Normally, you don’t need to be a fortune teller to predict Oscar winners, but the Academy has sprung a few surprises in recent years.

Recently, a team of data scientists tested whether their machine learning model could outsmart the bookmakers — with mixed results.

The boffins behind the BigML machine learning platform made their predictions with a Deepnets model, an optimised implementation of the Deep Neural Networks supervised learning technique.

Its biggest miss was in the hotly-contested best picture category. The model correctly rejected the bookie’s favourite, 1917, to pick an outsider. But it ultimately went for the wrong one, plumping for Once Upon a Time in Hollywood ahead of surprise winner Parasite.

One of the great things about the current wave of AI innovation is the large number of open source tools, technologies, and frameworks.

From TensorFlow to Python, Kafka to PyTorch, there’s an explosion in diversity of data science and big data tool sets.

However, when it comes to putting these tools together and building real-world AI applications, regular companies suffer from a serious technology gap compared to technology firms.

Here’s an interesting peice from Datanami on how to make AI work in the enterpise.

Many of the latest open source AI technologies are not known for being easy to work with, and typically require highly skilled data scientists to use. This puts a cap the applicability of the AI tech, and limits its use to companies that have the budget to hire experienced data scientists.

Here’s an interesting AI/geospatial talk posted by Esri Events

In 2018, the DoD’s Joint Artificial Intelligence Center (JAIC) selected Esri to operationalize artificial intelligence in a geospatial context. See how Esri is working with the JAIC to develop the workflows and AI models to turn imagery into actionable products.

ResearchMoz.us presents a comprehensive study on Machine Learning Software Market share, size, growth aspects, and major players.

The report comprises brief information on the regional competitive landscape, market trends, and drivers, opportunities and challenges, distributors, sales channels, risks & entry barriers, and more.

TL;DR: the future still looks bright for machine learning.

The report forecast global Machine Learning Software Market to grow to reach xx Million USD in 2019 with a CAGR of xx% during the period 2020-2026. 

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The Vision AI DevKit (https://aka.ms/iotshow/visionaidevkit) is a smart camera device powered by Azure IoT Edge. Equiped with a camera and microphones, it allows developing proof of concept (or even actual) projects implementing advanced image and sound analytics directly on the device.In a previous episode (https://aka.ms/iotshow/185), Mahesh Yadav showed us the unboxing and first time experience with the device.

In this new episode, Mahesh is back to show us how you can train and deploy new AI models on the device in a matter of minutes.

Check out the Vision AI devkit site to learn more and take it for a spin: https://aka.ms/iotshow/visionaidevkit

Lloyd Danzig, a leading expert in the field of Artificial Intelligence, explores ethical issues of automation. Lloyd is the Chairman & Founder of the International Consortium for the Ethical Development of Artificial Intelligence, a non-profit NGO dedicated to ensuring that rapid developments in A.I. are made with a keen eye toward the long-term interests of humanity.

He is a distinguished member of CompTIA’s AI Advisory Council, through which the world’s 20 most influential thought leaders establish best practices to foster technological development while protecting consumers.

The Spark + AI Summit is the largest data and machine learning conference bringing together engineers, scientists, developers, analysts and leaders from around the world.

“Over four days we’ll gather the greatest minds in our industry to shape the future of big data, analytics and AI and share knowledge through training, over 180 talks and networking events. Spark + AI Summit has become the destination for data teams to collaborate on solutions to solve the world’s toughest problems,” said Ali Ghodsi, cofounder and CEO at Databricks.