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Artificial Intelligence Latest News

Explore the latest insights and updates from top sources in technology, artificial intelligence, and innovation. Our curated collection of RSS feeds brings you real-time content from renowned platforms, including OpenAI, Google, and more. Stay informed about the cutting-edge developments, research breakthroughs, and industry trends, all in one central hub.

Google’s AI coding agent Jules is now out of beta

Powered by Gemini 2.5 Pro, Jules is an asynchronous, agent-based coding tool that integrates with GitHub, clones codebases into Google Cloud virtual machines, and uses AI to fix or update code while developers focus on other tasks.

Final call: TechCrunch Disrupt 2025 ticket savings end tonight

TechCrunch Disrupt 2025 marks 20 years of shaping the startup world — and tonight’s your last chance to save up to $675 on your ticket. From October 27–29, Disrupt returns to Moscone West in San Francisco. Join 10,000+ tech innovators, founders, VCs, and ecosystem builders for three days of high-impact…

AI shapes autonomous underwater “gliders”

An AI pipeline developed by CSAIL researchers enables unique hydrodynamic designs for bodyboard-sized vehicles that glide underwater and could help scientists gather marine data.

Google AI Blog - The latest research

Generative AI to quantify uncertainty in weather forecasting

Posted by Lizao (Larry) Li, Software Engineer, and Rob Carver, Research Scientist, Google Research Accurate weather forecasts can have a direct impact on people’s lives, from helping make routine decisions, like what to pack for a day’s activities, to informing urgent actions, for example, protecting people in the face of…

AutoBNN: Probabilistic time series forecasting with compositional bayesian neural networks

Posted by Urs Köster, Software Engineer, Google Research Time series problems are ubiquitous, from forecasting weather and traffic patterns to understanding economic trends. Bayesian approaches start with an assumption about the data's patterns (prior probability), collecting evidence (e.g., new time series data), and continuously updating that assumption to form a…

Computer-aided diagnosis for lung cancer screening

Posted by Atilla Kiraly, Software Engineer, and Rory Pilgrim, Product Manager, Google Research Lung cancer is the leading cause of cancer-related deaths globally with 1.8 million deaths reported in 2020. Late diagnosis dramatically reduces the chances of survival. Lung cancer screening via computed tomography (CT), which provides a detailed 3D…

Using AI to expand global access to reliable flood forecasts

Posted by Yossi Matias, VP Engineering & Research, and Grey Nearing, Research Scientist, Google Research Floods are the most common natural disaster, and are responsible for roughly $50 billion in annual financial damages worldwide. The rate of flood-related disasters has more than doubled since the year 2000 partly due to…

ScreenAI: A visual language model for UI and visually-situated language understanding

Posted by Srinivas Sunkara and Gilles Baechler, Software Engineers, Google Research Screen user interfaces (UIs) and infographics, such as charts, diagrams and tables, play important roles in human communication and human-machine interaction as they facilitate rich and interactive user experiences. UIs and infographics share similar design principles and visual language…

SCIN: A new resource for representative dermatology images

Posted by Pooja Rao, Research Scientist, Google Research Health datasets play a crucial role in research and medical education, but it can be challenging to create a dataset that represents the real world. For example, dermatology conditions are diverse in their appearance and severity and manifest differently across skin tones.…

MELON: Reconstructing 3D objects from images with unknown poses

Posted by Mark Matthews, Senior Software Engineer, and Dmitry Lagun, Research Scientist, Google Research A person's prior experience and understanding of the world generally enables them to easily infer what an object looks like in whole, even if only looking at a few 2D pictures of it. Yet the capacity…

HEAL: A framework for health equity assessment of machine learning performance

Posted by Mike Schaekermann, Research Scientist, Google Research, and Ivor Horn, Chief Health Equity Officer & Director, Google Core Health equity is a major societal concern worldwide with disparities having many causes. These sources include limitations in access to healthcare, differences in clinical treatment, and even fundamental differences in the…

Cappy: Outperforming and boosting large multi-task language models with a small scorer

Posted by Yun Zhu and Lijuan Liu, Software Engineers, Google Research Large language model (LLM) advancements have led to a new paradigm that unifies various natural language processing (NLP) tasks within an instruction-following framework. This paradigm is exemplified by recent multi-task LLMs, such as T0, FLAN, and OPT-IML. First, multi-task…

Talk like a graph: Encoding graphs for large language models

Posted by Bahare Fatemi and Bryan Perozzi, Research Scientists, Google Research Imagine all the things around you — your friends, tools in your kitchen, or even the parts of your bike. They are all connected in different ways. In computer science, the term graph is used to describe connections between…

