谷歌收入三年来增长最慢，手机、自动驾驶等业务盈利欠佳
周三，谷歌经历了三年来**收入增长最慢的一天**：营收同比增长17%（创自2016年第一季度增长率17%以来新低），不及上年同期的26%；营业利润率为18%，不及上年同期的25%。财报发布后，Alphabet股价在盘后交易中大跌7%，市值蒸发了600多亿美元。
作者： | Debra 来源：infoq
发布时间：2019-04-30 14:53:43
一键修复女神林青霞旧照，背后用到了哪些AI技术？
近日，第四届NTIRE比赛结果公布，美图影像实验室MTlab在图像增强赛道中斩获冠军，同时夺得图像去雾赛道的季军。
作者：Debra 来源：infoq
发布时间：2019-04-30 08:00:00
Unsupervised learning: the curious pupil
Unsupervised learning is a paradigm designed to create autonomous intelligence by rewarding computer programs for learning about the data they observe without a particular task in mind--in other words, the program learns for the sake of learning. We believe unsupervised learning will be foundational to building artificial general intelligence.
作者：DeepMind 来源：DeepMind
发布时间：2019-04-10 19:00:00
JavaScript for Machine Learning using TensorFlow.js
Web developers are just happy to do everything within their JS comfort Zone
作者：Priyesh Patel 来源：medium
发布时间：2019-04-01 23:13:50
Towards Robust and Verified AI: Specification Testing, Robust Training, and Formal Verification
Bugs and software have gone hand in hand since the beginning of computer programming. Over time, software developers have established a set of best practices for testing and debugging before deployment, but these practices are not suited for modern deep learning systems. Today, the prevailing practice in machine learning is to train a system on a training data set, and then test it on another set. While this reveals the average-case performance of models, it is also crucial to ensure robustness, or acceptably high performance even in the worst case. In this article, we describe three approaches for rigorously identifying and eliminating bugs in learned predictive models: adversarial testing, robust learning, and formal verification.
作者：DeepMind 来源：DeepMind
发布时间：2019-03-29 01:00:00
TF-Replicator: Distributed Machine Learning for Researchers
At DeepMind, the Research Platform Team builds infrastructure to empower and accelerate our AI research. We are excited to share how we developed TF-Replicator, a software library that helps researchers deploy their TensorFlow models on GPUs and Cloud TPUs with minimal effort and no previous experience with distributed systems. TF-Replicator’s programming model has now been open sourced as part of TensorFlow’s tf.distribute.Strategy.
作者：DeepMind 来源：DeepMind
发布时间：2019-03-08 01:04:00
Artificial Intelligence for Advanced Blockchain Investigations
Blockchain and Artificial Intelligence work together beautifully. While the former is good for storing and validating records of every…
作者：ORS CryptoHound 来源：medium
发布时间：2019-03-03 22:46:38
Machine learning can boost the value of wind energy
Since last year, a joint DeepMind/Google project to apply machine learning to 700 MW of wind power in the central US has so far boosted the value of wind energy by ~20%. A neural net trained on weather forecasts & historical turbine data predicts wind power output 36 hours ahead of actual generation. Based on these, our model recommends optimal hourly delivery commitments to the power grid 24 hours in advance. These wind farms—part of Google’s global fleet of renewable energy projects—collectively generate as much electricity as is needed by a medium-sized city.
作者：DeepMind 来源：DeepMind
发布时间：2019-02-26 21:32:00
Music Created by Artificial Intelligence Is Better Than You Think
A.I. doesn’t have to be a threat to human musicians. It might actually improve their melodies.
作者：Stuart Dredge 来源：medium
发布时间：2019-02-01 22:01:01
AlphaStar: Mastering the Real-Time Strategy Game StarCraft II
StarCraft, considered to be one of the most challenging Real-Time Strategy games and one of the longest-played esports of all time, has emerged by consensus as a “grand challenge” for AI research. Here, we introduce our StarCraft II program AlphaStar, the first Artificial Intelligence to defeat a top professional player.
作者：DeepMind 来源：DeepMind
发布时间：2019-01-25 01:55:00
Using the latest advancements in deep learning to predict stock price movements
Link to the complete notebook: https://github.com/borisbanushev/stockpredictionai
作者：Boris B 来源：medium
发布时间：2019-01-15 11:15:40
AlphaZero: Shedding new light on the grand games of chess, shogi and Go
We introduce a full evaluation of AlphaZero, published in the journal Science, which describes a single algorithm that taught itself from scratch how to master the games of chess, shogi (Japanese chess), and Go, convincingly beating a world champion program in each case. AlphaZero’s ability to learn each game by itself results in a distinctive, creative and dynamic playing style that has captured the attention of the chess community. The result also marks an important step towards creating a flexible, general-purpose system that could one day learn to solve many different important and complex scientific problems.
作者：DeepMind 来源：DeepMind
发布时间：2018-12-07 03:00:00
AlphaFold: Using AI for scientific discovery
Our system, AlphaFold, which we have been working on for the past two years, builds on years of prior research in using vast genomic data to predict protein structure. The 3D models of proteins that AlphaFold generates are far more accurate than any that have come before—making significant progress on one of the core challenges in biology.
作者：DeepMind 来源：DeepMind
发布时间：2018-12-02 23:00:00
