Brain to the Cloud: Examining the Relationship Between Brain Activity and Video Game Performance

A few months back, I read a really excellent (but pretty old) blog post that explained how to hack a toy called a Mind Flex to extract and analyze the data within it. At first, I couldn't believe that such a thing existed. I mean, sure — gimmicky toys have been around for ages, so I wasn't shocked that the toy claimed to read the user's mind. It's not uncommon to fake this kind of gimmick. But, the fact that the Mind Flex contains a real, legit EEG chip that read your mind seemed almost too good to be true. I wondered if it was possible to take this hack a step further. Instead of just reading the data, or using the data to "control" something else, what if I were to read the data while performing some task and see what the data reveals about my performance during that task? I would need to complete an activity with quantifiable data to properly compare the brain activity to the task results to see if my attention levels correlated to the task's success or failure. Deciding on the actual action to measure wasn't tricky. I am a pretty avid video game player and had recently been trying to think of a way to integrate my gameplay statistics into a project, so I surmised that the combination would be an intriguing one.

So I asked myself: "if I could hack the Mind Flex and wear it while playing Call of Duty, what would the data show?" Could I establish a relationship between cognitive function and video game performance? In other words, when I'm focused and attentive, do I play better? Or, when I'm distracted, do I play worse? Is there no connection at all? I wasn't sure if my tests would succeed, but I decided to find out.

Enterprise Messaging With Autonomous DB and Micronaut

I’ve written about messaging many times on my blog, and for good reason, too. It’s a popular subject that developers can’t seem to get enough of. In this world of distributed architectures, it’s critical that services communicate with each other to ensure the application's business logic is implemented properly. It’s well established that messaging is crucial for modern applications, so let’s look at a messaging solution that exists in the Oracle Cloud that you may not be aware of. In fact, if you’re already using Autonomous DB, then this solution is available to you at no additional charge! Allow me to introduce you to Oracle Advanced Queuing (AQ). 

What’s AQ? It’s exactly what it sounds like: a full-featured messaging solution right inside the database. Point-to-point, pub/sub, persistent, and non-persistent messaging are all supported. There are tons of ways to interact — including via PL/SQL, JMS, JDBC, .NET, Python, Node.JS — and pretty much any popular language can interface with AQ. Demos tend to be the best way to understand concepts like this, so in this post, we’re going to look at how to enable AQ in your Autonomous DB instance, create a queue, and enqueue and dequeue messages with PL/SQL. To complete the demo, we’ll look at publishing and consuming messages from AQ from a very simple Java application written with Micronaut.

How to Set Up and Run a (Really Powerful) Free Minecraft Server in the Cloud

In this post, I’m going to show you how to set up and run your very own private, dedicated Minecraft server in the cloud. I have blogged about this before, but the server was limited to 1 CPU core and 1 GB of RAM in that post. In this post, we're going to create a server with up to 4 CPU cores and 24 GB of RAM! That’s more than enough resources to host a game with 20+ friends with excellent performance (and still have enough leftover to create another server for something else). And best of all, it’s absolutely free! Forever!! I’m sure you’re just as excited as I am about this, so let’s jump right into it and get started!

Why Is This a Big Deal? 

In this post, we’re going to launch a new OCI Virtual Machine that uses a new Ampere Arm chip. These VMs provide better price-performance and near-linear scaling for CPU-bound workloads compared to x86-based instances. They are suitable for a wide range of workloads including web applications, media encoding, AI Inferencing, and much more. We’re very proud that Oracle is now partnering with leading technology vendors to make Arm server-side development first-class and easy.