December 14, 2024

Why AI Art Protections Aren’t as Strong as They Seem | HackerNoon

Table of Links Abstract and 1. Introduction Background and Related Work Threat Model Robust Style Mimicry Experimental Setup Results 6.1 Main Findings: All Protections are Easily Circumvented 6.2 Analysis Discussion and Broader Impact, Acknowledgements, and References A. Detailed Art Examples B. Robust Mimicry Generations C. Detailed Results D. Differences with Glaze Finetuning E. Findings on Glaze 2.0 F. Findings on Mist v2 G. Methods for Style Mimicry H. Existing Style Mimicry Protections I. Robust Mimicry

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Synthetic data has its limits — why human-sourced data can help prevent AI model collapse

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More My, how quickly the tables turn in the tech world. Just two years ago, AI was lauded as the “next transformational technology to rule them all.” Now, instead of reaching Skynet levels and taking over the world, AI is, ironically, degrading.  Once the harbinger of a new era of intelligence, AI is now tripping over its

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Software

Join Lumoz zkVerifier Node Mining and Share 2.5 Billion MOZ Rewards | HackerNoon

Abstract: The Lumoz Node Network and MOZ staking system officially launched on December 13, 2024, at 16:00 UTC+8. Opportunities for the community and node users to participate in the zkVerifier network and MOZ staking are now fully open. By running zkVerifier Nodes, staking MOZ, and delegating licenses, users can collectively share 25% of the total MOZ token mining rewards! With the successful launch of the mainnet and completion of the TGE, Lumoz has received widespread

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Software

Zero-shot Prompts for Logical Reasoning Tasks in Biological Pathways | HackerNoon

Table of Links Abstract and Introduction SylloBio-NLI Empirical Evaluation Related Work Conclusions Limitations and References A. Formalization of the SylloBio-NLI Resource Generation Process B. Formalization of Tasks 1 and 2 C. Dictionary of gene and pathway membership D. Domain-specific pipeline for creating NL instances and E Accessing LLMs F. Experimental Details G. Evaluation Metrics H. Prompting LLMs – Zero-shot prompts I. Prompting LLMs – Few-shot prompts J. Results: Misaligned Instruction-Response K. Results: Ambiguous Impact of

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How Are Artists Protecting Their Unique Styles from Imitation in AI Art? | HackerNoon

Table of Links Abstract and 1. Introduction Background and Related Work Threat Model Robust Style Mimicry Experimental Setup Results 6.1 Main Findings: All Protections are Easily Circumvented 6.2 Analysis Discussion and Broader Impact, Acknowledgements, and References A. Detailed Art Examples B. Robust Mimicry Generations C. Detailed Results D. Differences with Glaze Finetuning E. Findings on Glaze 2.0 F. Findings on Mist v2 G. Methods for Style Mimicry H. Existing Style Mimicry Protections I. Robust Mimicry

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AR/VR

The best of The Game Awards and the redemption of Geoff Keighley | The DeanBeat

Geoff Keighley redeemed himself with his tenth anniversary show for The Game Awards. It was an evening full of memorable moments, new game trailers and well-deserved awards. I was in the Peacock theater for more than three hours to witness it all on Thursday night. We held our own GamesBeat Insider Series: Hollywood and Games event on the same day, but I managed to churn out 17 stories on the day of gaming’s biggest celebration.

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Software

The Science Behind AI’s Ability to Recreate Art Styles | HackerNoon

Table of Links Abstract and 1. Introduction Background and Related Work Threat Model Robust Style Mimicry Experimental Setup Results 6.1 Main Findings: All Protections are Easily Circumvented 6.2 Analysis Discussion and Broader Impact, Acknowledgements, and References A. Detailed Art Examples B. Robust Mimicry Generations C. Detailed Results D. Differences with Glaze Finetuning E. Findings on Glaze 2.0 F. Findings on Mist v2 G. Methods for Style Mimicry H. Existing Style Mimicry Protections I. Robust Mimicry

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AI

How Have Data Science Interviews Changed Over 4 Years?

An aggregated look on the differences between then & now: 2020 vs 2024 — some big frustrations and positive learnings. Matt Przybyla · Follow Published in Towards Data Science · 7 min read · 11 hours ago — Yes this is actually a screenshot of my own LinkedIn [1]. Table of Contents Introduction Application Process Interview Process Summary References Introduction This article is intended for data scientists looking for a company change, people considering applying

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Hardware

Here’s The Nintendo Switch 2 And Its Dimensions, Leaked By Dbrand

Dbrand, the accessories maker famous for its cheeky marketing, has potentially spilled the beans on one of the most hotly anticipated gaming devices, the Nintendo Switch 2. Known for crafting cases and skins for phones as well as gaming devices like the Steam Deck and the original Switch, Dbrand has now unveiled a new Killswitch case—this time for what appears to be Nintendo’s next-gen console. The dedicated page on Dbrand’s website is a single-screen teaser

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Robotics

Diversity and inclusion can accelerate robotics innovation, finds Max Planck study – The Robot Report

A German study outlines the benefits of having a diverse team for robotics research. | Source: Adobe Stock The field of robotics is highly interdisciplinary, encompassing mechanical and electrical engineering, materials science, computer science, neuroscience, and biology. If that academic diversity is paired with workforce diversity, it could drive more creativity and innovation, according to a recent study from the Max Planck Institute for Intelligent Systems, or MPI-IS. The Stuttgart, Germany-based institute identified seven ways

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