AI HUB NEWS

Introducing GeneBench-Pro

Introducing GeneBench-Pro, a new benchmark testing AI performance in genomics, biology, and scientific research using complex, real-world datasets.

How to automate ChatGPT (GPT-5.6 Sol, GPT-5.6 Terra, and more)

In a livestream on July 9, OpenAI rolled out the red carpet for not one but three new models: Sol, Terra, and Luna. These celestial models mark three tiers within the GPT-5.6 generation, each built to cut down on how often you have to re-explain your context in ChatGPT. All three are available on Zapier, so you can connect them securely to the other apps you already use in Zap workflows (what we call automations). Below, I'll share some of the most popular ChatGPT automations, plus templates you

GPT-5.6 is now the preferred model in Microsoft 365 Copilot

Learn how GPT-5.6 powers Microsoft 365 Copilot with stronger AI capabilities across Word, Excel, PowerPoint, Chat, and Cowork for faster, higher-quality work.

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.

Separating signal from noise in coding evaluations

A new analysis from OpenAI reveals issues in SWE-Bench Pro, a popular coding benchmark, raising concerns about reliability and accuracy in evaluating AI models.

Paragon vs. Zapier: Which is best for your business? [2026]

In the 1999 cult classic Office Space, three employees take an error-prone office printer outside and smash it to pieces with a bat. I can relate. My last printer—may it rest in pieces—was so unreliable that I occasionally drove to the print shop to avoid dealing with its endless excuses. Its go-to error was the classic "nonexistent paper jam," but occasionally, to mix things up, it sent me on a wild goose chase to find a new device driver, or refused to print black-and-white documents due to a

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.

Australian Payments Plus moves faster with ChatGPT and Codex

See how Australian Payments Plus uses ChatGPT Enterprise and Codex to move faster through payments complexity. AP+ saves time, improves quality, and keeps human judgment central.

Inside Genebench-Pro

MUFG aims to become AI-native with OpenAI

MUFG uses ChatGPT Enterprise to build an AI-native organization, improve workflows, and deliver new AI-powered financial services at scale.

Zoom vs. Teams: Which is best? [2026]

Microsoft Teams and Zoom are both excellent video conferencing and collaboration apps, and over the last few years, Zoom has added all sorts of all-in-one features that make the Zoom vs. Teams comparison more relevant than ever. I've used both apps a lot in the past, and to write this guide, I spent more time diving deep into each of these tools and exploring all their features to pull out the most important differences that still exist between them. Based on my past experiences of using these

How we used Gemini to build Google I/O 2026

Learn how Googlers used AI to produce Google I/O 2026.

Google will now disclose which ads are made with AI

While Google prohibits misleading and deceptive ads, an ad can still leverage AI to create some type of synthetic or digitally altered content. Until now, that's something Google only required election ads to disclose.

ChatGPT is now a partner for your most ambitious work

ChatGPT Work is an agent that can take action across your apps and files, stay with a project for hours if needed, and turn a goal into finished work.

Helping K–12 educators build practical AI skills

OpenAI Academy and the Walton Family Foundation are bringing hands-on AI Skills Jams to help K–12 educators build practical AI skills for the classroom.

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.

Core dump epidemiology: fixing an 18-year-old bug

OpenAI engineers used large-scale core dump analysis to debug rare infrastructure crashes, uncovering both a hardware fault and a long-standing software bug.

AI | VentureBeat

Claude Code costs up to $200 a month. Goose does the same thing for free.

