Google is intending to expand the dev tools available to makers using the Raspberry Pi microprocessor to power their projects this year -- potentially offering software tools for face- and emotion-recognition, speech-to-text translation, natural language processing, sentiment analysis, predictive analytics and more. The company is currently running a survey for Pi makers asking about the sorts of tools they would like it to develop. You can access the survey via the Raspberry Pi Foundation's website. "We at Google are interested in creating smart tools for Makers, and want to hear from you about what would be most helpful," it says in this survey. Tech areas that can be selected during the survey include home automation, drones, IoT, robotics, 3D printing, wearables and machine learning -- so the company is casting a pretty wide net here. We've reached out to Google and the Pi Foundation with questions and will update this post with any response.

Driving into Johannesburg, the skyline is often encased in a dome of smog. As Africa urbanises and industrialises, its economic growth is powered by coal, its vehicles by dirty fuels, and many still cook over paraffin and three-stone fires, burning their rubbish in the street. Researchers believe that more than 700,000 Africans die each year as a result of air pollution – and the number continues to grow. Few African cities even measure air pollution, but those that do routinely rank among the dirtiest on the planet. Nigeria is home to four of the worst, including Onitsha, which holds the dubious distinction of the Earth's most toxic air.

Apple's alleged decision to join competitors on the Partnership on A.I. research group shows it now understands that artificial intelligence can only succeed if competitors find some ways to work together. There are lots of different technologies that contribute to A.I. Machine intelligence, sensor development, voice recognition, security and biometrics, pattern matching, neural networking and so many more. The challenge is that as we witness the emergence of what seems likely to be the most disruptive set of technologies since the first iPhone, players in this space must make their solutions compatible. Apple, Facebook, IBM, Microsoft and others involved in A.I. development are beginning to realize they need to be compatible. Apple clearly understands this as it now allows its A.I. research teams to publish research papers, engage in peer review and get involved in the cooperative nature of scientific research.

IBM today took the wraps off a new release of PowerAI, the prepackaged bundle of deep learning frameworks that debuted last fall. With the addition of Google's TensorFlow framework, the company says its AI business model is starting to resemble the Linux distributor Red Hat. "In a sense, PowerAI makes IBM the Red Hat of deep learning," Sumit Gupta, the vice president of IBM's High Performance Computing & Data Analytics business, told Datanami. In the same way, instead of going to TensorFlow or Caffe or other websites [for deep learning frameworks], they want an enterprise-level distribution." The first release of PowerAI included "optimized" versions of Caffe-bvlc, Caffe-ibm, Caffe-nv, DIGITS, Torch, and Theano. With this release, the software includes TensorFlow 0.12, as well as Chainer, a deep learning framework that's very popular in Japan. Gupta says PowerAI--which is free and distributed as a binary for Ubuntu Linux (sorry, Red Hat)--is resonating with IBM clients, particularly those who have bought the "Minsky" Power8 servers to run deep learning and machine learning workloads on. "Enterprise customers prefer not to go to an open source website and download software and build it.

Artificial intelligence (AI) is sweeping into every industry this year powering trailblazing opportunities for software vendors and their partners. Forrester predicts investments in AI will triple in 2017, and IDC totals spending on cognitive systems at over $31 billion in just two years. I was at SAP TechEd 2016 in Barcelona when SAP announced its Application Intelligence Partner Program, which fast-tracks partners that add intelligence to SAP applications or additional AI platform capabilities. One noteworthy trailblazer is NVIDIA. Originally acclaimed for its unparalleled computer graphics capabilities, NVIDIA has repositioned itself as "the artificial intelligence company."

PowerAI is IBM's machine learning framework for companies that use servers based on its Power processors and NVIDIA's NVLink high-speed interconnects that allow for data to pass extremely quickly between the processor and the GPU that does most of the deep learning calculations. Today, the company announced that PowerAI now supports Google's popular Tensorflow machine learning library. While TensorFlow has only been available for a little over a year, it has quickly become the most popular open source machine learning project on GitHub. IBM's PowerAI already supported other frameworks and libraries like CAFFETheano, Torch, cuDNN, and NVIDIA DIGITS, but Tensorflow support was sorely missing from this lineup. IBM clearly sees the combination of PowerAI with Nvidia's NVLink interface and Pascal P100 GPU accelerators as a way to differentiate itself from the competition -- and in this case, the competition it is gunning for is clearly Intel (though it's worth noting that Intel and Google also recently teamed up to improve TensorFlow performance on its CPUs).

Microsoft will increase its use of artificial intelligence (AI) in order to improve the company's products, chief executive Satya Nadella said when revealing the tech giant's latest financial results. The company behind the Windows PC software reported revenue of 24.1 billion US dollars (£19.1bn) in the three months to December 31, up on the 23.8 billion dollars (£18.9bn) it generated in the same period last year, an increase driven by the firm's cloud-based products, Nadella said. Since taking over as chief executive in 2014, Nadella has shifted Microsoft's focus to its cloud business and software and away from hardware including smartphones. "Our customers are seeing greater value and opportunity as we partner with them through their digital transformation," he said of the latest figures, which also included 5.2 billion dollars (£4.1bn) in net income. "Accelerating advancements in AI across our platforms and services will provide further opportunity to drive growth in the Microsoft Cloud."

Actor Kristen Stewart, known for her portrayal of Bella in the "Twilight" movie franchise and director of "Come Swim" at the Sundance Film Festival, now has another line on her résumé: co-author of a computer science paper. The paper, published online in the preprint journal ArXiv, is called "Bringing Impressionism to Life with Neural Style Transfer in Come Swim." The authors describe a set of programming shortcuts that can make movie shots look as though they were painted or drawn in a certain style, such as impressionism or pointillism. The process relies on machine learning, a type of artificial intelligence, and gave certain shots in the film short, which uses allusive images to follow a man through his day, the look of an impressionistic painting. The shot described in the paper is about 15 seconds long, and the painting is by Stewart herself.

To complement existing offerings like Sparkling Water and Steam, H2O.ai is releasing Deep Water, a new tool to help businesses make deep learning a part of everyday operations. Deep Water will open up new possibilities for the TensorFlow, MXNet and Caffe communities to engage with H2O.ai. This also means that the GPU is set to become a greater part of business operations for the entire Fortune 500, not just tech companies. SriSatish Ambati, CEO of H2O.ai, says his company has found a sweet spot with predictive analytics. Ambati gave me the example of an insurance provider using H2O to analyze images of roofs and provide insights for preventative maintenance.

A year ago, in a report on Big Data and investment management, Citi Business Advisory Services predicted that "with the improved volume, velocity and variety of data inherent in the big data approach, the innovation seen in systematic trading models over the past decade could accelerate." One of the platforms highlighted in the Citi report was DataSift, a service that promises to "integrate social, blog and news data in a single place." Or as Citi put it, DataSift aggregates "marquee data source partners, including Edgar Online, Wikipedia, and WordPress." Edgar, of course, is consistent with old-fashioned ideas of what hedge fund managers through various third parties should keep track of. But Wikipedia presence on this short list might pull up short those who still think of it as a pastime for nerds who like to think of themselves as editors.