10 top women in AI in 2026
AI is changing our world, but the stories of who build it often get lost in the noise. Behind the headlines and hype, a group of women are solving AI’s fundamental challenges – despite working in an industry persisently impacted by gender inequality. Women make up just 22% of AI professionals worldwide and only 12% of AI researchers. In academic publishing, female researchers account for just 29% of first authors on AI papers, a number that hasn’t increased since the mid-2000s. This is a story about ten leaders who have influenced AI despite the odds being stacked against them. Their The post 10 top women in AI in 2026 appeared first on DailyAI.
How AI guardrails are impeding the work of offensive cybersecurity researchers
We spoke with several cybersecurity researchers, who look for unknown vulnerabilities and develop tools to exploit them, about how OpenAI’s and Anthropic’s guardrails affect their work.
OpenAI’s new voice mode makes it to the ChatGPT desktop app
ChatGPT Voice on desktop can work with both ChatGPT Work and Codex to complete tasks and control agents.
Beyond the Algorithm: A Critical and Evidence-Based Review of Artificial Intelligence in Chronic Pain Rehabilitation - Cureus
Beyond the Algorithm: A Critical and Evidence-Based Review of Artificial Intelligence in Chronic Pain Rehabilitation Cureus
‘AI communism’, rogue models, and the why Kimi K3 spooked Wall Street
Chinese AI lab Moonshot’s open model Kimi went viral this week for reasons that had less to do with the model itself and more to do with how the U.S. AI industry reacted to it. Meanwhile, an unreleased OpenAI model wandered outside its test environment and ended up connected to a real security breach at Hugging Face — a reminder […]
Gemini Spark updates: macOS launch, connected apps and more
The latest Gemini Spark updates brings Spark to the macOS app, connects with your favorite apps and tracks topics in real time.
Alphabet Just Proved Why It's a Top Artificial Intelligence (AI) Stock Once Again - Yahoo Finance
Alphabet Just Proved Why It's a Top Artificial Intelligence (AI) Stock Once Again Yahoo Finance
Here's how Gemini can help you avoid jetlag.
If you’ve got a faraway trip coming up, the Gemini app can help you avoid jetlag so you can make the most of your visit.Once you’ve given Gemini permission to access you…
OpenAI says its AI went rogue and launched 'unprecedented' cyber-attack - BBC
OpenAI says its AI went rogue and launched 'unprecedented' cyber-attack BBC
16 AI prompt templates for better AI agent outputs
I've gone through a lot of painful trial and error with AI prompting—a lot. Which was fine when I was experimenting in back-and-forth conversations with AI chatbots, because I could refine my prompts with every response. But it's a different story with AI agents. A weak AI prompt baked into an agent's instructions produces the same bad output—and bills you for the same mistake—every single time it runs, with no one at the keyboard to catch it. I've rounded up 16 AI prompt templates that the Zap
Anthropic updates Claude voice mode with more capable models
Claude's new voice model will let you reschedule your meeting or draft an email.
Our new community investments in Virginia support local jobs and expand energy affordability.
We’re helping build the state’s next-generation workforce and investing in energy programs.
Here’s how to ask Gemini Live for help with anything you see.
Have you ever struggled to describe something you’re looking at? Whether it’s a complex manual, a blinking error code, or a unique object, sometimes you just need an exp…
Midjourney acquired the astrology app Co-Star
The AI lab Midjourney continues to expand its purview beyond image and video generation.
Relay.app is shutting down: How to export your workflows and move to Zapier
Relay is shutting down on August 15, 2026, for free users, and on September 14 for paid plans. Either way, if you built workflows, agents, or tables in Relay, the end is near. The good news is that Relay has made it as easy as possible to transition your workflows to a new tool. Here's how to export your Relay.app data and rebuild those workflows in Zapier, plus what to expect from Zapier as a former Relay user. We'll also cover why Zapier is your best option compared to other Relay alternatives
Turn off your slop cannon
Good writing is a gift to everyone around you. Clear, concise communication means your readers spend less time decoding your words and more time acting on them. Here's how to write in a way that respects your reader's time and keeps us all from drowning in walls of text. Why this matters AI slop is real, and we can do better. The internet is full of bloated, padded writing generated (or at least inspired) by AI that optimizes for length over clarity. Don't add to it. When you write vague or word
Unlocking Britain’s next era of productivity: Building a nation of AI trailblazers
Google UK shares its latest Economic Impact Report and how to enable more people to unlock the benefits of AI-powered technologies.
