Not to be outdone by OpenAI, Apple is reportedly developing an AI wearable
Should this wearable materialize, it could be released as early as 2027, according to a report on the device.
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.
Sources: Project SGLang spins out as RadixArk with $400M valuation as inference market explodes
SGLang, which originated as an open source research project at Ion Stoica’s UC Berkeley lab, has raised capital from Accel.
A timeline of the US semiconductor market in 2025
From leadership changes at legacy semiconductor companies to wishy washy policy around chip exports, a lot happened last year.
Todoist’s app now lets you add tasks to your to-do list by speaking to its AI
The feature, now public, lets you create to-do's and action items by speaking naturally to the app's AI.
Apple plans to make Siri an AI chatbot, report says
Siri could look more like ChatGPT than its current state as an integrated feature across Apple products.
Anthropic revises Claude’s ‘Constitution,’ and hints at chatbot consciousness
The newly revised document offers a roadmap for what Anthropic says is a safer and more helpful chatbot experience.
Irony alert: Hallucinated citations found in papers from NeurIPS, the prestigious AI conference
Research from startup GPTZero points to the impossible problem prestigious conferences face in the age of AI slop.
YouTube will soon let creators make Shorts with their own AI likeness
YouTube Shorts viewers might soon see AI versions of their favorite creators when scrolling through their feeds.
OpenAI aims to ship its first device in 2026, and it could be earbuds
The AI startup is on track to announce its first hardware device in the second half of this year, OpenAI Chief Global Affairs Officer Chris Lehane said during an interview at Davos.
TechCrunch Disrupt 2026 tickets now on sale: Lowest rates all year
TechCrunch Disrupt 2026 tickets are officially on sale. Save up to $680 on your ticket and be among the first 500 registrants to score a plus-one pass at 50% off. Don't miss 10,000 tech leaders, founders, and VCs in San Francisco from October 13-15. Register before these one-time deals vanish.
Adobe Acrobat now lets you edit files using prompts, generate podcast summaries
Adobe is adding AI tools to Acrobat, including the ability to generate podcast summaries of files, create presentations, and a way for users to edit files using prompts.
Zanskar thinks 1 TW of geothermal power is being overlooked
Zanskar has raised $115 million to find about a dozen geothermal resources that could help power the grid throughout the U.S. West.
Language learning marketplace Preply’s unicorn status embodies Ukrainian resilience
Language learning marketplace Preply is now valued at $1.2 billion after raising a $150 million Series D round that marks a new chapter for the 14-year-old company.
Consumers spent more on mobile apps than games in 2025, driven by AI app adoption
Consumers spent more money in mobile apps than games in 2025, driven by AI app adoption.
Bolna nabs $6.3M from General Catalyst for its India-focused voice orchestration platform
Bolna said that 75% of its revenue is coming from self-serve customers.
Anthropic’s CEO stuns Davos with Nvidia criticism
Anthropic CEO Dario Amodei unloaded on both the administration and U.S. chip companies over plans to sell to China. The criticism was particularly notable because one of those chipmakers, Nvidia, is a major partner and investor in Anthropic.
In an effort to protect young users, ChatGPT will now predict how old you are
The feature is designed to stop problematic content from being delivered to users under the age of 18.
Elon Musk says Tesla’s restarted Dojo3 will be for ‘space-based AI compute’
Tesla aims to restart work on Dojo3, its previously abandoned third-generation AI chip. Only this time, Dojo3 won’t be aimed at training self-driving models on Earth. Instead, Musk says it will be dedicated to “space-based AI compute.”
Humans&, a ‘human-centric’ AI startup founded by Anthropic, xAI, Google alums, raised $480M seed round
Humans&, a startup that believes AI should empower people, not replace them, has reportedly raised a $480 million seed round at a $4.48 billion valuation.
Indian vibe-coding startup Emergent triples valuation to $300M with $70M fundraise
The funding comes as the startup claims it has scaled ARR to $50 million and is targeting $100 million by April 2026.
Why it’s critical to move beyond overly aggregated machine-learning metrics
New research detects hidden evidence of mistaken correlations — and provides a method to improve accuracy.
Generative AI tool helps 3D print personal items that sustain daily use
“MechStyle” allows users to personalize 3D models, while ensuring they’re physically viable after fabrication, producing unique personal items and assistive technology.
3 Questions: How AI could optimize the power grid
While the growing energy demands of AI are worrying, some techniques can also help make power grids cleaner and more efficient.
Decoding the Arctic to predict winter weather
With the help of AI, MIT Research Scientist Judah Cohen is reshaping subseasonal forecasting, with the goal of extending the lead time for predicting impactful weather.
MIT scientists investigate memorization risk in the age of clinical AI
New research demonstrates how AI models can be tested to ensure they don’t cause harm by revealing anonymized patient health data.
Guided learning lets “untrainable” neural networks realize their potential
CSAIL researchers find even “untrainable” neural nets can learn effectively when guided by another network’s built-in biases using their guidance method.
