Month: April 2020

Go language use still anchored in technology companies

While the Google-developed Go (golang) language has branched out into industries such as finance and media, much of its usage remains concentrated in the technology industry itself, according to the Go Developer 2019 Survey.

A report featuring results of the survey was published on April 20. Forty-three percent of respondents reported working in the technology sector while 12 percent were in financial services, 9 percent in media/gaming, and 7 percent in retail/consumer packaged goods.

A large majority of respondents said Go was working well for their teams (86 percent) and that they would prefer to use Go for their

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Innovating distributed AI training in every direction

Data science is hard work, not a magical incantation. Whether an AI model performs as advertised depends on how well it’s been trained, and there’s no “one size fits all” approach for training AI models.

The necessary evil of distributed AI training

Scaling is one of the trickiest considerations when training AI models. Training can be especially challenging when a model grows too resource hungry to be processed in its entirety on any single computing platform. A model may have grown so large it exceeds the memory limit of a single processing platform, or an accelerator has required developing special

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Google Cloud Anthos now available for AWS, with Azure to follow

Google Cloud has announced that Anthos — the company’s software for deploying and managing Kubernetes workloads across multiple on-prem and cloud environments — now supports running workloads on rival cloud platform Amazon Web Services (AWS), with Microsoft Azure support still in preview for now.

Speaking to InfoWorld, Jennifer Lin, vice president of product management at Google Cloud, said the delay in Azure support was simply down to internal engineering resources and “market demand” making AWS a higher priority for customers than Microsoft’s cloud.

Google Cloud was planning on announcing the news during its big Cloud Next conference earlier this month,

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PyTorch 1.5 adds C++ power, distributed training

PyTorch, the Python framework for quick-and-easy creation of deep learning models, is now out in version 1.5.

PyTorch 1.5 brings a major update to PyTorch’s C++ front end, the C++ interface to PyTorch functionality. The C++ front end now offers complete feature parity with the Python API. Normally one would write PyTorch applications exclusively in Python, but this change makes it readily possible to prototype the application in Python, then move it to C++ without losing any features, or to freely mix C++ and Python.

PyTorch 1.5 also adds a way to bind custom C++ classes to

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This planetary system’s perfect rhythm tells us a lot about how it came to be

A planetary system of six exoplanets in near-perfect synchronization gives astronomers a hint at how such groupings could evolve.

Over a period of seven years, astronomers have observed the star HD 158259 — invisible to the naked eye — discovering six planets in orbit around it in near-perfect synchronization. The extrasolar planets (exoplanets) consist of one ‘Super-Earth’ and five ‘Mini-Neptunes’ with exceptionally regular spacing and timing. Their regimented order gives researchers a hint as to how the system may have formed.

The study, led by researchers from the University of Geneva (UNIGE), was conducted with the aid of the SOPHIE

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How to fine-tune Gmail for maximum productivity

Email is a complicated beast. There are so many layers to mull over when it comes to making an inbox manageable, from the surface-level organizational factors (hello, labels!) to the more advanced under-the-hood features (filters, anyone?).

But beyond all of that, even, is the issue of your actual inbox interface. It may seem trivial, but having an interface that emphasizes the functions you use most while minimizing unnecessary clutter can go a long way in making email easier to manage — both in terms of efficiency and for the simple matter of sanity. (I know I feel

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