Agentic AI vs. RPA: Everything you need to know
Automation has evolved far beyond simple scripts and basic workflows. While robotic process automation (RPA) has long been used to handle repetitive, rules-based work, especially inside legacy systems, agentic AI represents a newer approach to automation built for far more dynamic problems. Both are designed to reduce manual work and improve efficiency. But RPA works by mimicking human interactions with software through predefined rules and screen-based actions, while agentic AI systems are buil
The best CRM software for real estate agents in 2026
A CRM is your prized possession in real estate. You need something to keep things straight when juggling client management, property listings, and the looming threat of being upstaged by that insufferably smug agent from the office across the street. But with countless options on the market, how do you know which software is right for you? I looked into dozens of options, read approximately a million reviews, watched demos narrated by people way too cheerful for 9 a.m., and gathered insights
How Gemini is speaking the language of Southeast Asia
Gemini is taking off across Southeast Asia, thanks to its local language fluency and the region’s mobile-first population.
Introducing the ChatGPT for small business program
OpenAI launches the ChatGPT for Small Businesses program, helping entrepreneurs build AI skills, automate work, and grow with ChatGPT Work.
Introducing Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber
We’re introducing new Gemini models, including Gemini 3.6 Flash, 3.5 Flash-Lite and 3.5 Flash Cyber.
The 6 best vibe coding tools in 2026
Decades ago, building the Facebooks of the world was reserved for a small elite clad in technical skills. Today, with a sequence of good prompts, endless curiosity, and good testing practices, you too can stand next to the big names and launch your own app—and no, you don't need to know how to write a function. That's what vibe coding is all about: as coined by Andrej Karpathy, you build an app using natural language, and forget that the code is even there. While the hype is mostly gone—the firs
The latest AI news we announced in June 2026
Here are Google’s latest AI updates from June 2026.
Bluesky’s AI assistant Attie expands into an open social research tool
Users can now ask Attie questions about news, trends, and conversations on Bluesky and other apps on the AT Protocol.
Expanding Managed Agents in Gemini API: background tasks, remote MCP and more
We’re announcing new capabilities in Managed Agents in Gemini API so developers can build reliable, production-ready agents.
NTT DATA Group cuts incident analysis to 30 minutes with Codex
NTT DATA Group uses ChatGPT Enterprise and Codex to help 9,000 employees automate work, cut incident analysis to 30 minutes, and scale secure AI adoption.
New research shows how AMIE, our medical AI, could help manage health conditions.
Research in “Nature” shows our conversational AI system matches primary care physicians in complex disease management.
OpenClaw vs. Zapier: What's the difference? [2026]
If you've spent any time in AI automation circles this year, you've probably heard about OpenClaw. The open-source AI agent went from a side project to a global phenomenon in a matter of weeks, and for good reason: it gives anyone the ability to run an always-on AI assistant from their own machine, controlled through the messaging apps they already use. But popularity doesn't mean it's the right tool for every job. OpenClaw is powerful, flexible, and community-driven. It's also self-hosted, perm
Gemini can now take notes in Google Meet for Google AI Pro and Ultra subscribers.
Google Meet's "Take notes for me" feature is available to Google AI Pro and Ultra subscribers in select languages.
We’re strengthening our presence in Alabama through new investments and community support.
Google has announced a $1.5 billion investment for 2026 and 2027 to expand its data center campus in Jackson County, Alabama. Operating since 2019 on a repurposed former…
Safety and alignment in an era of long-horizon models
OpenAI shares lessons from deploying long-running AI models, highlighting new safety risks, observed failures, and improved safeguards through iterative deployment.
Advancing the next era of national science
OpenAI outlines its commitment to advancing American science working with the U.S. Department of Energy and national labs to use frontier AI to accelerate discovery.
Runway launches AI model router as generative media gets crowded
The Media Router is a tool that automatically selects the best image, video, or audio generation model for a request based on whether a developer prioritizes quality, speed or cost.
Nvidia is sending GPUs to the moon
If there's a place in the universe without GPUs, Nvidia is sending them there.
Our latest Google Finance upgrades, including a new app
The new Google Finance is coming out of beta and launching a new Android app.