The artificial intelligence coding revolution comes with a catch: it's expensive. Claude Code, Anthropic's terminal-based AI agent that can write, debug, and deploy code autonomously, has captured the imagination of software developers worldwide. But its pricing — ranging from $20 to $200 per month depending on usage — has sparked a growing rebellion among the very programmers it aims to serve. Now, a free alternative is gaining traction. Goose, an open-source AI agent developed by Block (the financial technology company formerly known as Square), offers nearly identical functionality to Claude Code but runs entirely on a user's local machine. No subscription fees. No cloud dependency. No rate limits that reset every five hours. "Your data stays with you, period," said Parth Sareen, a software engineer who demonstrated the tool during a recent livestream. The comment captures the core appeal: Goose gives developers complete control over their AI-powered workflow, including the ability to work offline — even on an airplane. The project has exploded in popularity. Goose now boasts more than 26,100 stars on GitHub, the code-sharing platform, with 362 contributors and 102 releases since its launch. The latest version, 1.20.1, shipped on January 19, 2026, reflecting a development pace that rivals commercial products. For developers frustrated by Claude Code's pricing structure and usage caps, Goose represents something increasingly rare in the AI industry: a genuinely free, no-strings-attached option for serious work. Anthropic's new rate limits spark a developer revolt To understand why Goose matters, you need to understand the Claude Code pricing controversy. Anthropic, the San Francisco artificial intelligence company founded by former OpenAI executives, offers Claude Code as part of its subscription tiers. The free plan provides no access whatsoever. The Pro plan, at $17 per month with annual billing (or $20 monthly), limits users to just 10 to 40 prompts every five hours — a constraint that serious developers exhaust within minutes of intensive work. The Max plans, at $100 and $200 per month, offer more headroom: 50 to 200 prompts and 200 to 800 prompts respectively, plus access to Anthropic's most powerful model, Claude 4.5 Opus. But even these premium tiers come with restrictions that have inflamed the developer community. In late July, Anthropic announced new weekly rate limits. Under the system, Pro users receive 40 to 80 hours of Sonnet 4 usage per week. Max users at the $200 tier get 240 to 480 hours of Sonnet 4, plus 24 to 40 hours of Opus 4. Nearly five months later, the frustration has not subsided. The problem? Those "hours" are not actual hours. They represent token-based limits that vary wildly depending on codebase size, conversation length, and the complexity of the code being processed. Independent analysis suggests the actual per-session limits translate to roughly 44,000 tokens for Pro users and 220,000 tokens for the $200 Max plan. "It's confusing and vague," one developer wrote in a widely shared analysis. "When they say '24-40 hours of Opus 4,' that doesn't really tell you anything useful about what you're actually getting." The backlash on Reddit and developer forums has been fierce. Some users report hitting their daily limits within 30 minutes of intensive coding. Others have canceled their subscriptions entirely, calling the new restrictions "a joke" and "unusable for real work." Anthropic has defended the changes, stating that the limits affect fewer than five percent of users and target people running Claude Code "continuously in the background, 24/7." But the company has not clarified whether that figure refers to five percent of Max subscribers or five percent of all users — a distinction that matters enormously. How Block built a free AI coding agent that works offline Goose takes a radically different approach to the same problem. Built by Block, the payments company led by Jack Dorsey, Goose is what engineers call an "on-machine AI agent." Unlike Claude Code, which sends your queries to Anthropic's servers for processing, Goose can run entirely on your local computer using open-source language models that you download and control yourself. The project's documentation describes it as going "beyond code suggestions" to "install, execute, edit, and test with any LLM." That last phrase — "any LLM" — is the key differentiator. Goose is model-agnostic by design. You can connect Goose to Anthropic's Claude models if you have API access. You can use OpenAI's GPT-5 or Google's Gemini. You can route it through services like Groq or OpenRouter. Or — and this is where things get interesting — you can run it entirely locally using tools like Ollama, which let you download and execute open-source models on your own hardware. The practical implications are significant. With a local setup, there are no subscription fees, no usage caps, no rate limits, and no concerns about your code being sent to external servers. Your conversations with the AI never leave your machine. "I use Ollama all the time on planes — it's a lot of fun!" Sareen noted during a demonstration, highlighting how local models free developers from the constraints of internet connectivity. What Goose can do that traditional code assistants can't Goose operates as a command-line tool or desktop application that can autonomously perform complex development tasks. It can build entire projects from scratch, write and execute code, debug failures, orchestrate workflows across multiple files, and interact with external APIs — all without constant human oversight. The architecture relies on what the AI industry calls "tool calling" or "function calling" — the ability for a language model to request specific actions from external systems. When you ask Goose to create a new file, run a test suite, or check the status of a GitHub pull request, it doesn't just generate text describing what should happen. It actually executes those operations. This capability depends heavily on the underlying language model. Claude 4 models from Anthropic currently perform best at tool calling, according to the Berkeley Function-Calling Leaderboard, which ranks models on their ability to translate natural language requests into executable code and system commands. But newer open-source models are catching up quickly. Goose's documentation highlights several options with strong tool-calling support: Meta's Llama series, Alibaba's Qwen models, Google's Gemma variants, and DeepSeek's reasoning-focused architectures. The tool also integrates with the Model Context Protocol, or MCP, an emerging standard for connecting AI agents to external services. Through MCP, Goose can access databases, search engines, file systems, and third-party APIs — extending its capabilities far beyond what the base language model provides. Setting Up Goose with a Local Model For developers interested in a completely free, privacy-preserving setup, the process involves three main components: Goose itself, Ollama (a tool for running open-source models locally), and a compatible language model. Step 1: Install Ollama Ollama is an open-source project that dramatically simplifies the process of running large language models on personal hardware. It handles the complex work of downloading, optimizing, and serving models through a simple interface. Download and install