Technology News Worth Reading

Here are a few technology news stories that I’ve read in the past week or so.

Cloud Native Computing Foundation Announces Rook Graduation

Rook is an open source cloud native storage orchestrator for Kubernetes, providing the platform, framework, and support for a diverse set of storage solutions to natively integrate with cloud native environments. Rook delivers its services via a Kubernetes Operator for each storage provider. It was originally accepted as a CNCF project in 2018. It is the thirteenth CNCF project, and the first project based on block, file, or object storage, to graduate. Read the announcement article

How is Robotics Changing the Healthcare Industry?

Robotics is changing the healthcare industry in a lot of fundamental ways. Robots can manage the monotonous and repetitive tasks while leaving the doctors and nurses free to do the critical tasks they were trained for. This article discusses the wide variety of applications that robotics has in healthcare to make the lives of both doctors and patients much easier. Read the article.

Looking for the Next Step in Cloud Performance? Look to Data Center Design

In the near future, data centers will need specialized storage and compute areas that are segregated from each other. For example, when designing a floor plan, it’s likely we’ll see data center operators walling off Compute-as-a-Service from Storage-as-a-Service. This can help solve issues around cooling, which is paramount to eliminating waste and improving performance. However, it doesn’t fully solve the issue of accessibility and latency speeds. Read the post.

Object Detection from 9 FPS to 650 FPS

This article is a practical deep dive into making a specific deep learning model (Nvidia’s SSD300) run fast on a powerful GPU server, but the general principles apply to all GPU programming. The SSD300 is an object-detection model trained on COCO, so output will be bounding boxes with probabilities for 81 classes of object.

Product Demo Sucks Because It’s Focused on Your Product

In this exclusive interview, Falcone shares the structure of a winning product demo and the tactics he’s discovered to convince people that they need your product in just one conversation. one of the easiest and biggest mistakes he sees is that companies don’t effectively craft their demo to fit their specific audience — i.e. they don’t distill their dozens of features and selling points into the few that will really resonate with this particular investor, prospect, or even prospective employee.

Computer Scientists Break Traveling Salesperson Record

In a paper posted online, Klein and his advisers at the University of Washington, Anna Karlin and Shayan Oveis Gharan, have finally achieved a goal computer scientists have pursued for nearly half a century: a better way to find approximate solutions to the traveling salesperson problem. Read the article. Read the paper.

The Gap: Where Machine Learning Education Falls Short

As the field of machine learning has become ever more popular, a litany of online courses has emerged claiming to teach the skills necessary to “build a career in AI”. But before signing up for such a course, you should know whether the skills acquired will directly allow you to apply machine learning better. These questions are not limited to online courses but rather encompass machine learning classes that have begun to fill lecture halls at many universities. Are these classes that students flock towards actually helping them achieve their practical goals? Read the article.

10 Popular Backend APIs

A Backend API is an Application Programming Interface that developers can use to integrate with backend services. A great place to find these APIs is in the Backend or Backend as a Service categories in the ProgrammableWeb API directory. This article gives details to the ten most popular Backend APIs on ProgrammableWeb, based on website traffic.

The unreasonable effectiveness of the Julia programming language

Six years ago, the author wrote about the enduring prominence of Fortran for scientific computing and compared it with several other languages. That article with a prediction that, in 10 years, a new language called Julia stood a good chance of becoming the one that scientists would turn to when tackling large-scale numerical problems. The author’s prediction was not very accurate, though. It actually only took Julia about half that time. Read the article.

Big Tech, Out-of-Control Capitalism and the End of Civilization

“Our digital era is a blend of “utopia and dystopia,” says Tristan Harris, who left Google to cofound The Center for Humane Technology (a phrase that sounds increasingly oxymoronic). “I can hit a button on my phone and a car shows up in 30 seconds and I can go exactly where I need to go. That is magic.” But Harris fears tech’s ill effects are outweighing its benefits. “If we don’t agree on truth,” he says, “or even that there is such a thing as truth, we’re toast.” Read the complete Scientific American article.

10 Best Text Annotation Tools and Services for Machine Learning

In the AI research and development industries, annotated data is gold. Large quantities of high-quality annotated data is a goldmine. On the other hand, sometimes finding or creating this data can be an expensive and arduous task for your team. Fortunately, there are a variety of text annotation tools and services available that can provide you with the data you need. Some of these services include entity extraction, part-of-speech tagging, sentiment analysis, and more. Read the DZone article.

30+ Tools List for GitOps

Speaking of the right tools for the job, there are countless tools to help you integrate the GitOps approach with your existing workflows. Some of the tools supporting GitOps are so popular that you may even be using it in your existing pipeline. To help you get started, here are the tools that we recommend if you want to incorporate GitOps. Read the post.