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Only Use LLMs If You Know How to Do the Task on Your Own
Silent mistakes or harsh consequences can arise if not careful.
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How to Avoid Five Common Mistakes in Google BigQuery / SQL
The text discusses five common mistakes made by experienced Data Scientists when working with BigQuery.
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Revolutionizing Language Model Fine-Tuning: Achieving Unprecedented Gains with NEFTune’s Noisy Embeddings
The NEFTune method is proposed as a way to improve the performance of language models on instruction-based tasks. By adding random noise to the embedding vectors during fine-tuning, the model’s performance is significantly enhanced without needing more computational resources or data. This approach leads to better conversational abilities without sacrificing factual question-answering performance. NEFTune has…
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How can Pre-Trained Visual Representations Help Solve Long-Horizon Manipulation? Meet Universal Visual Decomposer (UVD): An off-the-Shelf Method for Identifying Subgoals from Videos
The authors of the research paper “Universal Visual Decomposer: Long-Horizon Manipulation Made Easy” propose the Universal Visual Decomposer (UVD), a task decomposition method that uses pre-trained visual representations to teach robots long-horizon manipulation tasks. UVD identifies subtasks within visual demonstrations, aiding in policy learning and generalization. The effectiveness of UVD is demonstrated through evaluations in…
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This AI Research Introduces ‘RAFA’: A Principled Artificial Intelligence Framework for Autonomous LLM Agents with Provable Sample Efficiency
A study by Northwestern University, Tsinghua University, and the Chinese University of Hong Kong introduces a moral framework called “reason for future, act for now” (RAFA) to improve the reasoning capabilities of LLMs. They use a Bayesian adaptive MDP paradigm to describe how LLMs reason and act. RAFA performs well on text-based benchmarks such as…
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Revolutionizing Document Parsing: Meet DSG – The First End-to-End Trainable System for Hierarchical Structure Extraction
The Document Structure Generator (DSG) is a powerful system for parsing and generating structured documents. It surpasses commercial OCR tools and offers the first end-to-end trainable solution for hierarchical document parsing. DSG utilizes deep neural networks to capture entity sequences and nested structures, revolutionizing document processing.
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DeepMind’s CEO draws comparison between AI risks and the climate crisis
Google DeepMind CEO, Demis Hassabis, has called for AI risks to be treated as seriously as the climate crisis. He emphasized the need for an immediate response to the challenges posed by AI and suggested the establishment of an independent international regulatory board. Hassabis will attend the AI Safety Summit in November.
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The Idaho police force invest in AI-powered remote phone access technology
The Nampa Police Department in Idaho is adopting AI technology from Cellebrite, an Israeli company, to unlock cell phones and access personal data. The software helps filter and organize information, saving time for officers. However, legal boundaries still apply, requiring a search warrant or consent. Cellebrite assures lawful and ethical operations, although previous concerns have…
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Meet DiagrammerGPT: A Novel Two-Stage Text-to-Diagram Generation AI Framework that Leverages the Knowledge of LLMs for Planning and Refining the Overall Diagram Plans
DiagrammerGPT is a groundbreaking system powered by advanced LLMs like GPT-4 that generates precise diagrams from text. It consists of two stages: generating diagram plans and creating diagrams with text labels. This approach addresses the lack of T2I models for diagram generation and achieves superior performance, encouraging further research in the field. However, caution is…
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Researchers from CMU and UC Santa Barbara Propose Innovative AI-Based ‘Diagnosis of Thought’ Prompting for Cognitive Distortion Detection in Psychotherapy
Mental health disorders are underserved globally due to lack of specialists, subpar treatments, high costs, and societal stigma. Automated tools like chatbots and sentiment analysis have been developed to help, but they have limitations. Recent advancements in Large Language Models (LLMs) show promise in supporting psychotherapy. Researchers propose the Diagnosis of Thought (DoT) approach, which…