The Present and Future of Quantum Computing for AI
Quantum computing is still in it’s infancy, and no universal architecture for quantum computers exists right now. However, their prototypes are already here and showing promising results in cryptography, logistics, modelling and optimization tasks. For AI researchers optimization and sampling is particularly important, because it allows to train Machine Learning models much faster with higher accuracy.
Artificial intelligence could be the future of banking
By leveraging AI, banks can engage with consumers in a faster and more consistent manner. They can use “bots” at contact centres for basic inquiries to free up employees for more complicated questions. They can use robo-advisers to provide basic investment services at lower cost.
New app scans your face and tells companies whether you’re worth hiring
HireVue, a company with a “video interview intelligence platform,” wants to make that easier by using artificial intelligence to do the heavy lifting for you and screen multiple candidates at once.
Pandas tips and tricks
This post includes some useful tips for how to use Pandas for efficiently preprocessing and feature engineering from large datasets.
The Hard Thing About Machine Learning
Building systems is hard; building machine learning systems that give robust predictions is especially hard.
Aug. 2017 Hive User Group Meeting @HortonWorks
1. Hive on Spark, production experience @Uber (Xuefu Zhang)
2. Reair and its usage for Uber's multi data center replication (Zheng Shao)
3. ACID, use cases in data management (Carter Shanklin)
4. Optimized Hive replication (Anishek Agarwal)
5. LLAP: Locality is dead (in the cloud) (Gopal Vijayaraghavan)
6. Don't reengineer, reimagine: Hive buzzing with Druid's magic potion (Slim Bouguerra)
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