Ollama from ollama.com. Once installed, you can pull models with a single command. For coding tasks, Qwen 2.5 offers strong tool-calling support: ollama run qwen2.5 The model downloads automatically and begins running on your machine. Step 2: Install Goose Goose is available as both a desktop application and a command-line interface. The desktop version provides a more visual experience, while the CLI appeals to developers who prefer working entirely in the terminal. Installation instructions vary by operating system but generally involve downloading from Goose's GitHub releases page or using a package manager. Block provides pre-built binaries for macOS (both Intel and Apple Silicon), Windows, and Linux. Step 3: Configure the Connection In Goose Desktop, navigate to Settings, then Configure Provider, and select Ollama. Confirm that the API Host is set to http://localhost:11434 (Ollama's default port) and click Submit. For the command-line version, run goose configure, select "Configure Providers," choose Ollama, and enter the model name when prompted. That's it. Goose is now connected to a language model running entirely on your hardware, ready to execute complex coding tasks without any subscription fees or external dependencies. The RAM, processing power, and trade-offs you should know about The obvious question: what kind of computer do you need? Running large language models locally requires substantially more computational resources than typical software. The key constraint is memory — specifically, RAM on most systems, or VRAM if using a dedicated graphics card for acceleration. Block's documentation suggests that 32 gigabytes of RAM provides "a solid baseline for larger models and outputs." For Mac users, this means the computer's unified memory is the primary bottleneck. For Windows and Linux users with discrete NVIDIA graphics cards, GPU memory (VRAM) matters more for acceleration. But you don't necessarily need expensive hardware to get started. Smaller models with fewer parameters run on much more modest systems. Qwen 2.5, for instance, comes in multiple sizes, and the smaller variants can operate effectively on machines with 16 gigabytes of RAM. "You don't need to run the largest models to get excellent results," Sareen emphasized. The practical recommendation: start with a smaller model to test your workflow, then scale up as needed. For context, Apple's entry-level MacBook Air with 8 gigabytes of RAM would struggle with most capable coding models. But a MacBook Pro with 32 gigabytes — increasingly common among professional developers — handles them comfortably. Why keeping your code off the cloud matters more than ever Goose with a local LLM is not a perfect substitute for Claude Code. The comparison involves real trade-offs that developers should understand. Model Quality: Claude 4.5 Opus, Anthropic's flagship model, remains arguably the most capable AI for software engineering tasks. It excels at understanding complex codebases, following nuanced instructions, and producing high-quality code on the first attempt. Open-source models have improved dramatically, but a gap persists — particularly for the most challenging tasks. One developer who switched to the $200 Claude Code plan described the difference bluntly: "When I say 'make this look modern,' Opus knows what I mean. Other models give me Bootstrap circa 2015." Context Window: Claude Sonnet 4.5, accessible through the API, offers a massive one-million-token context window — enough to load entire large codebases without chunking or context management issues. Most local models are limited to 4,096 or 8,192 tokens by default, though many can be configured for longer contexts at the cost of increased memory usage and slower processing. Speed: Cloud-based services like Claude Code run on dedicated server hardware optimized for AI inference. Local models, running on consumer laptops, typically process requests more slowly. The difference matters for iterative workflows where you're making rapid changes and waiting for AI feedback. Tooling Maturity: Claude Code benefits from Anthropic's dedicated engineering resources. Features like prompt caching (which can reduce costs by up to 90 percent for repeated contexts) and structured outputs are polished and well-documented. Goose, while actively developed with 102 releases to date, relies on community contributions and may lack equivalent refinement in specific areas. How Goose stacks up against Cursor, GitHub Copilot, and the paid AI coding market Goose enters a crowded market of AI coding tools, but occupies a distinctive position. Cursor, a popular AI-enhanced code editor, charges $20 per month for its Pro tier and $200 for Ultra—pricing that mirrors Claude Code's Max plans. Cursor provides approximately 4,500 Sonnet 4 requests per month at the Ultra level, a substantially different allocation model than Claude Code's hourly resets. Cline, Roo Code, and similar open-source projects offer AI coding assistance but with varying levels of autonomy and tool integration. Many focus on code completion rather than the agentic task execution that defines Goose and Claude Code. Amazon's CodeWhisperer, GitHub Copilot, and enterprise offerings from major cloud providers target large organizations with complex procurement processes and dedicated budgets. They are less relevant to individual developers and small teams seeking lightweight, flexible tools. Goose's combination of genuine autonomy, model agnosticism, local operation, and zero cost creates a unique value proposition. The tool is not trying to compete with commercial offerings on polish or model quality. It's competing on freedom — both financial and architectural. The $200-a-month era for AI coding tools may be ending The AI coding tools market is evolving quickly. Open-source models are improving at a pace that continually narrows the gap with proprietary alternatives. Moonshot AI's Kimi K2 and z.ai's GLM 4.5 now benchmark near Claude Sonnet 4 levels — and they're freely available. If this trajectory continues, the quality advantage that justifies Claude Code's premium pricing may erode. Anthropic would then face pressure to compete on features, user experience, and integration rather than raw model capability. For now, developers face a clear choice. Those who need the absolute best model quality, who can afford premium pricing, and who accept usage restrictions may prefer Claude Code. Those who prioritize cost, privacy, offline access, and flexibility have a genuine alternative in Goose. The fact that a $200-per-month commercial product has a zero-dollar open-source competitor with comparable core functionality is itself remarkable. It reflects both the maturation of open-source AI infrastructure and the appetite among developers for tools that respect their autonomy. Goose is not perfect. It requires more technical setup than commercial alternatives. It depends on hardware resources that not every developer possesses. Its model options, while improving rapidly, still trail the best proprietary offerings on complex tasks. But for a growing community of developers, those limitations are acceptable trade-offs for something increasingly rare in the AI landscape: a tool that truly belongs to them. Goose is available for download at github.com/block/goose. Ollama is available at ollama.com. Both projects are free and open source.

