Adam Paszke speaks at PyData Warsaw 2018 about PyTorch, one of the main tools used for machine learning research.

It’s been developed in beta mode for over 2 years, but this October, a release candidate for 1.0 version has been finally released. In this talk, Adam briefly introduces the library, and then move on to showcase the cutting edge features we introduced recently.

CNBC has a look at the Waldorf School where technology is not ever present in the classroom – an idea which runs counter to the prevailing philosophy that more tech equates to better education.

The Waldorf teaching philosophy is used at more than 1,000 institutions in 91 countries, including 136 schools in the U.S. Technology and screens aren’t used at all through 8th grade, and are scarce even in high school. CNBC gets an inside look at what it is like.

Here’s an interesting idea: an open deep learning compiler stack to compile various deep learning models from different frameworks to the CPU, GPU or specialised accelerators. It’s called the Tensor Virtual Machine or TVM for short.

TVM supports model compilation from a wide range of frontends like TensorFlow, Onnx, Keras, Mxnet, Darknet, CoreML and Caffe2. TVM-compiled modules can be deployed on backends like LLVM (JavaScript or WASM, AMD GPU, ARM or X86), NVidia GPU (CUDA), OpenCL and Metal. TVM also supports runtime bindings for programming languages like JavaScript, Java, Python, C++ and Golang. With a wide range of frontend, backend and runtime bindings, this deep learning compiler enables developers to integrate and deploy deep learning models from any framework to any hardware, via any programming language.

College Humor claims to have an AI written script for the Game of Thrones finale. It’s funny to watch and reads like it was written by a bot. However, without a link to any documentation or source code, we will have to take it on faith that it’s a product of AI or random typing (like the actual GoT finale).

Machine learning is no longer just for data science whiz kids. Now, front end developers need to have a basic handle on this technology. Here’s a great talk by Charlie Gerard on “Practical Machine Learning for Front End Developers.”

From the abstract:

Machine learning can have some pretty complicated concepts to grasp if you’re not a data scientist. However, recent developments in tooling make it more and more accessible for developers and people with little or no experience. One of these advancements is the ability to now train and run machine learning algorithms and models in the browser, opening this world to front-end developers to learn and experiment. In this presentation, we will talk about the different applications, possibilities, tools and resources, as well as show a few examples and demos, so you can get started building your own experiments using machine learning in JavaScript.

MLflow enables data scientists to track and distribute experiments, package and share models across frameworks, and deploy them – no matter if the target environment is a personal laptop or a cloud data center. Here’s an interesting take from the Register.

MLflow was designed to take some of the pain out of machine learning in organizations that don’t have the coding and engineering muscle of the hyperscalers. It works with every major ML library, algorithm, deployment tool and language.

AI is the wonder of our age and the hottest tech of the 2010s, but does it hurt the environment?

For Emma Strubell, the lead author behind the paper, the most shocking discovery of the research was when she analyzed one of the recent models she designed as part of her PhD work at University of Massachusetts Amherst. While the algorithm’s carbon footprint–78,468 pounds of carbon dioxide–wasn’t quite as big as some of the others she assessed in the paper, it still was similar in size to the carbon dioxide that the average American emits in two years.

We are quickly getting to the point that any AI engineer worth their salt needs to have a good grip on the fundamentals of kubernetes.  It’s not just for the DevOps crowd anymore.

Official kubernetes (k8s) website says, Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications. It groups containers that make up an application into logical units for easy management and discovery. Kubernetes builds upon 15 years of experience of running production workloads at Google , […]