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Watermarking AI-generated text and video with SynthID

Technologies Published 14 May 2024 Announcing our novel watermarking method for AI-generated text and video, and how we’re bringing SynthID to key Google products Generative AI tools — and the large language model technologies behind them — have captured the public imagination. From helping with work tasks to enhancing creativity, these tools are quickly becoming …

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Google Gemini Is Entering the Advent of Code Challenge | by Heiko Hotz | Dec, 2024

The Chief Historian is always present for the big Christmas sleigh launch, but nobody has seen him in months! Last anyone heard, he was visiting locations that are historically significant to the North Pole; a group of Senior Historians has asked you to accompany them as they check the places they think he was most …

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Around the Prompt – Simon Willison: The Future of Open Source and AI

In this conversation, Simon Willison discusses the intersection of AI, Open Source, and journalism, emphasizing the importance of tools like Dataset in enhancing data journalism. He reflects on his journey from developing Django to his current work with AI, highlighting the role of open source in software development. Willison shares insights on how AI can …

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Introducing Veo and Imagen 3 generative AI tools

Responsible from design to deployment We’re mindful about not only advancing the state of the art, but doing so responsibly. So we’re taking measures to address the challenges raised by generative technologies and helping enable people and organizations to responsibly work with AI-generated content. For each of these technologies, we’ve been working with the creative …

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Making News Recommendations Explainable with Large Language Models | by Alex Held | Nov, 2024

A prompt-based experiment to improve both accuracy and transparent reasoning in content personalization. Deliver relevant content to readers at the right time. Image by author. At DER SPIEGEL, we are continually exploring ways to improve how we recommend news articles to our readers. In our latest (offline) experiment, we investigated whether Large Language Models (LLMs) …

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AI Predictive Analytics: Transforming Business Decision-Making

The business world stands on the cusp of a revolution, driven by the transformative power of AI-powered predictive analytics. This technology isn’t just another fleeting trend; it represents a fundamental shift in how companies foresee and shape their futures. As we explore the intricacies of this paradigm shift, we’ll explore how AI is reshaping business …

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Flash 1.5, Gemma 2 and Project Astra

1.5 Flash excels at summarization, chat applications, image and video captioning, data extraction from long documents and tables, and more. This is because it’s been trained by 1.5 Pro through a process called “distillation,” where the most essential knowledge and skills from a larger model are transferred to a smaller, more efficient model. Read more …

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The Intuition behind Concordance Index — Survival Analysis | by Antonieta Mastrogiuseppe | Nov, 2024

Ranking accuracy versus absolute accuracy Taken by the author and her Border Collie. “Be thankful for what you have. Be fearless for what you want” How long would you keep your Gym membership before you decide to cancel it? or Netflix if you are a series fan but busier than usual to allocate 2 hours …

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Introducing the Frontier Safety Framework

Our approach to analyzing and mitigating future risks posed by advanced AI models Google DeepMind has consistently pushed the boundaries of AI, developing models that have transformed our understanding of what’s possible. We believe that AI technology on the horizon will provide society with invaluable tools to help tackle critical global challenges, such as climate …

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Addressing Missing Data. Understand missing data patterns (MCAR… | by Gizem Kaya | Nov, 2024

Understand missing data patterns (MCAR, MNAR, MAR) for better model performance with Missingno In an ideal world, we would like to work with datasets that are clean, complete and accurate. However, real-world data rarely meets our expectation. We often encounter datasets with noise, inconsistencies, outliers and missingness, which requires careful handling to get effective results. …

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