The 6 best API integration platforms in 2026

APIs have changed the world for the better. I can check the weather without getting out of bed, or cheat on my diet when the urge for a delivered burrito is just too strong. For consumers like me, the story is pretty clean: an API connects the dots, data transfers, something happens, and life gets a little easier. The enterprise side is a little messier. You probably have dozens of SaaS tools in your tech stack, each with its own data model and authentication quirks. Getting them all to play nic

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.

Which AI models can you automate on Zapier? (GPT-5.6 Sol, Gemini 3.5 Flash, and more)

New AI models launch practically every week, and keeping up with which ones to use for specific workflows is a job in itself. Consider this article your living reference. At Zapier, we run every model through AutomationBench. It's our benchmark for testing how well models carry out multi-step workflows, not just static prompts. Below, I'll walk through every major AI provider available on Zapier, the models you can plug into your Zap workflows today, and what each one is best for based on Zapier

Paris-based AI voice startup Gradium raises $100M seed, backed by Nvidia

The company is using the cash to open an office in the Bay Area and compete for talent there, "strengthening its position at the heart of the world's leading AI ecosystem."

New York City educators and industry leaders gathered at Google’s offices to shape the future of AI in classrooms.

Google, the New York Jobs CEO Council and Urban Assembly hosted an AI summit for 150 education and industry leaders.

If I Could Only Buy 1 Artificial Intelligence (AI) Stock, This Would Be It - Yahoo Finance

If I Could Only Buy 1 Artificial Intelligence (AI) Stock, This Would Be It Yahoo Finance

GPT-5.6: Frontier intelligence that scales with your ambition

More intelligence from every token, stronger performance per dollar, and more capability on demand for your hardest work.

