A journey into Kindle AI slop hell

Kindle's algorithms appear to have identified new mothers as a market for AI-generated books, evident from the shift in ad recommendations to children's bedtime stories that seemingly cater to adults as well. These books, with lifeless covers and generic themes, are easily distinguishable as AI-generated due to their basic storytelling and inconsistent details. Intriguingly, some books even vanish after being advertised, only to reappear with slight modifications, hinting at possible real-time content generation based on user behavior. The phenomenon raises questions about Amazon’s potential use of generative models to churn out low-cost content, possibly gaming their own marketplace while doing so.

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Linear Algebra 101 for AI/ML

The "Linear Algebra 101 for AI/ML" is a basic overview of the Linear Algebra behind Gen AI. Key concepts covered include scalars, vectors, and matrices along with their mathematical operations. The guide incorporates practical coding exercises using PyTorch.

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Mozilla roll out first AI features in Firefox Nightly

Firefox is offering new AI features in Firefox Nightly. Notable additions include local alt-text generation for PDF images, providing superior privacy by processing data locally. Firefox also introduces an opt-in experiment enabling users to access popular AI services like ChatGPT and Google Gemini directly from the browser sidebar for tasks like summarizing and simplifying information.

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Generative AI Misuse: A Taxonomy of Tactics and Insights from Real-World Data

This paper introduces a taxonomy of misuse tactics for generative, multimodal artificial intelligence (GenAI), drawing from previously reported misuse incidents between January 2023 and March 2024. Through qualitative analysis of around 200 incidents, it identifies key patterns, motivations, and strategies used by attackers. It details how GenAI systems are leveraged maliciously across various modalities such as image, text, audio, and video.

ArXiv

Should AI optimize your code? A studio

This paper compares GPT-4.0 and CodeLlama-70B with traditional optimizing compilers (CETUS, PLUTO, and ROSE) to see how well they optimize code. Using both Chain of Thought (CoT) and Instruction Prompting (IP), it assessed performance across challenging optimization patterns. CodeLlama-70B showed strong potential, achieving up to 2.1x speedup, but often produced incorrect code for larger inputs. CETUS led among traditional compilers with a 1.9x speedup. No major differences were found between the CoT and IP methods. Automated verification methods are suggested to handle correctness in LLM-generated code.

ArXiv

DataComp-LM: In search of the next generation training sets for language models

DataComp for Language Models (DCLM) is introduced as a testbed for improving language models through controlled dataset experiments. It provides a 240T token corpus from Common Crawl, effective pretraining recipes via the OpenLM framework, and evaluations across 53 downstream tasks.

ArXiv

DiffSynth Studio

DiffSynth Studio is a diffusion engine designed to enhance computational performance while maintaining compatibility with various open-source models. It includes features for image and video synthesis, such as long video generation, high-resolution image creation, toon shading, and video stylization. The project has seen significant updates and proposals, including FastSDXL, FastBlend, and ExVideo for advanced video generation capabilities.

Repo