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.
‘This is fine’ creator says AI startup stole his art
The ad comes from Artisan, the AI startup behind billboards urging businesses to "stop hiring humans."
In Harvard study, AI offered more accurate emergency room diagnoses than two human doctors
A new study examines how large language models perform in a variety of medical contexts, including real emergency room cases — where at least one model seemed to be more accurate than human doctors.
AI-generated actors and scripts are now ineligible for Oscars
Bad news for Tilly Norwood.
The best AI dictation apps, tested and ranked
AI-powered dictation apps are useful for replying to emails, taking notes, and even coding through your voice
Replit’s Amjad Masad on the Cursor deal, fighting Apple, and why he’d rather not sell
At TechCrunch's sold-out StrictlyVC event in San Francisco on Thursday night, we covered a lot of ground in a short time, beginning with the question everyone in the industry is asking right now: in a world where rival Cursor is reportedly in talks to be acquired by SpaceX for $60…
Meta buys robotics startup to bolster its humanoid AI ambitions
Meta bought humanoid startup Assured Robot Intelligence to beef up its AI models for robots, the company said.
Did you know you can’t steal a charity? Don’t worry. Elon Musk will remind you.
Elon Musk spent the better part of three days on the witness stand this week in his lawsuit against OpenAI, and it’s already getting messy. Emails, texts, and his own tweets are surfacing in court, and there are plenty more witnesses to come. Musk’s argument against OpenAI? By converting the company to a for-profit model, Sam Altman…
Pentagon inks deals with Nvidia, Microsoft, and AWS to deploy AI on classified networks
The deals come as the DOD has doubled down on diversifying its exposure to AI vendors in the wake of its controversial dispute with Anthropic over usage terms of its AI models.
Musk v. Altman is just getting started
Elon Musk spent the better part of three days on the witness stand this week in his lawsuit against OpenAI, and it’s already getting messy. Emails, texts, and his own tweets are surfacing in court, and there are plenty more witnesses to come. Musk’s argument against OpenAI? By converting the company to a for-profit model, Sam Altman…
ChatGPT Images 2.0 is a hit in India, but not a big winner elsewhere, yet
Users in India are embracing ChatGPT Images 2.0 for creative, personal visuals — from avatars to cinematic portraits.
Sources: Anthropic potential $900B+ valuation round could happen within 2 weeks
Anthropic is asking investors to submit allocations for the AI company’s latest fundraise within the next 48 hours, according to sources familiar with the matter.
Apple was surprised by AI-driven demand for Macs
Apple said it will be supply-constrained on Mac mini, Studio, and Neo in the next quarter, too.
Legal AI startup Legora hits $5.6B valuation and its battle with Harvey just got hotter
The two wildly fast-growing rivals have raised massive sums, pushed into each other's home turf, and now have dueling ad campaigns.
After dissing Anthropic for limiting Mythos, OpenAI restricts access to Cyber, too
OpenAI will begin rolling out its cybersecurity testing tool, GPT-5.5 Cyber only "to critical cyber defenders" at first.
OpenAI announces new advanced security for ChatGPT accounts, including a partnership with Yubico
OpenAI is launching additional opt-in protections for ChatGPT accounts. The new security initiative includes a new partnership with security key provider Yubico.
Elon Musk testifies that xAI trained Grok on OpenAI models
"Distillation" is a hot topic as frontier labs try to prevent smaller competitors from copying their models.
FDA approval, fundraising, and the reality of building in healthcare according to BioticsAI founder
BioticsAI CEO Robhy Bustami joined Isabelle Johannessen on Build Mode to discuss how the company has navigated a highly regulated space and kept the team motivated while cutting through all the red tape.
Google’s Gemini AI assistant is hitting the road in millions of vehicles
The move signals Google’s push to bring more advanced, conversational AI into the driving experience.
Stripe updates Link, a digital wallet that autonomous AI agents can use, too
Link lets users connect cards, banks, and subscriptions, then authorize AI agents to spend securely via approval flows.
Beacon Biosignals is mapping the brain during sleep
Founded by Jake Donoghue PhD ’19 and former MIT researcher Jarrett Revels, the company is creating an AI-driven platform to help diagnose and treat disease.
Solving the “Whac-a-mole dilemma”: A smarter way to debias AI vision models
A new debiasing technique called WRING avoids creating or amplifying biases that can occur with existing debiasing approaches.
The MIT-IBM Computing Research Lab launches to shape the future of AI and quantum computing
Building on a long-standing MIT–IBM collaboration, the new lab will chart the convergence of AI, algorithms, and quantum computing.
Enabling privacy-preserving AI training on everyday devices
A new method could bring more accurate and efficient AI models to high-stakes applications like health care and finance, even in under-resourced settings.
A faster way to estimate AI power consumption
The “EnergAIzer” method generates reliable results in seconds, enabling data center operators to efficiently allocate resources and reduce wasted energy.
