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OpenAI responds to The New York Times lawsuit
OpenAI has responded to The New York Times copyright lawsuit, asserting its aim to support a healthy news ecosystem and create mutually beneficial opportunities. It believes training AI models with publicly available data is fair use. OpenAI states it is working to fix the rare verbatim content reproduction issue and hopes to resolve the situation…
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What to expect from the coming year in AI
The text discusses the author’s reflections on the past year and the expectations for AI in 2024, as well as the upcoming AI regulation. It also highlights the security vulnerabilities of AI and the growing role of AI in society. Additionally, it mentions the potential of AI in earthquake prediction and provides updates on AI…
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NVIDIA announces new chips and tools for on-device AI
NVIDIA unveiled new GPUs, graphics cards, and developer tools at CES, targeting AI models and applications on local devices. The focus shifts to powering generative AI on laptops and PCs with GeForce RTX SUPER desktop GPUs. New AI developer tools and features like AI Workbench and NVIDIA RTX Remix aim to transform gaming. More announcements…
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From Adaline to Multilayer Neural Networks
The provided text is a technical article covering the implementation and explanation of a multilayer neural network from scratch. It discusses the foundations, implementation, training, hyperparameter tuning, and conclusions about the network, along with sections on activation, loss function, backpropagation, and dataset. It also includes code for implementation and examples of mathematical notation and equations…
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Moving Earth, Word, and Concept
This article discusses three measures of distance: Earth Mover’s Distance (EMD) for image search, Word Mover’s Distance (WMD) for document retrieval, and Concept Mover’s Distance (CMD) for analyzing concepts within texts. The measures progress from tangible to abstract, impacting their analytical power. The CMD, utilizing an “ideal pseudo document,” distinguishes itself by presuming likeness analytically,…
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How to Use Backdoor Criterion to Select Control Variables
The article introduces the use of Directed Acyclic Graphs (DAG) and backdoor criterion in causal inference for experimental settings to select good control variables. It explains the process through a data science problem of influencing sustainable behavior and includes examples and simulated experiments in R to demonstrate the application. The article emphasizes the importance of…
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Diffusion Models: Midjourney, Dall-E Reverse Time to Generate Images from Prompts
The text discusses the author’s experience with AI-generated image models, particularly focusing on diffusion models for image generation from text prompts. The author highlights the theoretical foundations of these models, their training process, and conditioning on input like text prompts. They refer to key research papers and discuss applications of the models, emphasizing their generative…
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Generative AI’s plagiarism problem a legal risk to users
AI art generators present a growing legal risk due to potential copyright infringements. Dr. Gary Marcus and Reid Southen noted that prompts can lead to AI-generated images resembling copyrighted material, posing legal challenges for end users. Companies like Midjourney and DALL-E face difficulties in preventing illegal content, prompting the need for improved safeguards. Accidental infringements…
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AI for everything: 10 Breakthrough Technologies 2024
In November 2022, OpenAI launched ChatGPT, which quickly became the fastest-growing web app. Microsoft and Google also revealed plans to integrate chatbots with search, despite early hiccups. The tech now promises to revolutionize daily internet interactions, from office software to photo editing. The rapid development of AI has left us grappling with its impact.
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Researchers from Tsinghua University Unveil ‘Gemini’: A New AI Approach to Boost Performance and Energy Efficiency in Chiplet-Based Deep Neural Network Accelerators
Researchers from multiple universities have developed Gemini, a comprehensive framework for optimizing performance, energy efficiency, and monetary cost (MC) in DNN chiplet accelerators. Gemini employs innovative encoding and mapping strategies, a dynamic programming-based graph partition algorithm, and a Simulated-Annealing-based approach for optimization. Experimentation demonstrates Gemini’s superiority over existing state-of-the-art designs.