Chain-of-table: Evolving tables in the reasoning chain for table understanding

Posted by Zilong Wang, Student Researcher, and Chen-Yu Lee, Research Scientist, Cloud AI Team People use tables every day to organize and interpret complex information in a structured, easily accessible format. Due to the ubiquity of such tables, reasoning over tabular data has long been a central topic in natural…

Health-specific embedding tools for dermatology and pathology

Posted by Dave Steiner, Clinical Research Scientist, Google Health, and Rory Pilgrim, Product Manager, Google Research There’s a worldwide shortage of access to medical imaging expert interpretation across specialties including radiology, dermatology and pathology. Machine learning (ML) technology can help ease this burden by powering tools that enable doctors to…

Social learning: Collaborative learning with large language models

Posted by Amirkeivan Mohtashami, Research Intern, and Florian Hartmann, Software Engineer, Google Research Large language models (LLMs) have significantly improved the state of the art for solving tasks specified using natural language, often reaching performance close to that of people. As these models increasingly enable assistive agents, it could be…

Croissant: a metadata format for ML-ready datasets

Posted by Omar Benjelloun, Software Engineer, Google Research, and Peter Mattson, Software Engineer, Google Core ML and President, MLCommons Association Machine learning (ML) practitioners looking to reuse existing datasets to train an ML model often spend a lot of time understanding the data, making sense of its organization, or figuring…

Google at APS 2024

Posted by Kate Weber and Shannon Leon, Google Research, Quantum AI Team Today the 2024 March Meeting of the American Physical Society (APS) kicks off in Minneapolis, MN. A premier conference on topics ranging across physics and related fields, APS 2024 brings together researchers, students, and industry professionals to share…

Microsoft Research Blog - The latest

Self-adaptive reasoning for science

Microsoft is pioneering a vision for a self-adapting AI system that can adapt to the dynamic nature of scientific discovery, promoting deeper, more refined reasoning in complex scientific domains. The post Self-adaptive reasoning for science appeared first on Microsoft Research.

VeriTrail: Detecting hallucination and tracing provenance in multi-step AI workflows

VeriTrail, new from Microsoft Research, can detect AI-generated content that is not supported by the source text, trace the provenance of content from final output back to the source, and locate where errors were likely introduced. The post VeriTrail: Detecting hallucination and tracing provenance in multi-step AI workflows appeared first…

Project Ire autonomously identifies malware at scale

Designed to classify software without context, Project Ire replicates the gold standard in malware analysis through reverse engineering. It streamlines a complex, expert-driven process, making large-scale malware detection faster & more consistent. The post Project Ire autonomously identifies malware at scale appeared first on Microsoft Research.

Navigating medical education in the era of generative AI

Next-generation physicians Morgan Cheatham and Daniel Chen discuss how generative AI is transforming medical education, exploring how students and attending physicians integrate new tools while navigating questions on trust, training, and responsibility. The post Navigating medical education in the era of generative AI appeared first on Microsoft Research.

Technical approach for classifying human-AI interactions at scale

Semantic Telemetry helps LLMs run efficiently, reliably, and in near real-time. Learn about the engineering behind that system, including the trade-offs and lessons learned along the way—from batching strategies to token optimization and orchestration. The post Technical approach for classifying human-AI interactions at scale appeared first on Microsoft Research.

AI Testing and Evaluation: Reflections

In the series finale, Amanda Craig Deckard returns to examine what Microsoft has learned about testing as a governance tool. She also explores the roles of rigor, standardization, and interpretability in testing and what’s next for Microsoft’s AI governance work. The post AI Testing and Evaluation: Reflections appeared first on…

CollabLLM: Teaching LLMs to collaborate with users

Recipient of an ICML 2025 Outstanding Paper Award, CollabLLM improves how LLMs collaborate with users, including knowing when to ask questions and how to adapt tone and communication style to different situations. This approach helps move AI toward more user-centric and trustworthy systems. The post CollabLLM: Teaching LLMs to collaborate…

AI Testing and Evaluation: Learnings from cybersecurity

Drawing on his previous work as the UK’s cybersecurity chief, Professor Ciaran Martin explores differentiated standards and public-private partnerships in cybersecurity, and Microsoft’s Tori Westerhoff examines the insights through an AI red-teaming lens. The post AI Testing and Evaluation: Learnings from cybersecurity appeared first on Microsoft Research.

How AI will accelerate biomedical research and discovery

Daphne Koller, Noubar Afeyan, and Dr. Eric Topol, leaders in AI-driven medicine, discuss how AI is changing biomedical research and discovery, from accelerating drug target identification and biotech R&D to helping pursue the “holy grail” of a virtual cell. The post How AI will accelerate biomedical research and discovery appeared…

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