Author Archives: Shraddha Goled - Page 32

02 Jul

MLOps Vs DevOps: A Comparative Analysis

Advances in machine learning and data science have led to the creation of new branches. The new specialisations are often rooted in the same basic principles and have overlapping functionalities. For example, MLOps and DevOps. In this article, we discuss why the two are different and cannot be used interchangeably. DevOps: Development + operations DevOps…

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01 Jul

The Linux Foundation Launches New License Agreement For Open-Source Datasets

The Linux Foundation has announced the release of the new license agreement, CDLA-Permissive-2.0. It’s a short, simple, and broad agreement to enable wider and more open use of data, particularly with respect to artificial intelligence and machine learning models. IBM and Microsoft have already made their datasets available under CDLA-Permissive 2.0. CDLA-Permissive 2.0 In October…

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29 Jun

Top Distributed Training Frameworks In 2021

In distributed training, the workload is shared between mini processors called the worker nodes. The nodes run in parallel to speed up the model training. Traditionally, distributed training has been used for machine learning models.  But of late, it’s making inroads into compute-intensive tasks such as deep learning to train deep neural networks. Below, we…

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27 Jun

Tesla’s Karpathy On The Tech Behind Its Autopilot Project

“We are in bad shape when it comes to transportation. We have these metallic objects travelling really quickly with really high kinetic energy. We are putting meat in the control system; it is quite undesirable. It fundamentally comes down to people not being too good at driving. They get into a lot of trouble,” said…

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24 Jun

How Transformers Are Making Headway In Reinforcement Learning

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In 2017, Google researchers announced Transformers to the world in a NIPS paper titled “Attention is All You Need”. The self-attention mechanism-based novel neural network architecture has since been used in several NLP applications, GPT-3 being a good case in point. Transformers–thanks to their ability to integrate information over long time horizons and scale to…

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24 Jun

Is CUDA NVIDIA’s Competitive Moat?

NVIDIA designed GeForce 256, a chip company widely marketed as the ‘world’s first GPU’, in 1999. The single-chip processor with an integrated transform, lighting, and rendering engine could process a minimum of 10 million polygons per second. Since then, the researchers and scientists have leveraged the floating point performance of GeForce 256 for general-purpose computing.…

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