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Nightshade registers 250,000+ downloads within days of release
Nightshade, a tool from the University of Chicago, gained over 250,000 downloads within five days of its release. It combats unauthorized use of artwork by AI models by poisoning them at the pixel level, rendering them unable to replicate images accurately. The team is overwhelmed by its success, with potential future integration and cloud hosting.
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US lawmakers propose DEFIANCE Act to tackle troublesome deep fakes
US lawmakers have proposed the DEFIANCE Act to address the growing problem of AI-generated explicit images. Prompted by a series of deep fake AI-generated images of Taylor Swift, the bipartisan bill aims to empower individuals to sue for damages if they are depicted in “digital forgeries” without consent. This legislation expands the legal framework to…
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Mastercard creates a generative AI model to fight fraud
Mastercard has developed a new generative AI fraud detection tool, called Decision Intelligence Pro (DI Pro), powered by a recurrent neural network. It analyzes cardholders’ purchasing histories and scans data points to predict transaction authenticity in less than 50 milliseconds. Initial modeling suggests a potential 20-300% boost in fraud detection rates. The tool is expected…
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DAI#24 – Brain chips, clones, and Swifties fight back
This week’s AI news features the following highlights: 1. Taylor Swift’s battle against explicit AI deep fake images and the concerning ease of generating such content using AI. 2. The rise of political deep fakes showcasing AI’s capabilities in replicating voices with convincing realism and the challenges of detecting these fakes. 3. OpenAI’s evolving transparency…
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Meet CMMMU: A New Chinese Massive Multi-Discipline Multimodal Understanding Benchmark Designed to Evaluate Large Multimodal Models LMMs
The CMMMU benchmark has been introduced to bridge the gap between powerful Large Multimodal Models (LMMs) and expert-level artificial intelligence in tasks involving complex perception and reasoning with domain-specific knowledge. It comprises 12,000 Chinese multimodal questions across six core disciplines and employs a rigorous data collection and quality control process. The benchmark evaluates LMMs, presents…
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DeepSeek-AI Introduce the DeepSeek-Coder Series: A Range of Open-Source Code Models from 1.3B to 33B and Trained from Scratch on 2T Tokens
The integration of large language models (LLMs) in software development has revolutionized code intelligence, automating aspects of programming and increasing productivity. Disparities between open-source and closed-source models have hindered accessibility and democratization of advanced coding tools. DeepSeek-AI and Peking University’s DeepSeek-Coder series addresses this gap, enhancing open-source models’ functionality and performance, marking a significant advancement…
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This AI Paper from China Introduces ‘AGENTBOARD’: An Open-Source Evaluation Framework Tailored to Analytical Evaluation of Multi-Turn LLM Agents
AgentBoard, developed by researchers from multiple Chinese universities, presents a benchmark framework and toolkit for evaluating LLM agents. It addresses challenges in assessing multi-round interactions and diverse scenarios in agent tasks. With a fine-grained progress rate metric and interactive visualization, it illuminates the capabilities and limitations of LLM agents across varied environments.
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Researchers from the Chinese University of Hong Kong and Tencent AI Lab Propose a Multimodal Pathway to Improve Transformers with Irrelevant Data from Other Modalities
The researchers from The Chinese University of Hong Kong and Tencent AI Lab introduce the Multimodal Pathway Transformer (M2PT) to enhance transformer performance by incorporating irrelevant data from other modalities, resulting in substantial performance improvements across various recognition tasks. The approach involves Cross-Modal Re-parameterization and demonstrates tangible implementation of auxiliary weights without incurring inference costs.
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Data center energy demands are outstripping what the grid can provide
The demand for AI is challenging environmental sustainability, as it significantly increases electricity consumption. Data centers, particularly those supporting generative AI, strain global energy infrastructure. The rising electricity demands from AI and data centers are creating environmental and grid stability concerns, urging the need for more sustainable practices within the AI industry and alternative energy…
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Meet BiTA: An Innovative AI Method Expediting LLMs via Streamlined Semi-Autoregressive Generation and Draft Verification
Recent advancements in large language models (LLMs) like Chat-GPT and LLaMA-2 have led to an exponential increase in parameters, posing challenges in inference delay. To address this, Intellifusion Inc. and Harbin Institute of Technology propose Bi-directional Tuning for lossless Acceleration (BiTA) to expedite LLMs, achieving significant speedups without compromising output quality. (50 words)