Cloud News & Reviews
Chris Preimesberger, April 16, 2019 5:00 AM
More Cloud News
TREND ANALYSIS: Qualcomm is working on applying quantum field theory to deep-learning AI. This is an enormous potential game changer in several real-world scenarios.
eWEEK DATA POINTS: There are lots of functions currently being conducted in the cloud. One of them that doesn't get a lot of attention is document capture, something every business has to handle.
The OpenStack Stein release introduces new multi-cloud orchestration capabilities, as well as enhancements to help enable edge computing use-cases.
Google wants to bridge the gap and complexity of managing the cloud and on-premises applications with Anthos, a hybrid cloud platform based on the earlier Google Cloud Services.
Google aims to boost the utility and features of its Google Cloud Platform by partnering with seven leading open-source providers of cloud services and also released Cloud Run, the latest member of Google’s serverless compute stack.
JOIN US: This is a chat-based conversation about how we realistically are going to be storing our business and personal data in places where it will be safe and accessible for years to come. Can the cloud handle all of this? Doubtful.
EXCLUSIVE: Sysdig is set to launch version 2.0 of its Cloud-Native Visibility and Security Platform, providing organizations with integrated capabilities to manage workload performance and security.
eWEEK DATA POINTS: Questionable online travel agencies, travel aggregators, competitors and criminals are using malicious bots to conduct a variety of attacks on airline websites that result in online fraud, website downtime and loss of potential revenue.
PRODUCT/SERVICE ANALYSIS: Why isn't it automatic--or at least much easier--to show movies from services with which you subscribe on any device you are using? It's all a complicated mess; perhaps this leaves open an opportunity for an enterprising new service company.
eWEEK DATA POINTS: Though excitement about AI and ML is legitimately growing, we hear little about how the data actually goes from collection to algorithm. By examining the process behind building hypothetical machine learning models, we can look at what important processes are often glossed...