OpenAI and Hugging Face partner to address security incident during model evaluation
OpenAI and Hugging Face share early findings from a security incident during AI model evaluation, highlighting advanced cyber capabilities and lessons for defenders.
Netflix Adds ChatGPT-Powered AI to Stop You From Scrolling Forever
In a bold move to tackle one of streaming’s biggest frustrations, endless scrolling, Netflix just unveiled a major redesign of its TV and mobile apps featuring a ChatGPT-powered AI chatbot and TikTok-style video reels. You’ll soon be able to ask Netflix in plain language what you’re in the mood for “funny and fast-paced” or “dark thrillers with strong female leads” and get instant, tailored recommendations. Netflix is partnering with OpenAI to power this feature, part of a broader overhaul aimed at making content discovery faster, more intuitive, and (finally) less painful. What’s changing Conversational AI Search: Powered by OpenAI, this The post Netflix Adds ChatGPT-Powered AI to Stop You From Scrolling Forever appeared first on DailyAI.
How Mach 1 uses Zapier MCP to run AI operations across 25 different companies
Most AI agents can complete a task inside a single tool. Running them reliably across an entire business is a different problem. Chris Olson is co-founder and CEO of Mach 1, an AI operations platform that helps mid-market companies deploy agents across go-to-market, customer success, sales, support, and finance operations. He developed the approach after applying AI-driven operations at a sports technology company, helping move the business from a $9 million annual cash burn to $5 million in fre
Nous Research's NousCoder-14B is an open-source coding model landing right in the Claude Code moment
Nous Research, the open-source artificial intelligence startup backed by crypto venture firm Paradigm, released a new competitive programming model on Monday that it says matches or exceeds several larger proprietary systems — trained in just four days using 48 of Nvidia's latest B200 graphics processors. The model, called NousCoder-14B, is another entry in a crowded field of AI coding assistants, but arrives at a particularly charged moment: Claude Code, the agentic programming tool from rival Anthropic, has dominated social media discussion since New Year's Day, with developers posting breathless testimonials about its capabilities. The simultaneous developments underscore how quickly AI-assisted software development is evolving — and how fiercely companies large and small are competing to capture what many believe will become a foundational technology for how software gets written. type: embedded-entry-inline id: 74cSyrq6OUrp9SEQ5zOUSl NousCoder-14B achieves a 67.87 percent accuracy rate on LiveCodeBench v6, a standardized evaluation that tests models on competitive programming problems published between August 2024 and May 2025. That figure represents a 7.08 percentage point improvement over the base model it was trained from, Alibaba's Qwen3-14B, according to Nous Research's technical report published alongside the release. "I gave Claude Code a description of the problem, it generated what we built last year in an hour," wrote Jaana Dogan, a principal engineer at Google responsible for the Gemini API, in a viral post on X last week that captured the prevailing mood around AI coding tools. Dogan was describing a distributed agent orchestration system her team had spent a year developing — a system Claude Code approximated from a three-paragraph prompt. The juxtaposition is instructive: while Anthropic's Claude Code has captured imaginations with demonstrations of end-to-end software development, Nous Research is betting that open-source alternatives trained on verifiable problems can close the gap — and that transparency in how these models are built matters as much as raw capability. How Nous Research built an AI coding model that anyone can replicate What distinguishes the NousCoder-14B release from many competitor announcements is its radical openness. Nous Research published not just the model weights but the complete reinforcement learning environment, benchmark suite, and training harness — built on the company's Atropos framework — enabling any researcher with sufficient compute to reproduce or extend the work. "Open-sourcing the Atropos stack provides the necessary infrastructure for reproducible olympiad-level reasoning research," noted one observer on X, summarizing the significance for the academic and open-source communities. The model was trained by Joe Li, a researcher in residence at Nous Research and a former competitive programmer himself. Li's technical report reveals an unexpectedly personal dimension: he compared the model's improvement trajectory to his own journey on Codeforces, the competitive programming platform where participants earn ratings based on contest performance. Based on rough estimates mapping LiveCodeBench scores to Codeforces ratings, Li calculated that NousCoder-14B's improvemen t— from approximately the 1600-1750 rating range to 2100-2200 — mirrors a leap that took him nearly two years of sustained practice between ages 14 and 16. The model accomplished the equivalent in four days. "Watching that final training run unfold was quite a surreal experience," Li wrote in the technical report. But Li was quick to note an important caveat that speaks to broader questions about AI efficiency: he solved roughly 1,000 problems during those two years, while the