September 10, 2024

AI

Automate Video Chaptering with LLMs and TF-IDF

Transform raw transcripts into well-structured documents Yann-Aël Le Borgne · Follow Published in Towards Data Science · 12 min read · 1 day ago — Photo by Jakob Owens on Unsplash Video chaptering is the task of segmenting a video into distinct chapters. Besides its use as a navigation aid as seen with YouTube chapters, it is also core to a series of downstream applications ranging from information retrieval (e.g., RAG semantic chunking), to referencing

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AI

How I Streamline My Research and Presentation with LlamaIndex Workflows

An example of orchestrating AI workflow with reliability, flexibility, and controllability Lingzhen Chen · Follow Published in Towards Data Science · 16 min read · 3 hours ago — LlamaIndex recently introduced a new feature: Workflows. It’s very useful for those who want to create an AI solution that’s both reliable and flexible. How so? Because it allows you to define customized steps with a control flow. It supports loops, feedback, and error handling. It’s

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AI

How to Create a Powerful AI Email Search for Gmail with RAG

Learn how you can develop an application to search emails using RAG Eivind Kjosbakken · Follow Published in Towards Data Science · 13 min read · 3 hours ago — In this article, I will show you how you can develop the MailDiscoverer application to search Gmail emails using RAG. First, I will show you how to set up the authentication pipeline to access user’s emails (if consent is given). The emails are then embedded

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Edge chip maker SiMa.ai launches Modalix to bring multimodal gen AI everywhere

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Edge computer chip and software startup SiMa.ai, fresh off a $70 million funding round from industry heavyweights including Dell Technologies Capital, is expanding its foothold in the edge AI market with the release of a new, smaller, lower power chip: MLSoC Modalix. At 6 nanometers, it comes in way smaller than the San Jose, California-based startup’s

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How Transliteration Enhances Machine Translation: The HeArBERT Approach | HackerNoon

Authors: (1) Aviad Rom, The Data Science Institute, Reichman University, Herzliya, Israel; (2) Kfir Bar, The Data Science Institute, Reichman University, Herzliya, Israel. Table of Links Abstract and Introduction Related Work Methodology Experimental Settings Results Conclusion and Limitations Bibliographical References 3. Methodology We begin by pre-training a new language model using texts written in both Arabic and Hebrew. This model, named HeArBERT, is subsequently finetuned to enhance performance in machine translation between Arabic and Hebrew.

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Software

HeArBERT: A Bilingual Model for Arabic-Hebrew Translation Using Transliteration | HackerNoon

Authors: (1) Aviad Rom, The Data Science Institute, Reichman University, Herzliya, Israel; (2) Kfir Bar, The Data Science Institute, Reichman University, Herzliya, Israel. Table of Links Abstract and Introduction Related Work Methodology Experimental Settings Results Conclusion and Limitations Bibliographical References K et al. (2020) have suggested that structural similarity of languages is essential for language model’s multilingual generalization capabilities. Their suggestion was further discussed by Dufter and Schütze (2020), who highlighted the essential components for

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Robotics

GelSight, Flexxbotics to offer joint system for robotic nondestructive testing – The Robot Report

Listen to this article GelSight & Flexxbotics are partnering for robot-enabled nondestructive testing. | Source: GelSight, Flexxbotics GelSight has partnered with Flexxbotics to jointly provide a system for nondestructive testing, or NDT, with autonomous process control. It incorporates GelSight’s tactile sensing technology into Flexxbotics’ controls for robotic machine tending. The companies said the system provides precise quality inspection and digital thread traceability that can reduce time to inspect by 40% or more. “In a lot

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Software

Training a Bilingual Language Model by Mapping Tokens onto a Shared Character Space | HackerNoon

Authors: (1) Aviad Rom, The Data Science Institute, Reichman University, Herzliya, Israel; (2) Kfir Bar, The Data Science Institute, Reichman University, Herzliya, Israel. Table of Links Abstract and Introduction Related Work Methodology Experimental Settings Results Conclusion and Limitations Bibliographical References Abstract We train a bilingual Arabic-Hebrew language model using a transliterated version of Arabic texts in Hebrew, to ensure both languages are represented in the same script. Given the morphological, structural similarities, and the extensive

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MiniMax’s AI video tool can create Star Wars battles in seconds – here’s why that matters

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More A new Chinese startup has taken the artificial intelligence world by storm, capturing the attention of tech enthusiasts and industry professionals alike. MiniMax—backed by tech giants Alibaba and Tencent—has thrust itself into the spotlight with its text-to-video AI model, challenging established players and potentially reshaping the landscape of generative AI. [embedded content] The company’s sudden rise

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AR/VR

Agentic AI: A deep dive into the future of automation

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Beyond generative AI The most transformative promise of AI has always been its potential for autonomy, to create systems that can act intelligently on their own without human supervision. However, this kind of “Agentic AI” has remained out of reach for most enterprise use cases, until now. Across industries, two related trends will change our perception

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