​Interfaces for machine learning (ML), information and visualizations about models or data, can help practitioners build robust and responsible ML systems. Despite their benefits, recent studies of ML teams and our interviews with practitioners (n=9) showed that ML interfaces have limited adoption in practice. While… Read More »Symphony: Composing Interactive Interfaces for Machine Learning Apple Machine Learning Research

​ To obtain information comparable to a given query, large-scale web search engines train an encoder to contain the query and then connect the encoder to an approximate nearest neighbor search (ANNS) pipeline. Learned representations are often stiff, high-dimensional vectors generally employed as-is throughout the… Read More »Meet AdANNS: A Novel Framework that Leverages Adaptive Representations for Different Phases of ANNS Pipelines to Improve the Accuracy-Compute Tradeoff Dhanshree Shripad Shenwai Artificial Intelligence Category – MarkTechPost

​Posted by Juhyun Lee and Raman Sarokin, Software Engineers, Core Systems & Experiences The proliferation of large diffusion models for image generation has led to a significant increase in model size and inference workloads. On-device ML inference in mobile environments requires meticulous performance optimization and… Read More »Speed is all you need: On-device acceleration of large diffusion models via GPU-aware optimizations Google AI Google AI Blog

​ “Mitigating the risk of extinction from A.I. should be a global priority alongside other societal-scale risks, such as pandemics and nuclear war,” according to a statement signed by more than 350 business and technical leaders, including the developers of today’s most important AI platforms.… Read More »The Alignment Problem Is Not New Tim O’Reilly AI & ML – Radar

​ The world changed on November 30, 2022 as surely as it did on August 12, 1908 when the first Model T left the Ford assembly line. That was the date when OpenAI released ChatGPT, the day that AI emerged from research labs into an… Read More »You Can’t Regulate What You Don’t Understand Tim O’Reilly AI & ML – Radar

​ Dive into Deep Learning (D2L.ai) is an open-source textbook that makes deep learning accessible to everyone. It features interactive Jupyter notebooks with self-contained code in PyTorch, JAX, TensorFlow, and MXNet, as well as real-world examples, exposition figures, and math. So far, D2L has been… Read More »Build a multilingual automatic translation pipeline with Amazon Translate Active Custom Translation Yunfei Bai AWS Machine Learning Blog

​ How to access an index in Python for loop? By default Python for loop doesn’t support accessing index, the reason being for loop in Python is similar to foreach where you don’t have access to index while iterating sequence types (list, set e.t.c). For… Read More »Python – Access Index in For Loop With Examples Vijetha Spark By {Examples}

​ Recent developments in artificial intelligence have concentrated on conversational assistants with great comprehension capabilities who can then act. The noteworthy successes of these conversational assistants may be ascribed to the practice of instruction adjustment in addition to the large language models’ (LLMs) high generalization… Read More »NTU and Microsoft Researchers Propose MIMIC-IT: A Large-Scale Multi-Modal in-Context Instruction Tuning Dataset Aneesh Tickoo Artificial Intelligence Category – MarkTechPost

​ Since the release of OpenAI’s revolutionary ChatGPT, the number of projects surrounding AI, especially large language models (LLMs), has been at an all-time high. Many of these projects are capable of disrupting various fields by enabling researchers and developers to leverage the power of… Read More »Meet AnythingLLM: A Full-Stack Application That Transforms Your Content into Rich Data for Enhanced Large Language Models LLMs Interactions Khushboo Gupta Artificial Intelligence Category – MarkTechPost

​ Text-to-Image Diffusion Models represent a groundbreaking approach to generating images from textual prompts. They leverage the power of deep learning and probabilistic modeling to capture the subtle relationships between language and visual concepts. By conditioning a generative model on textual descriptions, these models learn… Read More »Architectural Removal and Distillation: A Path to Efficient Compression in AI Text-to-Image Diffusion Models Daniele Lorenzi Artificial Intelligence Category – MarkTechPost