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Scarlett Johansson initiates legal proceedings over AI ad misuse
Scarlett Johansson has filed a lawsuit against an AI application called Lisa AI: 90’s Yearbook & Avatar for unauthorized use of her image and name in a promotional video. Her representatives have taken legal action and the controversial advertisement has been withdrawn. This is not the first time Johansson has dealt with unauthorized use of…
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AI-assisted final Beatles track, “Now and Then,” is released
Universal Music Group released the Beatles’ final track “Now and Then,” which features AI-reconstructed vocals by John Lennon. The release is accompanied by a documentary that showcases the technology behind the production. The documentary reveals how Peter Jackson developed software to isolate Lennon’s voice from a demo recording on a cassette tape from the 1970s.…
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Australian academics apologize for false AI-generated claims
Australian academics apologize for using false information generated by an AI chatbot, Bard, in their submission to an Australian parliamentary inquiry. The academics were lobbying for the breakup of the big four auditing firms and included inaccurate claims about misconduct by these firms. The auditing firms pointed out the inaccuracies, but cannot pursue defamation cases…
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My Experience with DevOps and DataOps
In this article, the author discusses their experience working as a data engineer in both a DevOps-focused role and an analytics engineering role. They highlight the differences between DevOps and DataOps, including the focus on software as a product in DevOps and data quality in DataOps. The key metrics of success for DevOps are downtime…
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5 Visualizations with Python to Show Simultaneous Changes in Geospatial Data
This article provides ideas and techniques for expressing simultaneous changes in geospatial data using Python. It covers various chart types, including choropleth maps, bubble charts, pie charts, bar charts, and line charts. The author explains how to obtain and plot geospatial data and includes examples and code snippets throughout the article. The goal is to…
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Set These Boundaries for a Better-Quality Work-Life Balance as a Data Scientist In 2024
The text discusses five boundaries that can help achieve a better work-life balance as a data scientist in 2024. These boundaries include setting up a documentation system, allowing for longer project timelines, refusing unrealistic deadlines, avoiding overtime for artificial deadlines, and prioritizing quality over speed in data analysis projects.
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This Artificial Intelligence-Focused Chip Redefines Efficiency: Doubling Down on Energy Savings by Unifying Processing and Memory
The rise in demand for data-centric local intelligence has highlighted the need for autonomous data analysis at the edge. Edge-AI devices, such as wearables and smartphones, represent the next phase of growth in the semiconductor industry. However, these devices face the challenge of the von Neumann bottleneck, which limits their ability to process data locally.…
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Beyond Fact or Fiction: Evaluating the Advanced Fact-Checking Capabilities of Large Language Models like GPT-4
Researchers from the University of Zurich evaluated the performance of Large Language Models (LLMs), specifically GPT-4, in autonomous fact-checking. While LLMs show promise in fact-checking with contextual information, their accuracy varies based on query language and claim veracity. Further research is needed to improve understanding of LLM capabilities and limitations in fact-checking tasks.
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Revolutionizing AI’s Listening Skills: Tsinghua University and ByteDance Unveil SALMONN – A Groundbreaking Multimodal Neural Network for Advanced Audio Processing
Researchers from Tsinghua University and ByteDance have developed SALMONN, a multimodal language model (LLM) that can recognize and comprehend various audio inputs, including voice, audio events, and music. They also propose a low-cost activation tuning technique to activate cross-modal emergent skills and reduce catastrophic forgetting. SALMONN performs well on a range of hearing tasks.
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Enhancing Factuality in AI: This AI Research Introduces Self-RAG for More Accurate and Reflective Language Models
SELF-RAG is a framework that enhances large language models by dynamically retrieving relevant information and reflecting on its generations. It significantly improves quality, factuality, and performance on various tasks, outperforming other models. SELF-RAG is effective in open-domain question-answering, reasoning, fact verification, and long-form content generation. Further research and refinement can enhance output accuracy and address…