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Top AI & Data Updates Announced By Tech Giants In 2019

Top AI & Data Updates Announced By Tech Giants In 2019

Srishti Deoras

The year 2019 was a very productive year in terms of new updates launched by tech giants. From new operating systems to open sourcing frameworks, this year was a giant step towards white boxing technologies and data democratisation.

In this article, we are compiling a list of all the major announcements in this field:



January

Microsoft announced that they will be implementing changes to the pricing of GitHub, the software development platform it acquired late last year. It announced that the option to make repositories private would now be free and users will be charged $7 per month for five private repos and $25 for organisations to maintain 10 private repos. 

March

Adobe CEO Shantanu Narayen and Microsoft CEO Satya Nadella revealed additional details about the Open Data Initiative that will help customers create new connections across previously siloed data, more seamlessly garner intelligence, and ultimately better serve brands with an improved view of their customer interactions.

Google’s AI research division, in March, open sourced GPipe, a library for efficiently training giant neural networks using pipeline parallelism. It was released under Lingvo, a TensorFlow framework for sequence modelling.

April

At the Cloud Next’19 event held in April at San Francisco, Google launched its very own AI platform that aims at making the life of machine learning developers, data scientists and data engineers easy. This AI Platform supports Kubeflow, Google’s open-source platform, which lets the users build portable ML pipelines that can be run on-premises or on Google Cloud without significant code changes. 

Researchers from IIT Delhi developed an AI system that will help medical practitioners detect health conditions like malaria, TB, cervical cancer and intestinal parasites in milliseconds using a low-powered electronic hardware system. 

Amazon announced their plan to make available a massive Topical Chat dataset. This data is reportedly a corpus of human-human social conversations collected from crowd workers that will be released publicly in mid-September.

May

Microsoft announced a series of new Azure services and developer technologies that put advanced capabilities spanning artificial intelligence, mixed reality, internet of things and blockchain in the hands of developers. Microsoft is also going to release Jupyter-like notebooks for advanced users.

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Amazon Web Services, the cloud computing arm of the e-commerce giant, launched an ML service for automated text and data extraction. The service, known as Textract, is fully cloud-hosted and managed by AWS, and allows users to parse various forms of data easily.

June

Facebook AI team behind PyTorch released PyTorch hub to help developers assist with implementing the breakthroughs. PyTorch hub is a simple API and workflow that provides the basic building blocks for improving machine learning research reproducibility.

September

Deloitte announced the launch of a first-of-its-kind public data visualization tool, Open Source Compass (OSC) intended to help C-suite leaders, product managers and software engineers understand the trajectory of open source development and emerging technologies.

October

Google introduced a number of enhancements to their Vision AI portfolio to help even more customers take advantage of artificial intelligence. One of the biggest enhancements is the fact that AutoML Vision Edge now detects objects.  It can now perform object detection as well as image classification—all directly on the edge device. 

November

OpenAI came up with a breakthrough language model that could generate natural language texts similar to humans. The GPT-2 can generate words, build sentences and paragraphs that are indistinguishable from human-generated content.

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