It is time to stop “collecting” the data into a central repository and start “connecting” to the data at the sources. A new architecture—logical data fabric—facilitates this approach by gaining a virtual view of the data.
Artificial intelligence could help us fight the coronavirus crisis. AI can, for example, already identify pneumonia on a CT scan in seconds with a high degree of accuracy. See what other things it can do to help flatten the curve.
TensorFlow 2.2.0 has been released, nearly four months after v2.1.0. The TensorFlow team has been keeping busy: In the latest version of the machine learning platform, they have added lots of new features and breaking changes, and have also fixed several bugs.
The initial release of Elyra AI Toolkit has been announced. This toolkit developed by IBM consists of different extensions for Jupyter Notebooks. They are designed to extend its capabilities for developing artifical intelligence models, so let’s take a closer look.
The initial release of the Julia programming language was eight years ago, in 2012. We spoke to the four creators of the language, Dr. Viral B. Shah, Dr. Jeff Bezanson, Stefan Karpinski and Prof. Alan Edelman, to find out whether Julia has been able to live up to their high expectations. They also went into detail about the various use cases Julia is applied to today, how the language compares to Python, and where it is headed in the future.
The second PyTorch release of the year has landed. PyTorch 1.5 brings some of the deep learning library’s previously experimental features into stable mode, including the C++ frontend API. Let’s take a closer look and see what that means—and what else has been updated in this release.
AI and ML technologies can make an impact by reducing emissions and maximizing production efficiency. The energy sector has lavish amounts of data to manage, AI is a perfect fit for this purpose. Let’s look at how machine learning can benefit the energy sector.
In this talk from the Machine Learning Conference, Kamil Kaczmarek and Jakub Czakon focus on practical guidelines and tips on how to set-up and maintain smooth collaboration in data science projects. Discover how to best track and collaborate in data science.
When artificial algorithms are biased, this can create unethical results, which in turn can lead to PR disasters for businesses. In this article, you will learn about three different types of AI bias – algorithmic, technical, and emergent – and what measures can be used to limit them.
Take a look at our brand new ML Magazine, in which the authors will give you a full idea of the cutting edge of machine learning—from tutorials for certain tools to insights about the relationship between AI and ethics. Don’t miss our first issue that includes an interview with Noam Chomsky.
For certain tasks, Jupyter users tend to switch to general-purpose IDEs. Therefore, the Jupyter project has decided to add a new feature that Jupyter users have been missing—a visual debugger in JupyterLab. Let’s take a closer look at the features of the debugging extension’s initial release.
Accidents at sea happen all the time. Their costs – in terms of lives, money and environmental destruction – are huge. Wouldn’t it be great if they could be predicted and perhaps prevented? Dr. Yonit Hoffman’s Machine Learning Conference session discusses new ways of preventing sea accidents with the power of data science.
The deep learning company Dessa has open sourced Atlas, a deep learning platform. Though currently still in beta mode, it is designed to make running, evaluating and deploying deep learning projects easier. It works on macOS, Linux and Windows, and offers TensorBoard integration. Let’s take a closer look.
How can machine learning and artificial intelligence change the landscape of manufacturing? According to reports by Deloitte and McKinsey, machine learning improves product quality and has the potential to double cash flow. Let’s take a look at three global manufacturers who are already on board.