The 8 best AI presentation makers in 2026
The days of spending hours dragging images to just the right place on a slide are far behind us. You can now create a presentation with AI, giving the robots the job of setting the structure, adding the initial content, and executing on the aesthetics of your deck. All you have to do is tweak it with your information, human insights, and flair—and rehearse it a bit before the big performance. I spent a month testing all the best presentation software, focusing on the ones that use AI in a way t
More than half of Georgia teachers now use artificial intelligence to prepare for class - Georgia Recorder
More than half of Georgia teachers now use artificial intelligence to prepare for class Georgia Recorder
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.
Jeff Bridges Introduces Theo Von to Making AI Music With Suno: ‘It’s Very Frightening’ - Yahoo
Jeff Bridges Introduces Theo Von to Making AI Music With Suno: ‘It’s Very Frightening’ Yahoo
The White House is asking OpenAI to slow roll the release of its new model over safety concerns
OpenAI reportedly plans to share its newest model, GPT 5.6, with a select group of partners instead of with the broader public. The reason: the Trump administration told it to.
Take our I/O 2026 quiz, vibe coded in Google AI Studio.
We used Google AI Studio to vibe code a quiz about our top I/O 2026 announcements.
Check out real-life AI prototypes from the Futures Lab.
University of Waterloo students develop AI prototypes like sign language tutors to reshape the future of education and work.
Our latest Google Finance upgrades, including a new app
The new Google Finance is coming out of beta and launching a new Android app.
How Artificial Intelligence is changing the job hunt - New Jersey Education Association
How Artificial Intelligence is changing the job hunt New Jersey Education Association
9 demos of Gemini Omni and Gemini 3.5 in action
Watch 9 videos showing the capabilities of Gemini Omni and Gemini 3.5, announced at Google I/O 2026.
We’re announcing new community investments in Missouri.
We’re helping build the state’s next-generation workforce and investing in energy programs.
Asian AI startups launch Mythos-like models as Anthropic’s export ban drags on
New models are launching in Asia that promise Mythos-like capabilities without fear of an export ban. U.S. AI labs may never recover this enormous market.
Early Bird pricing ends tonight for TechCrunch Founder Summit
Save up to $190 on your pass to TechCrunch Founder Summit 2026. Early Bird pricing ends today, at 11:59 p.m. PT, after which rates increase. Register now.
The fittest founder in the room got cancer. Here’s how he used AI to fight back.
When confronted with cancer, Connor Christou fed everything tied tied to his regime — blood results, scan data, wearable output, journal entries — into Claude.
Nonprofit aims to help displaced workers as businesses adopt artificial intelligence - PBS
Nonprofit aims to help displaced workers as businesses adopt artificial intelligence PBS
California becomes the first state to launch a tool to monitor and track artificial intelligence’s impacts on the workforce - California State Portal | CA.gov
California becomes the first state to launch a tool to monitor and track artificial intelligence’s impacts on the workforce California State Portal | CA.gov
How agents are transforming work
A new OpenAI research paper shows how AI agents are transforming work, enabling longer, more complex tasks and expanding productivity across roles.
OpenAI limits GPT-5.6 rollout after government request, says restrictions shouldn’t be the norm
“We don’t believe this kind of government access process should become the long-term default,” says OpenAI. “It keeps the best tools from users, developers, enterprises, cyber defenders, and global partners who need them.”
Diagnostic Accuracy of Artificial Intelligence for Detection of Intracranial Haemorrhage on Non-contrast CT Head: A Systematic Review - Cureus
Diagnostic Accuracy of Artificial Intelligence for Detection of Intracranial Haemorrhage on Non-contrast CT Head: A Systematic Review Cureus
U.S. Loosens Restrictions on Anthropic’s Mythos A.I. Model - The New York Times
U.S. Loosens Restrictions on Anthropic’s Mythos A.I. Model The New York Times
How Omio is building the future of conversational travel
Discover how Omio uses OpenAI to power conversational travel experiences, accelerate product development, and transform into an AI-native company.
Trump administration partially lifts Anthropic’s AI export ban - Politico
Trump administration partially lifts Anthropic’s AI export ban Politico
It’s not about Anthropic vs. OpenAI anymore
AI models have progressed to the point where their capabilities have real political consequences. Dealing with those consequences will require collective action.
OpenAI’s Jalapeño chip is Big Tech’s spiciest move away from Nvidia
Nvidia has dominated the AI chip market for years, but the era of total dependence might be ending. OpenAI just shared its plans to spice things up with Jalapeño, its custom inference chip built with Broadcom, joining Google, Apple, and SpaceX in a growing list of companies building their way out of single-supplier risk. The goal is less of a […]
5 ways to learn with study notebooks in the Gemini app
Study notebooks is a new space in the Gemini app that serves as an interactive learning tool tailored to any student's goals.
Codex-maxxing for long-running work
Learn how Jason Liu uses Codex to preserve context, manage complex projects, and help work continue beyond a single prompt.
Daybreak: Tools for securing every organization in the world
OpenAI introduces new Daybreak tools, including Codex Security and GPT-5.5-Cyber, to help organizations find, validate, and patch vulnerabilities at scale.
Catch up on 12 major I/O 2026 moments
Here are 12 of the biggest Google I/O 2026 keynote moments, including news about Gemini Omni, Gemini 3.5 Flash and more.
5 ways Google parents are using Gemini
How Gemini helps with homework, meal planning and more, so parents have time to focus on the good stuff.