model required 24,000. Humans, at least for now, remain dramatically more sample-efficient learners. Inside the reinforcement learning system that trains on 24,000 competitive programming problems NousCoder-14B's training process offers a window into the increasingly sophisticated techniques researchers use to improve AI reasoning capabilities through reinforcement learning. The approach relies on what researchers call "verifiable rewards" — a system where the model generates code solutions, those solutions are executed against test cases, and the model receives a simple binary signal: correct or incorrect. This feedback loop, while conceptually straightforward, requires significant infrastructure to execute at scale. Nous Research used Modal, a cloud computing platform, to run sandboxed code execution in parallel. Each of the 24,000 training problems contains hundreds of test cases on average, and the system must verify that generated code produces correct outputs within time and memory constraints — 15 seconds and 4 gigabytes, respectively. The training employed a technique called DAPO (Dynamic Sampling Policy Optimization), which the researchers found performed slightly better than alternatives in their experiments. A key innovation involves "dynamic sampling" — discarding training examples where the model either solves all attempts or fails all attempts, since these provide no useful gradient signal for learning. The researchers also adopted "iterative context extension," first training the model with a 32,000-token context window before expanding to 40,000 tokens. During evaluation, extending the context further to approximately 80,000 tokens produced the best results, with accuracy reaching 67.87 percent. Perhaps most significantly, the training pipeline overlaps inference and verification — as soon as the model generates a solution, it begins work on the next problem while the previous solution is being checked. This pipelining, combined with asynchronous training where multiple model instances work in parallel, maximizes hardware utilization on expensive GPU clusters. The looming data shortage that could slow AI coding model progress Buried in Li's technical report is a finding with significant implications for the future of AI development: the training dataset for NousCoder-14B encompasses "a significant portion of all readily available, verifiable competitive programming problems in a standardized dataset format." In other words, for this particular domain, the researchers are approaching the limits of high-quality training data. "The total number of competitive programming problems on the Internet is roughly the same order of magnitude," Li wrote, referring to the 24,000 problems used for training. "This suggests that within the competitive programming domain, we have approached the limits of high-quality data." This observation echoes growing concern across the AI industry about data constraints. While compute continues to scale according to well-understood economic and engineering principles, training data is "increasingly finite," as Li put it. "It appears that some of the most important research that needs to be done in the future will be in the areas of synthetic data generation and data efficient algorithms and architectures," he concluded. The challenge is particularly acute for competitive programming because the domain requires problems with known correct solutions that can be verified automatically. Unlike natural language tasks where human evaluation or proxy metrics suffice, code either works or it doesn't — making synthetic data generation considerably more difficult. Li identified one potential avenue: training models not just to solve problems but to generate solvable problems, enabling a form of self-play similar to techniques that proved successful in game-playing AI systems. "Once synthetic problem generation is solved, self-play becomes a very interesting direction," he wrote. A $65 million bet that open-source AI can compete with Big Tech Nous Research has carved out a distinctive position in the AI landscape: a company committed to open-source releases that compete with — and sometimes exceed — proprietary alternatives. The company raised $50 million in April 2025 in a round led by Paradigm, the cryptocurrency-focused venture firm founded by Coinbase co-founder Fred Ehrsam. Total funding reached $65 million, according to some reports. The investment reflected growing interest in decentralized approaches to AI training, an area where Nous Research has developed its Psyche platform. Previous releases include Hermes 4, a family of models that we reported "outperform ChatGPT without content restrictions," and DeepHermes-3, which the company described as the first "toggle-on reasoning model" — allowing users to activate extended thinking capabilities on demand. The company has cultivated a distinctive aesthetic and community, prompting some skepticism about whether style might overshadow substance. "Ofc i'm gonna believe an anime pfp company. stop benchmarkmaxxing ffs," wrote one critic on X, referring to Nous Research's anime-style branding and the industry practice of optimizing for benchmark performance. Others raised technical questions. "Based on the benchmark, Nemotron is better," noted one commenter, referring to Nvidia's family of language models. Another asked whether NousCoder-14B is "agentic focused or just 'one shot' coding" — a distinction that matters for practical