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IBM and Microsoft partnership accelerates sustainable cloud modernization

IBM Journey to AI blog

IBM’s recommendations included API-specific improvements, bot UX optimization, workflow optimization, DevOps microservices and design consideration, and best practices for Azure manage services.

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10 edge computing innovators to keep an eye on in 2023

Dataconomy

The strategic value of IoT development and data analytics Sierra Wireless Sierra Wireless , a wireless communications equipment designer and service provider, has been honing its focus on IoT software and managed services following its acquisition of M2M Group, a cluster of companies dedicated to IoT connectivity, in 2020.

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A Comprehensive Guide to the main components of Big Data

Pickl AI

According to a report by Statista, the global data sphere is expected to reach 180 zettabytes by 2025 , a significant increase from 33 zettabytes in 2018. Processing frameworks like Hadoop enable efficient data analysis across clusters. Introduction In today’s digital age, the volume of data generated is staggering.

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A Comprehensive Guide to the Main Components of Big Data

Pickl AI

According to a report by Statista, the global data sphere is expected to reach 180 zettabytes by 2025 , a significant increase from 33 zettabytes in 2018. Processing frameworks like Hadoop enable efficient data analysis across clusters. Introduction In today’s digital age, the volume of data generated is staggering.

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A review of purpose-built accelerators for financial services

AWS Machine Learning Blog

The following figure illustrates the idea of a large cluster of GPUs being used for learning, followed by a smaller number for inference. In 2018, other forms of PBAs became available, and by 2020, PBAs were being widely used for parallel problems, such as training of NN.

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5000x Generative AI: Intro, Overview, Models, Prompts, Technology, Tools, Comparisons & the Best…

Mlearning.ai

Traditional AI can recognize, classify, and cluster, but not generate the data it is trained on. The foundations for today’s generative language applications were elaborated in the 1990s ( Hochreiter , Schmidhuber ), and the whole field took off around 2018 ( Radford , Devlin , et al.). Let’s play the comparison game.

AI 98
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Generative AI in the Enterprise

O'Reilly Media

While the source code and weights for the LLaMA models are available online, the LLaMA models don’t yet have a public API backed by Meta—although there appear to be several APIs developed by third parties, and both Google Cloud and Microsoft Azure offer Llama 2 as a service. We expect others to follow.

AI 135