Article: IBM just launched the first developer certification for quantum computing

Open Software, Open Source

IBM just launched the first developer certification for quantum computing

IBM has unveiled its very first quantum developer certification, but what exactly does it suggest on a developer’s CV? Developers can now be officially quantum-certified. IBM has unveiled a quantum developer certification which it says, once devs have passed the 60-question test, will act as proof of at least some of the skills required to build and run quantum programs.

The certification, unsurprisingly, focuses on IBM’s own quantum computing software development kit (SDK), Qiskit, which is an open-source platform based on Python scripts that enables developers to carry out a range of quantum experiments, from prototyping quantum algorithms to executing code on cloud-based quantum devices.

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Article: Chip maker Innovium certifies white-box switches on open-source SONiC to disrupt networking industry

Circuits, Hardware, Open Infrastructure, Open Manufacturing

Chip maker Innovium certifies white-box switches on open-source SONiC to disrupt networking industry

The open-source SONiC software will bring the same benefits of reduced total cost of ownership in networking as happened in white-box servers, Innovium claims. Networking equipment from Cisco Systems, Arista Networks, and Juniper Networks and others runs on operating system software owned and built by those vendors. Some parties think that needs to change.

Tuesday morning, Innovium, a vendor to Cisco and others of switching chips, announced it with partners in the original device maker, or ODM, field, it is testing and certifying network switches built on its chips and the open-source SONiC operating systems, a network operating system developed by Microsoft and the Open Compute Project and licensed under a mix of the GNU GPL and the Apache License.

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Article: Data, analytics, machine learning, and AI in healthcare in 2021

Innovation, Language, Open Data, Open Health, Open Space, Procedures (Medical)

Data, analytics, machine learning, and AI in healthcare in 2021

The survey was conducted by Lorica and Paco Nathan, and sponsored by John Snow Labs. A total of 373 respondents from 49 countries participated. A quarter of respondents (27%) held Technical Leadership roles. Here are some key findings, with additional insights from Lorica and Talby.

When asked what technologies they plan to have in place by the end of 2021, almost half of respondents cited data integration. About one-third cited natural language processing (NLP) and business intelligence (BI) among the technologies they are currently using or plan to use by the end of the year.

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Article: Amazon AWS, Hugging Face team up to spread open-source deep learning

Code, Free, Language, Open Data, Open Software

Amazon AWS, Hugging Face team up to spread open-source deep learning

Two years ago, the New York-based startup Hugging Face burst onto the natural language processing scene with a way to let many more parties participate in state-of-the art deep learning. Transformers, a programming kit to quickly grab any of a number of natural language neural networks, including Google’s BERT, was posted as a library to be invoked from the dominant programming frameworks, PyTorch and TensorFlow.

It has grown and grown in popularity. More than 5,000 organizations are now using the library, the company says. The popularity of that toolkit has been recognized by Amazon AWS, the world’s biggest clouding computing provider, and the two companies Tuesday announced a partnership to combine Transformers with the best aspects of Amazon AWS’s programming tools.

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Article: Streamlining data science with open source: Data version control and continuous machine learning

Open Software, Open Source

Streamlining data science with open source: Data version control and continuous machine learning

MLOps, short for machine learning operations, is the equivalent of DevOps for machine learning models: Taking them from development to production, and managing their lifecycle in terms of improvements, fixes, redeployments, and so on.

MLOps, short for machine learning operations, is the equivalent of DevOps for machine learning models: Taking them from development to production, and managing their lifecycle in terms of improvements, fixes, redeployments, and so on.

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