AWS Machine Learning Blog

OCTOBER 6, 2023

Large language models (LLMs) are revolutionizing fields like search engines, natural language processing (NLP), healthcare, robotics, and code generation. Next, we recommend “Interstellar” (2014), a thought-provoking and visually stunning film that delves into the mysteries of time and space.

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IBM Journey to AI blog

NOVEMBER 13, 2023

Developed internally at Google and released to the public in 2014, Kubernetes has enabled organizations to move away from traditional IT infrastructure and toward the automation of operational tasks tied to the deployment, scaling and managing of containerized applications (or microservices ).

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AWS Machine Learning Blog

JANUARY 25, 2023

Apart from supporting explanations for tabular data, Clarify also supports explainability for both computer vision (CV) and natural language processing (NLP) using the same SHAP algorithm. It is constructed by selecting 14 non-overlapping classes from DBpedia 2014.

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Chatbots Life

MAY 16, 2023

Master of Code Global (MOCG) is a certified partner of Microsoft and AWS and has been recognized by LivePerson, Inc. Deeper Insights Year Founded : 2014 HQ : London, UK Team Size : 11–50 employees Clients : Smith and Nephew, Deloitte, Breast Cancer Now, IAC, Jones Lang-Lasalle, Revival Health. Elite Service Delivery partner of NVIDIA.

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AWS Machine Learning Blog

NOVEMBER 15, 2023

As an example downstream application, the fine-tuned model can be used in pre-labeling workflows such as the one described in Auto-labeling module for deep learning-based Advanced Driver Assistance Systems on AWS. Start building the future with AWS today.

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ODSC - Open Data Science

JANUARY 29, 2024

GANs, introduced in 2014 paved the way for GenAI with models like Pix2pix and DiscoGAN. While AWS is usually the winner when it comes to data science and machine learning, it’s Microsoft Azure that’s taking the lead for prompt engineering job descriptions. NLP skills have long been essential for dealing with textual data.

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DagsHub

OCTOBER 23, 2024

Large Language Models We engineer LLMs like Gemini and GPT-4 to process and understand unstructured text data. They can generate human-like text, summarize documents, and answer questions, making them essential for natural language processing and text analytics tasks. Our model achieves 28.4 after training for 3.5

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