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Researchers from the University of Washington and Duke University Introduce Punica: An Artificial Intelligence System to Serve Multiple LoRA Models in a Shared GPU Cluster
Researchers from the University of Washington and Duke University have developed Punica, a multi-tenant serving framework for LoRA models on a shared GPU cluster. By utilizing a new CUDA kernel called SGMV, Punica enables efficient batching of requests from multiple LoRA models, resulting in improved GPU usage and throughput. The paper details the contributions and…
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Parallelising Python on Spark: Options for concurrency with Pandas
This blog post discusses the options and benefits of parallelizing Python code on Spark when working with Pandas. It compares Pandas UDFs and the ‘concurrent.futures’ module as two approaches to concurrent processing in order to determine their use cases. The post also covers the challenges of working with large datasets and the performance results of…
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2024 Data Job Market: Oversaturated or Good Outlook?
The data job market has been challenging, with a significant decrease in job postings from Big Tech companies (FAANG) but slight improvement in hiring by other companies. The overall job market seems to be recovering after a dip in May. There is a higher demand for data engineers compared to data scientists or data analysts.…
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Researchers from SJTU China Introduce TransLO: A Window-Based Masked Point Transformer Framework for Large-Scale LiDAR Odometry
Researchers from Shanghai Jiao Tong University and China University of Mining and Technology have developed TransLO, a LiDAR odometry network that combines CNNs and transformers to enhance global feature embeddings and outlier rejection. TransLO outperforms existing methods on the KITTI odometry dataset with superior accuracy and efficiency. Components like WMSA and MCFA were evaluated through…
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Sentiment Analysis in Live Chat
Sentiment analysis is a natural language processing technique that analyzes emotions and opinions in text. Implementing sentiment analysis in live chat can enhance customer service by identifying frustrated or satisfied customers. It allows businesses to address concerns promptly and turn negative experiences into positive ones. Sentiment analysis also helps identify trends in customer feedback and…
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Meet SPHINX: A Versatile Multi-Modal Large Language Model (MLLM) with a Mixer of Training Tasks, Data Domains, and Visual Embeddings
SPHINX is a multi-modal large language model that addresses the limitations of existing models in understanding visual instructions and performing diverse tasks. It integrates model weights, tuning tasks, and visual embeddings to excel in tasks like human pose estimation and object detection. SPHINX’s fine-grained visual understanding and collaboration with other models make it a frontrunner…
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Amazon Researchers Propose KD-Boost: A Novel Knowledge Distillation Algorithm Designed for Real-Time Semantic Matching
Amazon researchers have developed KD-Boost, a knowledge distillation technique, to address the challenges of real-time semantic matching in web search and e-commerce product search. KD-Boost uses ground truth and soft labels from a teacher model to train low-latency, accurate student models. The technique has shown significant improvements in relevance, query-to-query matching, and product coverage.
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Empirical Methods in Natural Language Processing (EMNLP) 2023
Apple is sponsoring the EMNLP conference in Singapore from December 6 to 10. EMNLP is a prominent conference on natural language processing. Apple will host workshops and events during the conference.
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“Approximate-Predictions” Make Feature Selection Radically Faster
Learn how to accelerate feature selection, which typically involves creating multiple models and can be sluggish, thanks to the tips provided in the article on Towards Data Science.
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LastMile AI Releases AiConfig: An Open-Source Config-Driven, Source Control Friendly AI Application Development Framework
AI Config from LastMile Ai is an innovative tool that revolutionizes AI application development. It allows developers to separate application code from model logic, resulting in a more efficient and collaborative development process. AI Config offers advantages such as collaborative development, enhanced prototyping, governance and control, rapid iteration and deployment, a user-friendly interface, open-source support,…