeck, where a skeletal design was presented for a HAI Holodeck. A quick recap To put this post in context (more can be found in the first post: This series discusses a HAI Holodeck, »

Blogging with Ghost

I share with you below my experience with the blogging system Ghost (version 0.8.0 as of this writing) used for this blog, and the problems that I ran into. This is not an exhaustive survey, but hopefully my experience will be useful to someone out there. This blog in itself is a working document for the terraAI »

How to build a Holodeck - part 1

You may have seen the Holodeck device that appeared in the TV series Star Trek: The Next Generation, where a user goes into the Holodeck, issues verbal instructions, and entirely realistic 3D objects or environment would appear instantly. This post explores the relevant AI technology needed in order to support such a vision. Here we use the Holodeck as »

Help

This post contains the master index to help you find all kinds of information regarding the terraAI project. Index for this post About this blog To participate in TAI Find quick answers How to follow changes Table of content Infotips Glossary Learning resources for beginners How to find things Acknowledgement Change log About: about the members of the core »

ML Resources

This post is for cataloging those online resources that are useful to my work for the terraAI project, in particular those related to Machine Learning. Hopefully these will also be useful to other Machine Learning researchers. Typesetting math formulas It would seem that the best way to typeset formulas, which is useful when discussing topics related to Machine Learning, »

Crowd-driven socialization

When a large crowd come together due to a certain common interest, we call it Crowd-driven Socialization, or Crowd socialization. I have been working on this for many years, initially on an online platform called the sMesh Central (or SC), which is for a casual type of online crowd socialization (e.g., ball games, presidential election, major media event, »

Code libraries

In order to implement the terraAI system we are going to need many good quality open-source code libraries. If you have experience with any of the following, by all means please share your insights with us in the comments section below! This is a live document, meaning it will be updated and republished from time to time as needed. »

Design Overview

INCOMPLETE DRAFT. DO NOT PROCEED This post explains the motivation for the terraAI project. Below we summarize the overall design principle. In order to rectify the problems of the Dark KBs mentioned above, we seek to create an open-source and public-access online platform where everyone can join in to build up the KB and the associated tools together. For »

Crowd-driven socialization in TAI

TAI (short for terraAI) is not just a technical AI platform, but it is also a kind of social platform. The vision here is that we want to let TAI users of all levels help with building up this immense system, and also make it easy for users to help each other. As such, TAI is not a traditional »

On-site Client-centric Socialization

What is On-site Client-centric Socialization (OCS)? It is a term that I made up in order to describe an interesting concept, since I could not find the applicable terminology for it. The idea turns the tradition Internet up-side-down, by moving part of the control from a server-centric model to a client-centric model. The end result of this are that: »

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