A new way to increase the capabilities of large language models
MIT-IBM Watson AI Lab researchers developed an expressive architecture that provides better state tracking and sequential reasoning in LLMs over long texts.
A “scientific sandbox” lets researchers explore the evolution of vision systems
The AI-powered tool could inform the design of better sensors and cameras for robots or autonomous vehicles.
“Robot, make me a chair”
An AI-driven system lets users design and build simple, multicomponent objects by describing them with words.
3 Questions: Using computation to study the world’s best single-celled chemists
Assistant Professor Yunha Hwang utilizes microbial genomes to examine the language of biology. Her appointment reflects MIT’s commitment to exploring the intersection of genetics research and AI.
Deep-learning model predicts how fruit flies form, cell by cell
The approach could apply to more complex tissues and organs, helping researchers to identify early signs of disease.
Enabling small language models to solve complex reasoning tasks
The “self-steering” DisCIPL system directs small models to work together on tasks with constraints, like itinerary planning and budgeting.
New method improves the reliability of statistical estimations
The technique can help scientists in economics, public health, and other fields understand whether to trust the results of their experiments.
Robots that spare warehouse workers the heavy lifting
Founded by MIT alumni, the Pickle Robot Company has developed machines that can autonomously load and unload trucks inside warehouses and logistic centers.
A smarter way for large language models to think about hard problems
This new technique enables LLMs to dynamically adjust the amount of computation they use for reasoning, based on the difficulty of the question.
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
Multimodal reinforcement learning with agentic verifier for AI agents
Argos improves multimodal RL by evaluating whether an agent’s reasoning aligns with what it observes over time. The approach reduces visual hallucinations and produces more reliable, data-efficient agents for real-world applications. The post Multimodal reinforcement learning with agentic verifier for AI agents appeared first on Microsoft Research.
OptiMind: A small language model with optimization expertise
OptiMind is a small language model that converts business operation challenges, described naturally, into mathematical formulations that optimization software can solve. It reduces formulation time & errors & enables fast, privacy-preserving local use. The post OptiMind: A small language model with optimization expertise appeared first on Microsoft Research.
Agent Lightning: Adding reinforcement learning to AI agents without code rewrites
By decoupling how agents work from how they’re trained, Agent Lightning turns each step an agent takes into data for reinforcement learning. This makes it easy for developers to improve agent performance with almost zero code changes. The post Agent Lightning: Adding reinforcement learning to AI agents without code rewrites…
Promptions helps make AI prompting more precise with dynamic UI controls
Promptions helps developers add dynamic, context-aware controls to chat interfaces so users can guide generative AI responses. It lets users shape outputs quickly without writing long instructions. The post Promptions helps make AI prompting more precise with dynamic UI controls appeared first on Microsoft Research.
GigaTIME: Scaling tumor microenvironment modeling using virtual population generated by multimodal AI
Using AI-generated virtual populations, Microsoft researchers uncovered hidden cellular patterns that could reshape how we understand and treat cancer. The post GigaTIME: Scaling tumor microenvironment modeling using virtual population generated by multimodal AI appeared first on Microsoft Research.
Ideas: Community building, machine learning, and the future of AI
As the Women in Machine Learning Workshop (WiML) marks its 20th annual gathering, cofounders, friends, and collaborators Jenn Wortman Vaughan and Hanna Wallach reflect on WiML’s evolution, navigating the field of ML, and their work in responsible AI. The post Ideas: Community building, machine learning, and the future of AI…
Reducing Privacy leaks in AI: Two approaches to contextual integrity
New research explores two ways to give AI agents stronger privacy safeguards grounded in contextual integrity. One adds lightweight, inference-time checks; the other builds contextual awareness directly into models through reasoning and RL. The post Reducing Privacy leaks in AI: Two approaches to contextual integrity appeared first on Microsoft Research.
Fara-7B: An Efficient Agentic Model for Computer Use
Fara-7B is our first agentic small language model for computer use. This experimental model includes robust safety measures to aid responsible deployment. Despite its size, Fara-7B holds its own against larger, more resource-intensive agentic systems. The post Fara-7B: An Efficient Agentic Model for Computer Use appeared first on Microsoft Research.
MMCTAgent: Enabling multimodal reasoning over large video and image collections
MMCTAgent enables dynamic multimodal reasoning with iterative planning and reflection. Built on Microsoft’s AutoGen framework, it integrates language, vision, and temporal understanding for complex tasks like long video and image analysis. The post MMCTAgent: Enabling multimodal reasoning over large video and image collections appeared first on Microsoft Research.
BlueCodeAgent: A blue teaming agent enabled by automated red teaming for CodeGen AI
BlueCodeAgent is an end-to-end blue-teaming framework built to boost code security using automated red-teaming processes, data, and safety rules to guide LLMs’ defensive decisions. Dynamic testing reduces false positives in vulnerability detection. The post BlueCodeAgent: A blue teaming agent enabled by automated red teaming for CodeGen AI appeared first on…