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Achieving scalable and distributed technology through expertise: Harshit Sharan’s strategic impact

Dataconomy

in Computer Science and Engineering with a stellar GPA of 8.61, Harshit set a high bar for aspiring innovators. In 2015, seeking greater challenges, he transitioned to the marketing technology domain, marking a pivotal career shift. During competitions, Harshit developed technology skills. and M.Tech.)

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Who is Ilya Sutskever, meet the man who fired Sam Altman

Dataconomy

in computer science in 2013 under the guidance of Geoffrey Hinton. His work on the sequence-to-sequence learning algorithm and contributions to TensorFlow underscore his commitment to pushing AI’s boundaries. But, in 2015, he takes a leap of faith, leaving Google to co-found OpenAI.

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easy-explain: Explainable AI for YoloV8

Towards AI

(Left) Photo by Pawel Czerwinski on Unsplash U+007C (Right) Unsplash Image adjusted by the showcased algorithm Introduction It’s been a while since I created this package ‘easy-explain’ and published on Pypi. A few weeks ago, I needed an explainability algorithm for a YoloV8 model. PLoS ONE 10(7), e0130140 (2015) [2] Montavon, G.,

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Llama 4 family of models from Meta are now available in SageMaker JumpStart

AWS Machine Learning Blog

billion, representing a significant increase of approximately 223% over the 7-year period. ### Net Income Growth | Year | Net Income (in billion USD) | | | | | 2014 | 0.236 | | 2015 | 0.596 | | 2016 | 2.37 | | 2017 | 3.03 | | 2018 | 10.07 | | 2019 | 11.59 | | 2020 | 18.68 | | 2021 | 33.4 | | 2022 | 18.7 billion to a projected $574.78

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Faster R-CNNs

PyImageSearch

One of the most popular deep learning-based object detection algorithms is the family of R-CNN algorithms, originally introduced by Girshick et al. Since then, the R-CNN algorithm has gone through numerous iterations, improving the algorithm with each new publication and outperforming traditional object detection algorithms (e.g.,

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Build a scalable AI assistant to help refugees using AWS

AWS Machine Learning Blog

For over a decade in the world of technology, Taras has led everything from tight-knit agile teams of 5 or more to a company of 90 people that became the best small IT company in Ukraine under 100 people in 2015.

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Unlocking generative AI for enterprises: How SnapLogic powers their low-code Agent Creator using Amazon Bedrock

AWS Machine Learning Blog

Data retrieval and augmentation – When a query is initiated, the Vector Database Snap Pack retrieves relevant vectors from OpenSearch Service using similarity search algorithms to match the query with stored vectors. He focuses on Deep learning including NLP and Computer Vision domains.

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