f(AI)nder View - July 2018
f(AI)nder View - a monthly digest in the field of
Artificial Intelligence, Machine Learning, Deep Learning
exploring the various levels and faces of AI: from basic to sophisticated ones,
from algorithms and technologies to business applications

AI ecosystem
AI industry analytics, trends, foresights, insights, challenges, regulations, etc.
An analysis of more than 400 use cases across 19 industries and nine business functions highlights the broad use and significant economic potential of advanced AI techniques. For this briefing McKinsey Global Institute mapped both traditional analytics and newer "deep learning" techniques.
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The AIconics is a world-renowned, independently-judged awards celebrating the drive, innovation and hard work in the international Artificial Intelligence for Business Community. 2018 Award Categories include: Best Innovation in Deep Learning, in AI Hardware, in NLP, Best AI-StartUp and others.
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The demand for AI experts has grown exponentially over the last few years.
The report from Element AI summarizes and visualizes by maps the research into the scope and breadth of the worldwide AI talent pool.
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Pete Warden: "Machine learning can run on tiny, low-power chips, and that this combination will solve a massive number of problems we have no solutions for right now. Deep learning can be very energy-efficient."
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A team of AI algorithms just crushed humans in a complex computer game.
The accomplishment represents a major breakthrough in the history of artificial intelligence(AI) comparable with AlphaGo defeating Lee Sedol in 2016.
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Applications
"In this blogpost, we go back to basics, and let a car learn to follow a lane from scratch, with clever trial and error, much like how you learnt to ride a bicycle. No dense 3D map. No hand-written rules. We learnt to follow lanes from scratch in 20 minutes".
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Traffic congestion is a daunting problem that is affecting the daily lives of billions of people across the world. Recently, a promising new traffic control scheme known as Virtual Traffic Lights (VTL) has been proposed for mitigating traffic congestion. When two cars approach a junction on different roads, they elect a lead vehicle that controls the junction.
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The ability to correctly classify the room type for a given listing photo is incredibly useful for optimizing the user experience. On the guest side, it facilitates re-ranking and re-layout of photos based on distinct room types. On the host side, it helps automatically review listings.
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AI is already helping us more efficiently diagnose diseases, develop drugs, personalize treatments, and even edit genes. But this is just the beginning.
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Advanced algorithms working from large chemical databases can predict a new chemical's toxicity better than standard animal tests, suggests a study led by scientists at Johns Hopkins Bloomberg School of Public Health.
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AI beats human doctors in neuroimaging recognition
An artificial intelligence (AI) system scored 2:0 against elite human physicians in two rounds of competitions in diagnosing brain tumors and predicting hematoma expansion in Beijing.
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Introductions
Popular introduction to Recurrent Neural Networks (RNN), including basic math behind them and code tutorial showing how to implement a RNN model from scratch. The idea behind RNNs is to make use of sequential information. The beauty of RNNs lies in their diversity of application: Speech recognition, Handwriting recognition, Human action recognition, Time series prediction, Music composition and others.
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LSTMs have an edge over conventional feed-forward neural networks and RNN in many ways. This is because of their property of selectively remembering patterns for long durations of time. The memory blocks are responsible for remembering things and manipulations to this memory is done through three major mechanisms, called gates: Forget Gate, Input Gate, Output Gate.
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Splendid review of the use of CNNs for modeling biological vision in the Q&A format. What are CNNs? When was the current connection between CNNs and the visual system made? How should we interpret the different parts of a CNN in relationship to the brain? What do CNNs do that the visual system doesn't do? These and others interesting questions are uncovered excellently.
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Martin Zinkevich: "This document is intended to help those with a basic knowledge of machine learning get the benefit of Google's best practices in machine learning. To make great products do machine learning like the great engineer you are, not like the great machine learning expert you aren't". More than 40 structured and pragmatic ML rules.
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Very good and rather detailed introduction for object detection with overview of the evolution of the state-of-the-art object detectors and their differences, similarities and limitations that need to be solved for further progress. There are described and compared two-staged methods (R-CNN, SPPnet, Fast R-CNN, Mask R-CNN) and single-stage methods (YOLO, SSD, DSSD, RetinaNet).
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Toolbox
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
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This repository contains material related to Udacity's Deep Reinforcement Learning Nanodegree program. The tutorials lead you through implementing various algorithms in reinforcement learning. All of the code is in PyTorch (v0.4) and Python 3.
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Fully computational approach for modeling the structure of the space of visual tasks: via finding (first and higher-order) transfer learning dependencies across a dictionary of twenty six 2D, 2.5D, 3D, and semantic tasks in a latent space. Task Bank: A Unified Bank Of 25 Pretrained Visual Estimators.
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A new TensorFlow feature called "AutoGraph" converts Python code, including control flow, print() and other Python-native features, into pure TensorFlow graph code. Why do we need graphs at all? Graphs allow all kinds of optimizations, like removing common sub-expressions and fusing kernels.
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At first, the genomes are terrible at playing the game. But over time, they get better. And after many generations, they play well, sometimes better than humans. Evolved code is just as good as many deep-learning approaches and outperforms them in games like Asteroids, Defender, and Kung Fu Master.
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Events
International Conference on Machine Learning 2018 Notes
David Abel: "This document contains notes I took during the events I managed to make it to at ICML in Stockholm, Sweden".
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f(AI)nder View - a monthly digest in the field of
Artificial Intelligence, Machine Learning, Deep Learning
exploring the various levels and faces of AI:
from basic to sophisticated ones,
from algorithms and technologies to business applications

f(AI)nder View is prepared by f(AI)nder Lab
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