Artificial Intelligence
In this article, the author discusses their experience working as a data engineer in both a DevOps-focused role and an analytics engineering role. They highlight the differences between DevOps and DataOps, including the focus on software as a product in DevOps and data quality in DataOps. The key metrics of success for DevOps are downtime…
This article provides ideas and techniques for expressing simultaneous changes in geospatial data using Python. It covers various chart types, including choropleth maps, bubble charts, pie charts, bar charts, and line charts. The author explains how to obtain and plot geospatial data and includes examples and code snippets throughout the article. The goal is to…
The text discusses five boundaries that can help achieve a better work-life balance as a data scientist in 2024. These boundaries include setting up a documentation system, allowing for longer project timelines, refusing unrealistic deadlines, avoiding overtime for artificial deadlines, and prioritizing quality over speed in data analysis projects.
The rise in demand for data-centric local intelligence has highlighted the need for autonomous data analysis at the edge. Edge-AI devices, such as wearables and smartphones, represent the next phase of growth in the semiconductor industry. However, these devices face the challenge of the von Neumann bottleneck, which limits their ability to process data locally.…
Researchers from the University of Zurich evaluated the performance of Large Language Models (LLMs), specifically GPT-4, in autonomous fact-checking. While LLMs show promise in fact-checking with contextual information, their accuracy varies based on query language and claim veracity. Further research is needed to improve understanding of LLM capabilities and limitations in fact-checking tasks.
Researchers from Tsinghua University and ByteDance have developed SALMONN, a multimodal language model (LLM) that can recognize and comprehend various audio inputs, including voice, audio events, and music. They also propose a low-cost activation tuning technique to activate cross-modal emergent skills and reduce catastrophic forgetting. SALMONN performs well on a range of hearing tasks.
SELF-RAG is a framework that enhances large language models by dynamically retrieving relevant information and reflecting on its generations. It significantly improves quality, factuality, and performance on various tasks, outperforming other models. SELF-RAG is effective in open-domain question-answering, reasoning, fact verification, and long-form content generation. Further research and refinement can enhance output accuracy and address…
Artificial intelligence (AI) email assistants help users manage their inboxes more efficiently. They offer features like automatic task completion, message prioritization, and prompt responses. These AI assistants are beneficial for professionals with busy schedules, entrepreneurs, and students. Some popular AI email assistants include SaneBox, InboxPro, Lavender, Missive, Superflows, Superhuman, Scribbly, Tugan, AI Mailer, Nanonets, Flowrite,…
Researchers have introduced the Davidsonian Scene Graph (DSG), an automatic question generation and answering framework to evaluate text-to-image (T2I) models. DSG generates contextually relevant questions in dependency graphs for better semantic coverage and consistent answers. Experimental results demonstrate the effectiveness of DSG on various model configurations. The study emphasizes the need for further research into…
IBM has launched the Watsonx Code Assistant, an AI-powered tool that aims to help developers code quickly and accurately. The Code Assistant offers two models, one for IT automation and another for mainframe application modernization. It runs on IBM’s Watsonx platform, known for its security and compliance features. IBM Consulting is available to assist clients…
Large Language Models (LLMs) like GPT-3 have revolutionized Natural Language Processing. They demonstrate exceptional language recognition and excel in various areas such as reasoning, visual comprehension, and code development. LLMs possess broad understanding and can handle inputs and outputs beyond language. Researchers have proposed LLaRP, an approach using pre-trained LLMs to act as generalizable policies…
CuPL, also known as Customized Prompts via Language models, is a topic that can be explored further in Towards Data Science.
QML is being utilized to combine machine learning and particle physics in a fun application.
This article discusses the process of fine tuning language models for Named Entity Recognition. It can be found on Towards Data Science.
TRL (Transformer Reinforcement Learning) is a full-stack library that allows researchers to train transformer language models and stable diffusion models with reinforcement learning. It includes tools such as SFT (Supervised Fine-tuning), RM (Reward Modeling), and PPO (Proximal Policy Optimization). TRL improves the efficiency, adaptability, and robustness of transformer language models for tasks like text generation,…
Researchers at the Institute for Assured Autonomy propose advanced AI techniques and simulation environments to ensure safety in the expanding field of unmanned aircraft systems.
According to a new study, integrating AI into the business sector is proving to be lucrative. While business adoption has been slower than predicted, 71% of surveyed companies are implementing AI. AI projects are completed in less than a year, with businesses seeing an average return of $3.50 for every dollar spent on AI. Lack…
Elon Musk’s startup xAI will release its first AI products on November 4th to a select group. Musk claims that in “important respects,” xAI surpasses all existing AI. xAI aims to understand the true nature of the universe and collaborate with X, Tesla, and other entities. Its team includes researchers from companies like DeepMind and…
Microsoft researchers have introduced a novel framework called the “Large Search Model” (LSM) that aims to revolutionize online search engines. By combining multiple components, the LSM utilizes Large Language Models (LLMs) to improve search results. The model can be customized for different search tasks using natural language prompts and can adapt to specific situations. The…
Woodpecker is a new AI framework developed by Chinese researchers to address hallucinations in Multimodal Large Language Models (MLLMs). It offers a training-free alternative to mitigate inaccuracies in text descriptions generated by MLLMs. The framework consists of five stages, emphasizing transparency and interpretability. Woodpecker significantly improves accuracy and performance over baseline models in benchmark evaluations,…