Microsoft has introduced its first custom AI chips, the Microsoft Azure Maia 100 AI Accelerator and the Microsoft Azure Cobalt 100 CPU. These chips are designed for AI and cloud computing applications and will be used in Microsoft’s data centers to power Bing AI chatbot, Copilot, and Azure OpenAI. The goal is to meet the…

Data organisations often overlook the responsibilities of data consumers in data contracts. To maximize the value of data, data contracts should outline the consumer’s obligations in analyzing and applying the data. Neglecting consumer commitments can reduce the business impact of data contracts. Consumer commitments should go beyond compliance and focus on value creation. Structured approaches,…

This text discusses the semantics of slowly changing dimension type 2 (SCD2) techniques in dimensional modeling. It covers the importance of choosing appropriate reference dates and the impact of different row-versioning methods on access patterns. Three options for reference dates are discussed: extract timestamps, source system timestamps, and business timestamps. Additionally, the format of valid_to…

Researchers at the Clinic of Radiology and Nuclear Medicine at University Hospital Basel have developed a deep learning model called TotalSegmentator that can automatically segment anatomical structures in CT images. The model has been trained on a large dataset and can accurately segment a wide range of organs with minimal user input. The researchers have…

OpenAI’s DevDay showcased innovative features, offering exciting opportunities in the field of artificial intelligence. Discover the latest advancements and explore a world of endless possibilities in our article.

Grounding Large Multimodal Model (GLaMM) is introduced as a novel model for visually grounded conversations. GLaMM allows for natural language replies combined with object segmentation masks, providing improved user engagement. The researchers also introduce the Grounded Conversation Generation (GCG) task and the Grounding-anything Dataset (GranD) to aid in model training and evaluation.

Researchers at UCLA have developed a method called Rephrase and Respond (RaR) to improve the performance of Language Model LLMs. RaR allows LLMs to rephrase and expand human questions in a single prompt, demonstrating effectiveness across different tasks. The approach enhances translation and exhibits significant performance improvements compared to other methods. It also complements the…

The World’s Smallest Data Pipeline Framework is a simple and fast foundation for data pipelines with advanced functionality. It outlines a process for cleaning and transforming data, and introduces the concept of a pipeline to streamline the process. The framework also includes features like filtering, parallel processing, and visualization.

Whisper is an Automatic Speech Recognition (ASR) model trained on 680,000 hours of supervised data from the web. However, it has low-performance on low-resource languages like Marathi and Dravidian languages. Fine-tuning Whisper is challenging due to high computational and storage requirements. LoRA is a unique approach to fine-tuning that reduces trainable parameters and GPU memory…