9 Google Forms features you should know about
Google Forms is a simple-to-use form builder app, but there seems to be a perception that it's too simple. Which is unfortunate, because it's a pretty robust tool—if you know how to use it. To demonstrate how powerful it is, here are nine Google Forms features to help you make the most of this app—from collecting and routing responses to building quizzes and customizing your form's look and feel. 9 Google Forms features you should know about Before you get started, head to docs.google.com/form
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.
Police use of artificial intelligence grows as rules lag behind - Stateline
Police use of artificial intelligence grows as rules lag behind Stateline
Anthropic Moves Toward Deal With US to Lift Curbs on AI Models - Bloomberg.com
Anthropic Moves Toward Deal With US to Lift Curbs on AI Models Bloomberg.com
A new experiment brings better group meetings to Google Beam
See and hear your colleagues in true-to-life size and sound, making hybrid meetings feel more inclusive and connected.
General Intuition’s $2.3B bet that video games can train AI agents for the real world
General Intuition has raised $320 million to scale AI trained on millions of hours of gameplay, betting action data can help AI develop something closer to human intuition.
Improving health intelligence in ChatGPT
Learn how GPT-5.5 Instant improves ChatGPT’s health and wellness responses with stronger reasoning, better context, clearer communication, and physician-informed evaluations.
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…
100 things we announced at I/O 2026
We've been busy! Here’s a rundown of the top announcements, launches and demos at I/O 2026.
The 5 best online whiteboards in 2026
Brainstorming works better visually. Sometimes that means a physical whiteboard full of sticky notes—it works. But if your team is spread between multiple offices, or works remotely, you need a virtual whiteboard. These applications take what's great about a physical whiteboard—the freewheeling, visual collaboration—and bring it to your computer screen. You can draw, drag virtual sticky notes around, and even embed images or entire documents. For the past few years, I've tested dozens of onlin
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.
Murder Victim Speaks from the Grave in Courtroom Through AI
Chris Pelkey was shot and killed in a road rage incident. At his killer’s sentencing, he forgave the man via AI. In a historic first for Arizona, and possibly the U.S., artificial intelligence was used in court to let a murder victim deliver his own victim impact statement. What happened Pelkey, a 37-year-old Army veteran, was gunned down at a red light in 2021. This month, a realistic AI version of him appeared in court to address his killer, Gabriel Horcasitas. “In another life, we probably could’ve been friends,” said AI Pelkey in the video. “I believe in forgiveness, and The post Murder Victim Speaks from the Grave in Courtroom Through AI appeared first on DailyAI.
The 5 best AI app builders in 2026
Even using no-code, building a new app can take a big chunk of your time. Setting up data sources requires smart planning and foresight. Building an intuitive user interface takes multiple tries until you find the perfect layout. And tying it all together with bug-free app logic demands attention to detail and many rounds of testing. AI helps in two ways here. The first is by turning your prompt into a first-draft app, speeding up setup. The other is by building solutions with code and placing t
Fluid, natural voice translation with Gemini 3.5 Live Translate
Gemini 3.5 Live Translate brings near real-time, natural speech translation to Google AI Studio, Google Translate and Google Meet.
Powering the world’s first AI arts museum
Refik Anadol Studio opens Dataland, the first museum of AI arts, powered by Google Cloud and supported by Google Arts & Culture.
The 8 best AI image generators in 2026
AI image generators have been brewing (generating?) up a storm for the last few years. If you've been on social media, watched prime time news shows, or read a magazine, AI-generated images have been impossible to miss. These kinds of AI-generated images are everywhere, and sometimes you won't even realize. If you want to join in the fun, or add some AI-powered features to your business workflows, the apps on this list will give you what you're looking for. I've been writing about AI image gener
Why everyone from OpenAI to SpaceX is building their own chips (and turning up the heat on Nvidia)
Nvidia has dominated the AI chip market for years, but the era of total dependence might be ending. OpenAI just shared its plans to spice things up with Jalapeño, its custom inference chip built with Broadcom, joining Google, Apple, and SpaceX in a growing list of companies building their way out of single-supplier risk. The goal is less of a […]
Helping build shared standards for advanced AI
OpenAI helps build shared standards for advanced AI, supporting evaluation frameworks, safety practices, and global cooperation through the Appia Foundation.
Apple Vision Pro exec is reportedly leaving for OpenAI
Paul Meade, the Apple vice president in charge of the Vision Pro headset, is reportedly leaving the company to join OpenAI’s hardware team.
Best Universities To Study AI in 2026
Artificial intelligence has made enormous strides in the past few years – with the introduction of a wide range of AI tools changing the landscape of how we assess data and operate within online spaces forever. This page ranks the 50 best universities to study AI around the world, based on scope, prestige, and the level of AI-related research each institution has released. Career prospects in AI There is a huge demand for individuals with a high degree of skills in artificial intelligence and machine learning, making AI a potential lucrative career prospect with countless opportunities as AI continues to The post Best Universities To Study AI in 2026 appeared first on DailyAI.
AI May Soon Help You Understand What Your Pet Is Trying to Say
Chinese tech powerhouse Baidu has filed a patent for a system that could use AI to decode animal sounds and behaviour then translate those signals into human language. For the millions of pet owners wondering what their animals are thinking, this could be the first real step toward bridging the communication gap between humans and animals. The tech Baidu’s system would collect animal vocalizations, body movements, and biological signals. It would merge that data and feed it into an AI model trained to identify emotional states. These emotional states could then be rendered in human language to boost “cross-species communication”. The post AI May Soon Help You Understand What Your Pet Is Trying to Say appeared first on DailyAI.