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This AI Paper Proposes Infini-Gram: A Groundbreaking Approach to Scale and Enhance N-Gram Models Beyond Traditional Limits
This paper introduces the groundbreaking Infini-gram, which modernizes traditional n-gram language models by leveraging trillion-token training data. It challenges historical constraints on n, introducing the concept of an ∞-gram LM and demonstrating its potential to complement neural language models, yielding improved predictive accuracy and efficiency. The paper outlines Infini-gram’s implications and applications across diverse neural…
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LLMWare Launches SLIMs: Small Specialized Function-Calling Models for Multi-Step Automation
LLMWare has launched SLIMs, small language models that generate structured outputs suitable for programmatic handling and tackle multi-step automation challenges in private cloud environments. These SLIMs complement general-purpose LLMs and are designed for enterprise use cases, demonstrating LLMWare’s commitment to advancing small language models for complex workflows. For more details, visit llmware’s GitHub repository or…
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AI in CX Success: Finding Your Ideal Starting Point, Scaling Up
The text discusses how AI can revolutionize customer interactions for businesses. It emphasizes the importance of finding the ideal first AI project for customer experience (CX) success. The multi-phased AI rollout approach is detailed, focusing on internal expansion, improvement, learning, and finally scaling out AI in CX augmentation and automation.
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Introducing Goody-2, the world’s most responsible AI model
BRAIN, an LA-based ad agency, launched Goody-2, described as the world’s most responsible AI model and “outrageously safe”. Although it playfully declines to answer certain questions, it highlights the potential impact of overly stringent alignment principles on AI functionality. While Goody-2 is comedic, it sheds light on the balance needed in AI development.
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FCC declares AI-generated voices in robocalls are illegal
The FCC has banned the use of AI-generated voices in robocalls to consumers, following a scandal involving a fake President Biden voice. FCC Chairwoman Jessica Rosenworcel warned of robocall fraud and misinformation. The ruling also sets limits on using AI voices to interact with consumers and exempts civil services and politicians for non-commercial use.
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Nomic AI Introduces Nomic Embed: Text Embedding Model with an 8192 Context-Length that Outperforms OpenAI Ada-002 and Text-Embedding-3-Small on both Short and Long Context Tasks
Nomic AI introduces Nomic Embed, an open-source, auditable text embedding model with an 8192 context length. It outperforms closed-source models like OpenAI’s text-embedding-ada-002, emphasizing transparency and reproducibility. Nomic Embed is built through a multi-stage contrastive learning pipeline, achieving superior performance on benchmarks. This release marks a significant advancement in the field of text embeddings.
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Can Large Language Models be Trusted for Evaluation? Meet SCALEEVAL: An Agent-Debate-Assisted Meta-Evaluation Framework that Leverages the Capabilities of Multiple Communicative LLM Agents
Researchers introduce SCALEEVAL, a framework utilizing multiple LLM agents engaging in agent-debate to evaluate LLMs as responders. It reduces reliance on costly human annotation, balancing efficiency and human judgment for accurate assessments. It exposes effectiveness and limitations of LLMs in varied scenarios, advancing scalable evaluation methods crucial for expanding LLM applications.
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Pinterest Researchers Present an Effective Scalable Algorithm to Improve Diffusion Models Using Reinforcement Learning (RL)
Pinterest researchers have introduced a reinforcement learning framework to fine-tune diffusion models, addressing issues like bias and fairness. The method outperforms existing models, demonstrating generality, robustness, and the ability to generate diverse images. It achieved better results across various tasks and encourages further research to enhance diffusion models. [50 words]
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Meet Graph-Mamba: A Novel Graph Model that Leverages State Space Models SSM for Efficient Data-Dependent Context Selection
Graph Transformers face scalability challenges due to high computational costs. Existing methods fail to adequately address data-dependent contexts. Graph Neural Networks have introduced innovations like BigBird and Performer to reduce computational demands. Researchers have introduced Graph-Mamba, integrating a selective State Space Model into the GraphGPS framework, promising significant improvements in computational efficiency and scalability.
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‘Weak-to-Strong JailBreaking Attack’: An Efficient AI Method to Attack Aligned LLMs to Produce Harmful Text
Large Language Models (LLMs) like ChatGPT and Llama have shown remarkable performance in AI applications, but concerns about misuse and security vulnerabilities persist. Researchers have introduced the concept of weak-to-strong jailbreaking attacks, which exploit weaker models to manipulate larger ones. Token Distribution Fragility Analysis and Experimental Validation aim to address these vulnerabilities. For more details,…