MIT scientists build the world’s largest collection of Olympiad-level math problems, and open it to everyone
New dataset of 30,000-plus competition math problems from 47 countries gives AI researchers a harder test — and students worldwide a better training ground.
Teaching AI models to say “I’m not sure”
A new training method improves the reliability of AI confidence estimates without sacrificing performance, addressing a root cause of hallucination in reasoning models.
Jacob Andreas and Brett McGuire named Edgerton Award winners
The associate professors of EECS and chemistry, respectively, are honored for exceptional contributions to teaching, research, and service at MIT.
Bringing AI-driven protein-design tools to biologists everywhere
Founded by Tristan Bepler PhD ’20 and former MIT professor Tim Lu PhD ’07, OpenProtein.AI offers researchers open-source models and other tools for protein engineering.
Human-machine teaming dives underwater
Researchers are developing hardware and algorithms to improve collaboration between divers and autonomous underwater vehicles engaged in maritime missions.
New technique makes AI models leaner and faster while they’re still learning
Researchers use control theory to shed unnecessary complexity from AI models during training, cutting compute costs without sacrificing performance.
Helping data centers deliver higher performance with less hardware
Researchers developed a system that intelligently balances workloads to improve the efficiency of flash storage hardware in a data center.
Working to advance the nuclear renaissance
Dean Price, assistant professor in the Department of Nuclear Science and Engineering, sees a bright future for nuclear power, and believes AI can help us realize that vision.
Evaluating the ethics of autonomous systems
MIT researchers developed a testing framework that pinpoints situations where AI decision-support systems are not treating people and communities fairly.
Preview tool helps makers visualize 3D-printed objects
By quickly generating aesthetically accurate previews of fabricated objects, the VisiPrint system could make prototyping faster and less wasteful.
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
Red-teaming a network of agents: Understanding what breaks when AI agents interact at scale
Safe agents don’t guarantee a safe ecosystem of interconnected agents. Microsoft Research examines what breaks when AI agents interact and why network-level risks require new approaches. The post Red-teaming a network of agents: Understanding what breaks when AI agents interact at scale appeared first on Microsoft Research.
AutoAdapt: Automated domain adaptation for large language models
Deploying large language models (LLMs) in real-world, high-stakes settings is harder than it should be. In high-stakes settings like law, medicine, and cloud incident response, performance and reliability can quickly break down because adapting models to domain-specific requirements is a slow and manual process that is difficult to reproduce. The…
Can we AI our way to a more sustainable world?
Doug Burger, sustainability expert Amy Luers, and optimization researcher Ishai Menache examine the global emissions implications of datacenter operations, efficiency gains, and AI's potential across electrification, materials, and food systems. The post Can we AI our way to a more sustainable world? appeared first on Microsoft Research.
New Future of Work: AI is driving rapid change, uneven benefits
For the past five years, the New Future of Work report has captured how work is changing. This year, the shift feels especially sharp. Previous editions have focused on technology’s role in increasing productivity by automating tasks, accelerating communication, and expanding access to information, as well as the rise of…
Ideas: Steering AI toward the work future we want
Microsoft Chief Scientist Jaime Teevan and researchers Jenna Butler, Jake Hofman, and Rebecca Janssen unpack the New Future of Work Report 2025 and explore the ideal AI-driven working world. Plus, is AI a tool or a collaborator? And why the answer matters. The post Ideas: Steering AI toward the work future we want…
ADeLe: Predicting and explaining AI performance across tasks
AI benchmarks report how large language models (LLMs) perform on specific tasks but provide little insight into their underlying capabilities that drive their performance. They do not explain failures or reliably predict outcomes on new tasks. To address this, Microsoft researchers in collaboration with Princeton University and Universitat Politècnica de València introduce ADeLe…
AsgardBench: A benchmark for visually grounded interactive planning
Imagine a robot tasked with cleaning a kitchen. It needs to observe its environment, decide what to do, and adjust when things don’t go as expected, for example, when the mug it was tasked to wash is already clean, or the sink is full of other items. This is the…
GroundedPlanBench: Spatially grounded long-horizon task planning for robot manipulation
Vision-language models (VLMs) use images and text to plan robot actions, but they still struggle to decide what actions to take and where to take them. Most systems split these decisions into two steps: a VLM generates a plan in natural language, and a separate model translates it into executable…
Will machines ever be intelligent?
Are machines truly intelligent? AI researchers Subutai Ahmad and Nicolò Fusi join Doug Burger to compare transformer-based AI with the human brain, exploring continual learning, efficiency, and whether today’s models are on a path toward human intelligence. The post Will machines ever be intelligent? appeared first on Microsoft Research.
Systematic debugging for AI agents: Introducing the AgentRx framework
As AI agents transition from simple chatbots to autonomous systems capable of managing cloud incidents, navigating complex web interfaces, and executing multi-step API workflows, a new challenge has emerged: transparency. When a human makes a mistake, we can usually trace the logic. But when an AI agent fails, perhaps by…