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10 highest-paying IT skills for 2024

CIO

These roles include data scientist, machine learning engineer, software engineer, research scientist, full-stack developer, deep learning engineer, software architect, and field programmable gate array (FPGA) engineer. It is used to execute and improve machine learning tasks such as NLP, computer vision, and deep learning.

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New Series: Creating Media with Machine Learning

Netflix Tech

By Vi Iyengar , Keila Fong , Hossein Taghavi , Andy Yao , Kelli Griggs , Boris Chen , Cristina Segalin , Apurva Kansara , Grace Tang , Billur Engin , Amir Ziai , James Ray , Jonathan Solorzano-Hamilton Welcome to the first post in our multi-part series on how Netflix is developing and using machine learning (ML) to help creators make better media?—?from

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All about Machine Learning

Hacker Earth Developers Blog

In our third episode of Breaking 404 , we caught up with Srivatsan Ramanujam, Director of Software Engineering: Machine Learning, Salesforce to discuss everything about Machine Learning and the best practices for ML engineers to excel in their careers. Again, focus on Data Science and Machine Learning.

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Emperia is helping brands like Bloomingdales build shopping experiences in VR

TechCrunch

Does the average person want to shop for apparel in virtual reality (VR)? Enter Emperia , an “immersive” retail startup that — to its credit — has already created virtual stores for brands including Bloomingdales, Dior, Ralph Lauren and Lacoste. A virtual store created with Emperia’s platform.

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3 technology trends set to revolutionize retail

CIO

That means delivering a seamless initial contact online or in-store, removing any issue related to adding products to a virtual or physical cart, and making checkout and payment processes intuitive and easy to complete. Realistic 3D visualizations provide a good idea of how a product would look like when viewed from different angles.

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Blackshark.ai’s digital twin of Earth attracts $20M in funding

TechCrunch

The basis of their technique is turning widely available 2D imagery into accurate 3D representations with machine learning, a bit of smart guesswork, and a lot of computing power. Using all this it creates a plausible 3D reconstruction of the building. But that also necessitates the aforementioned 2D-to-3D method.

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How Nvidia became a trillion-dollar company

CIO

Its founders spotted that generating 3D graphics in video games—then a fast-growing market—placed highly repetitive, math-intensive demands on PC central processing units (CPUs). Although Nvidia’s first chips were used to enhance 3D gaming, the manufacturing industry is also interested in 3D simulations, and its pockets are deeper.