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Editors Pick

RABBITS: A Distinctive Database and Scoring System to Assist in Assessing Language Model Performance in Healthcare Sector

Biomedical Natural Language Processing (NLP) uses machine learning to interpret medical texts, aiding with diagnoses, treatment recommendations, and medical information extraction. However, ensuring the accuracy of these models is a challenge due to diverse and context-specific medical terminologies. To address this issue, researchers from MIT, Harvard, and Mass General Brigham, among other institutions, developed RABBITS (Robust…

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Explained with Simple Human Analogies: A Guide to Frequently Employed Advanced Techniques in Prompt Engineering

Artificial Intelligence (AI) models are becoming more sophisticated, and efficient communication with these models is crucial. Various prompt engineering strategies have been developed to facilitate this communication, utilizing concepts and structures similar to human problem-solving methods. These strategies can be categorized into different types: chaining methods, decomposition-based methods, path aggregation methods, reasoning-based methods, and external…

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Introducing BigCodeBench by BigCode: The New Benchmark for Assessing Sizeable Language Models in Practical Coding Assignments.

BigCode, a leading developer of large language models (LLMs), has launched BigCodeBench, a new benchmark for comprehensively assessing the programming capabilities of LLMs. This concurrent approach addresses the limitations of existing benchmarks like HumanEval, which has been criticized for its simplicity and scant real-world relevance. BigCodeBench comprises 1,140 function-level tasks which require the LLMs to…

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Researchers from Stanford University Initiate Nuclei.io: Transforming AI and Medical Practitioner Cooperation for Advanced Pathology Datasets and Models.

The integration of artificial intelligence (AI) in clinical pathology represents an exciting frontier in healthcare, but key challenges include data constraints, model transparency, and interoperability. These issues prevent AI and machine learning (ML) algorithms from being widely adopted in clinical settings, despite their proven effectiveness in tasks such as cell segmentation, image classification, and prognosis…

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PlanRAG: The concept of a Generative Large Language Model that Plans before Retrieving Augmented Generation for Decision-Making Purposes

Decision-making is crucial for organizations, often requiring data analysis and selection processes to determine the best alternative to meet specific objectives. For instance, pharmaceutical distribution networks often have to confront daunting decisions such as choosing the appropriate plants to run, deciding on the number of employees to employ, and optimizing production costs while ensuring prompt…

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Microsoft researchers have presented a conceptual structure that utilizes Variational Bayesian Theory and includes a Bayesian intention variable.

Historically, thinking around decision-making has dichotomized habitual and goal-oriented behavior, treating them as independent activities controlled by distinct neural systems. Habitual behaviors, being automatic, are fast and model-free while goal-oriented behaviors, requiring deliberate action, are slower, model-based but demanding computationally. Microsoft researchers, however, have proposed an innovative Bayesian behavior framework that attempts to synergize these…

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Project Oversight by Roboflow Improves Computer Vision Initiatives: A Guide to Installation, Functionality, and User Assistance

Roboflow’s Supervision is a reusable tool crafted to simplify numerous tasks relating to computer vision. The tool is quite adaptable and provides functionalities to load datasets from different sources, draw detections on images or videos, and count the number of detections within specified zones. One of the significant features of Supervision is its ability to…

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Researchers from the Allen Institute have unveiled a report on Artificial Intelligence which presents OLMES. This innovation aims to establish standards for equitable and repeatable assessments in the field of language modeling.

In the field of artificial intelligence (AI) research, language model evaluation is a vital area of focus. This involves assessing the capabilities and performance of models on various tasks, helping to identify their strengths and weaknesses in order to guide future developments and enhancements. A key challenge in this area, however, is the lack of…

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Mozart Data: A Comprehensive Data Platform Utilizing BigQuery or Snowflake Technologies Internally

In the modern data-driven economy, data generation is at an unprecedented level. Handling and investigating this data effectively poses a significant challenge due to its sheer volume and potential for insights. Data analysis and optimization can now benefit all business aspects, whether they are minor or major, ranging from marketing initiatives to general operations and…

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Removing Vector Quantization: Implementing Diffusion-Based AI Models for Autoregressive Image Production

Autoregressive image generation models have traditionally been built using vector-quantized representations. However, these models have exhibited drawbacks, particularly related to their limited flexibility and computational intensity that often result in suboptimal image reconstruction. The vector quantization process involves the conversion of continuous image data into discrete tokens, which can also give rise to loss of…

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HPC AI Tech’s Open-Sora 1.2: Revolutionizing Video Production through Advanced, Open-Source Video Creation and Reduction Techniques.

Open-Sora, a cutting-edge initiative by HPC AI Tech, intends to democratize the process of efficient video production. By espousing the principles of open-source, the project aims to make the sophisticated methods of video generation available to all, thereby promoting innovation, creativity, and inclusivity in the field of content creation. The first version, Open-Sora 1.0, established the…

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Microsoft Unveils Florence-2: A New Vision Foundation Model with an Integrated, Prompt-based Structure for a Range of Computer Vision and Vision-Language Responsibilities.

Microsoft research team has made significant strides in introducing Florence-2, a sophisticated computer vision model. The adoption of pretrained and adaptable systems in artificial general intelligence (AGI) is increasingly becoming popular. These systems, characterized by their task-agnostic capabilities, are used in diverse applications. Natural language processing (NLP), with its ability to learn new tasks and…

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