Favorite This post is co-authored with Richard Alexander and Mark Hallows from Arup. Arup is a global collective of designers, consultants, and experts dedicated to sustainable development. Data underpins Arup consultancy for clients with world-class collection and analysis providing insight to make an impact. The solution presented here is to
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Shared by AWS Machine Learning September 18, 2023
Favorite Machine learning (ML) is becoming increasingly complex as customers try to solve more and more challenging problems. This complexity often leads to the need for distributed ML, where multiple machines are used to train a single model. Although this enables parallelization of tasks across multiple nodes, leading to accelerated
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Shared by AWS Machine Learning September 18, 2023
Favorite Large language model (LLM) agents are programs that extend the capabilities of standalone LLMs with 1) access to external tools (APIs, functions, webhooks, plugins, and so on), and 2) the ability to plan and execute tasks in a self-directed fashion. Often, LLMs need to interact with other software, databases,
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Shared by AWS Machine Learning September 15, 2023
Favorite Posted by Haolin Jia, Software Engineer, and Qifei Wang, Senior Software Engineer, Core ML In recent years, we have witnessed rising interest across consumers and researchers in integrated augmented reality (AR) experiences using real-time face feature generation and editing functions in mobile applications, including short videos, virtual reality, and
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Shared by Google AI Technology September 15, 2023
Favorite This post takes you through the most common challenges that customers face when searching internal documents, and gives you concrete guidance on how AWS services can be used to create a generative AI conversational bot that makes internal information more useful. Unstructured data accounts for 80% of all the
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Shared by AWS Machine Learning September 14, 2023
Favorite Today, generative AI models cover a variety of tasks from text summarization, Q&A, and image and video generation. To improve the quality of output, approaches like n-short learning, Prompt engineering, Retrieval Augmented Generation (RAG) and fine tuning are used. Fine-tuning allows you to adjust these generative AI models to
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Shared by AWS Machine Learning September 14, 2023
Favorite “Data locked away in text, audio, social media, and other unstructured sources can be a competitive advantage for firms that figure out how to use it“ Only 18% of organizations in a 2019 survey by Deloitte reported being able to take advantage of unstructured data. The majority of data,
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Shared by AWS Machine Learning September 14, 2023
Favorite Posted by Gabriel Barcik and Duc-Hieu Tran, Research Engineers, Google Research In today’s digital age, smartphones and desktop web browsers serve as the primary tools for accessing news and information. However, the proliferation of website clutter — encompassing complex layouts, navigation elements, and extraneous links — significantly impairs both
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Shared by Google AI Technology September 14, 2023
Favorite [SPONSOR OPINION] By Heather Meeker, OSS Capital Machine learning has been around for a long time. But in late 2022, recent advancements in deep learning and large language models started to change the game and come into the public eye. And people started thinking, “We love Open Source software,
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Shared by voicesofopensource September 14, 2023
Favorite There’s still a few days left for you to take part in the 2023 Knoco global survey of KM. Thank you if you have already taken part. If you haven’t, we would love it if you could join too! Please follow the link to take part, and please forward
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Shared by Nick Milton September 14, 2023