software development, where iterating on feedback typically produces better results than single attempts. What researchers say must happen next for AI coding tools to keep improving The release includes several directions for future work that hint at where AI coding research may be heading. Multi-turn reinforcement learning tops the list. Currently, the model receives only a final binary reward — pass or fail — after generating a solution. But competitive programming problems typically include public test cases that provide intermediate feedback: compilation errors, incorrect outputs, time limit violations. Training models to incorporate this feedback across multiple attempts could significantly improve performance. Controlling response length also remains a challenge. The researchers found that incorrect solutions tended to be longer than correct ones, and response lengths quickly saturated available context windows during training — a pattern that various algorithmic modifications failed to resolve. Perhaps most ambitiously, Li proposed "problem generation and self-play" — training models to both solve and create programming problems. This would address the data scarcity problem directly by enabling models to generate their own training curricula. "Humans are great at generating interesting and useful problems for other competitive programmers, but it appears that there still exists a significant gap in LLM capabilities in creative problem generation," Li wrote. The model is available now on Hugging Face under an Apache 2.0 license. For researchers and developers who want to build on the work, Nous Research has published the complete Atropos training stack alongside it. What took Li two years of adolescent dedication to achieve—climbing from a 1600-level novice to a 2100-rated competitor on Codeforces—an AI replicated in 96 hours. He needed 1,000 problems. The model needed 24,000. But soon enough, these systems may learn to write their own problems, teach themselves, and leave human benchmarks behind entirely. The question is no longer whether machines can learn to code. It's whether they'll soon be better teachers than we ever were.
Report claims teachers unions are expanding DEI efforts into artificial intelligence - KABB
Report claims teachers unions are expanding DEI efforts into artificial intelligence KABB
The US is advancing AI safety through state and federal action
OpenAI outlines a “reverse federalism” approach to AI governance, where state laws help build a national framework for safe, democratic AI.
Radiology artificial intelligence marketplace CARPL.ai raises $10M - Radiology Business
Radiology artificial intelligence marketplace CARPL.ai raises $10M Radiology Business
Zapier for enterprise orchestration: Scaling automation on a trusted platform
Zapier is easy to use—and sometimes ease of use gets conflated with simplicity. But at Zapier, we know that being easy to use and being enterprise-ready aren't mutually exclusive. Any enterprise tool should prioritize ease of use. If you want your entire organization to adopt software, there can't be barriers to entry. Zapier helps your entire company operate more efficiently and achieve mission-critical goals at scale. And it goes beyond workflows: Zapier is an AI orchestration platform where y
China Unveils World’s First AI Hospital: 14 Virtual Doctors Ready to Treat Thousands Daily
China has unveiled the world’s first fully AI-powered hospital, marking a radical shift in the future of healthcare. Developed by Tsinghua University in Beijing, the “Agent Hospital” features 14 AI doctors and 4 AI nurses that can diagnose, treat, and manage up to 3,000 patients per day, without any human staff. Faster, smarter care: What would take human doctors 3 years, the AI doctors can do in 1 day. High IQ bots: These AI agents scored a 93.06% pass rate on the US Medical Licensing Exam. Training without risk: The virtual hospital allows medical students to practice in a fully The post China Unveils World’s First AI Hospital: 14 Virtual Doctors Ready to Treat Thousands Daily appeared first on DailyAI.
David Vélez and Robin Vince join the boards of the OpenAI Foundation and OpenAI Group PBC
David Vélez and Robin Vince join the boards of the OpenAI Foundation and OpenAI Group PBC, bringing global leadership in finance, technology, and governance.
Integrately vs. Zapier: Which is best? [2026]
Most businesses sign up for an automation platform to fix a specific annoyance. There's only so much copy-paste work you can take before you finally reach the limits of your patience, search "Typeform to HubSpot automation," and find yourself researching whether Integrately or Zapier is the right fit. Integrately is an automation-only platform that's built for one-off workflows like this. But sooner or later, most businesses start asking more questions, like: "Can we filter leads before adding t
As US weighs response to Chinese AI, industry urges against broad open-weight restrictions
AI companies, including Nvidia and Mistral, urge policymakers to avoid broad restrictions on open-weight AI models as Washington debates responses to Chinese AI and alleged model distillation.
Why teens deserve access to safe AI
Learn how OpenAI is making ChatGPT safer for teens with age-appropriate protections, learning tools, parental controls, and expert partnerships.
5 ways Google Search can level up your thrift and vintage shopping
Uncover second-hand scores with AI tools in Google Search and Shopping.