There are many choices for solving problems with machine learning (ML) available, some that you can build and some that you can buy. We’ll be focusing on the build side here, exploring the various options and the problems they solve, along with recommendations.
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Over the last year, our collective understanding of work—where it takes place and how it gets done—has been transformed. As companies and organizations across the globe reimagine work, new challenges and opportunities are emerging.
Explainable AI (XAI) is a set of tools and frameworks that can be used to help you understand how your machine learning models make decisions. This shouldn’t be confused with showing a complete step-by-step deconstruction of an AI model, which can be close to impossible if you’re attempting to trace the millions of parameters used in deep learning algorithms. Rather, XAI aims to provide insights into how models work, so human experts are able to understand the logic that goes into making a decision.
Cloud Spanner is the only enterprise-grade, globally-distributed, and strongly-consistent database service built for the cloud, specifically to combine the benefits of relational database structure with non-relational horizontal scale. It is a unique database that combines transactions, SQL queries, and relational structure with the scalability that you typically associate with non-relational or NoSQL databases.
Compute Engine is a customizable compute service that lets you create and run virtual machines on Google’s infrastructure. You can create a Virtual Machine (VM) that fits your needs. Predefined machine types are pre-built and ready-to-go configurations of VMs with specific amounts of vCPU and memory to start running apps quickly. With Custom Machine Types, you can create virtual machines with the optimal amount of CPU and memory for your workloads. This allows you to tailor your infrastructure to your workload. If requirements change, using the stop/start feature you can move your workload to a smaller or larger Custom Machine Type instance, or to a predefined configuration.
Last week, we took a look at Cloud Bigtable. For those who know a thing or two about big data, you may wonder how is Bigtable different from BigQuery. While these two services have several similarities, including “Big” in their names, they support very different use cases in your big data ecosystem.
Thinking of building an application that needs low latency and high throughput? You need a database that can scale for a large number of reads and writes. Cloud Bigtable is designed to handle just that.
In March, Google announced that Nearby Share is coming to Chromebooks, so you can quickly and securely share files between your Chromebook and other Chrome OS or Android devices. It’s rolling out today, alongside new additions like wallpapers, app notifications and an easier way to share files for offline use.
Sharing and exchanging data with other organisations is a critical element of analytics strategy but it’s hamstrung by unreliable data and processes and only getting harder with security threats and privacy regulations on the rise.
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