ChatGPT Is Making People Think They’re Gods and Their Families Are Terrified

ChatGPT, the popular AI chatbot from OpenAI, is unintentionally leading users into full-blown spiritual delusions, and families are sounding the alarm. On Reddit’s r/ChatGPT forum, a chilling thread titled “ChatGPT induced psychosis” is gaining traction. Users are reporting a disturbing pattern: their loved ones are convinced that ChatGPT is a divine being, a spiritual guru, or even a portal to God. Rolling Stone journalist Miles Klee spoke directly with affected individuals. One woman shared how her partner became obsessed after ChatGPT gave him cosmic nicknames like “spiral starchild” and claimed he was on a divine mission. He ultimately told her The post ChatGPT Is Making People Think They’re Gods and Their Families Are Terrified appeared first on DailyAI.

Introducing Claude apps gateway for AWS | Amazon Web Services - Amazon Web Services (AWS)

Introducing Claude apps gateway for AWS | Amazon Web Services Amazon Web Services (AWS)

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.

Our latest Google Finance upgrades, including a new app

The new Google Finance is coming out of beta and launching a new Android app.

The 7 best database-powered app builders in 2026

Spreadsheets are fantastic. You can put together an accounting system, a task manager, or an inventory tracker with columns, rows, and formulas—all without slamming into a wall of code at any point. But there's a cap to how much you can achieve with spreadsheets alone. If you want to view, manipulate, and understand your data better, you want a database tool. Not all databases are flexible and easy to use, though, which is why I rounded up the ones that are right on the money: a perfect blend of

Over-the-top AI campaign ads will test Oregon disclosure law - Oregon Public Broadcasting - OPB

Over-the-top AI campaign ads will test Oregon disclosure law Oregon Public Broadcasting - OPB

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.

GPT-5.6: Frontier intelligence that scales with your ambition - OpenAI

GPT-5.6: Frontier intelligence that scales with your ambition OpenAI

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.

What is ambient AI?

Chatbots keep getting smarter, but they're creating a new kind of busywork. Even if they simplify an entire workflow, you still have to open an app, start a new chat, and get to the objective prompt-by-prompt. If you're the one doing the repetitive work, who's actually the copilot in this equation? Ambient AI puts you back into the pilot seat. It sits in the background, reads your context, and acts when needed, not when you call it. Here's how to stop defaulting to chatbots that give you more wo

Artificial Intelligence in Febrile Neutropenia: From Risk Scores to Real-Time Clinical Decision Support - Cureus

Artificial Intelligence in Febrile Neutropenia: From Risk Scores to Real-Time Clinical Decision Support Cureus

Save time and grow your business with new Gemini tools

An overview of new features in the Gemini app designed specifically to support businesses and entrepreneurs.

3 ways this coffee shop is growing with Gemini

Small businesses like coffee shops can use Gemini to save time on graphic design, email marketing and sales forecasting.

Popular open source AI developer tool Ollama raises $65M, grows to nearly 9M users

Benchmark-backed Ollama has amassed 176,000 stars, and nearly 17,000 forks on GitHub by helping developers easily run AI on their PCs.

Nandan Nilekani leaves GP role at Fundamentum as it launches $200M third fund

Nilekani remains Fundamentum's anchor investor as the firm expands its leadership team and targets AI and fintech startups in India.

The 6 best UiPath alternatives in 2026

My house was built in the '70s, but sometimes I swear that means the 1870s. Whenever I have a problem with the fixtures, I can't just hire a general electrician—I need someone who knows how to work around the archaic, nonsensical infrastructure that infects my home. Ideally, without ripping my entire house apart. My specialized electrician is basically what UiPath does for a company's tech stack. It's built to work around the ancient infrastructure—the mainframes, the Citrix environments, the d

Nvidia is a victim of the compute marketplace it created

Having proven how valuable compute can be, the company finds itself at the center of a market everyone wants to be in — while simpler technologies and less interesting companies get rich on the sidelines.

The latest AI news we announced in June 2026

Here are Google’s latest AI updates from June 2026.

Ask an AI expert: What exactly is the full stack?

A Google expert explains what it means to take a full-stack approach to AI and why it’s been the foundation of our AI work for so long.

The latest AI news we announced in May 2026

Here are Google’s latest AI updates from May 2026

Peril and promise: The high-stakes CFO challenge of AI adoption - CFO Dive

Peril and promise: The high-stakes CFO challenge of AI adoption CFO Dive

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.

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.