First Look

Google has released an experimental note-taking app called Google AI Edge Foresight, according to The Verge. It transcribes meetings and audio files entirely on your device using Google's on-device EmbeddingGemma 2 model, meaning your audio never touches a cloud server.

It is free. During a meeting, you can jot shorthand bullet points and the app will turn them into polished notes using the transcript. A built-in assistant lets you ask questions about what was discussed, and you can attach local files for it to reference.

The privacy angle is the main differentiator here. Apps like Granola and Wispr Flow do similar things, but both send audio to remote servers to process it.

Currently only available for Macs with Apple Silicon (M-series chips). Windows is not supported.

Honest read: Worth trying if you're on a compatible Mac and privacy is why you've avoided AI note-taking apps until now — this closes the main objection.

Most Arabic language models are trained primarily on Modern Standard Arabic, the formal written dialect used in news and textbooks. That is not how most Arabic speakers actually talk. Falcon-Emirati-7B, built by the UAE's Technology Innovation Institute, is a 7-billion-parameter model fine-tuned (adapted from a general model using targeted training) specifically on Emirati Arabic — its vocabulary, grammar, poetry, proverbs, and cultural context.

It builds on Falcon-H1-Arabic, which already handled a broad mix of Arabic dialects. This version pushes that foundation specifically toward Emirati Gulf speech. It supports context windows (the amount of text a model can read at once) of up to 128,000 tokens, making it capable with long documents.

It is available now on Hugging Face. No pricing was listed for API access; the model weights are downloadable.

Honest read: Worth watching if you work with Gulf Arabic content — this is a genuine gap most models ignore. For everyone else, there is nothing to act on yet.

Meta has released the code behind Muse — its AI agent (a system that can carry out tasks on your behalf, rather than just answer questions) — so that anyone can build their own Muse-powered gadgets, according to The Verge.

The idea is that a hobbyist can load Muse onto a Raspberry Pi (a small, cheap single-board computer often used for DIY projects) or an ESP32 board (a low-cost microcontroller chip) and connect it to displays, buttons, sensors, or whatever else they have available. Meta suggests builds like a colour e-ink reminder display or a screen that connects to a TV.

Meta is also giving away a ready-made version called Muse Home Link, which lets Muse control lights, a TV, or a printer through community-built skills. Only 5,000 units are being distributed; you can join the waitlist now for shipping later this month.

This is for builders and tinkerers, not casual users. There is no app to download here.

Honest read: Worth watching if you enjoy hardware projects, but anyone hoping for a simple smart-home AI setup will find this underbaked — you are essentially providing the product Meta hasn't finished making yet.

Google has announced Gemini 4 Argon, its latest frontier model — meaning a model operating at the upper edge of what current AI systems can do — targeted at complex tasks in software engineering, legal work, finance, and cybersecurity, according to The Verge.

The catch: it is not available to the public yet. Access is currently limited to a "set of trusted cyber defenders," and Google says it is going through the US government's voluntary pre-release review process before a broader rollout. Google is also reportedly already using the model in its own internal workflows.

Google shared a benchmark chart showing Gemini 4 Argon outperforming models from OpenAI and Anthropic. Those benchmarks were run by Google. No independent evaluation has been published.

The announcement came one day after OpenAI's developer conference, which itself featured new model and agent releases. The timing is not subtle.

Honest read: Worth watching, not worth acting on. The model is not publicly available, the benchmarks are self-reported, and the access restrictions are real. Check back when independent testers have had a go.

GPT-6.1 Sol is an upgraded version of OpenAI's GPT-6 Sol model, aimed at developers and businesses running AI on documents, code, and multi-step workflows. According to OpenAI, it sits between GPT-6 Sol and the more powerful GPT-6 Astra in capability, at roughly one-fifth of Astra's price.

On DeepSWE v1.1 — a benchmark measuring performance on real software codebases, run by OpenAI — it matches GPT-6 Astra's score. On AutomationBench, which tests multi-step business workflow completion, it scores 2.2 points above Anthropic's Opus 5.5 at a third of the cost, in OpenAI's own testing.

All benchmarks cited are from OpenAI's internal evaluations. No independent verification has been published.

Who it is for: developers building AI tools who currently use Astra but need to reduce costs, and businesses running large volumes of document or workflow tasks.

There is a free tier for ChatGPT users with usage caps; API pricing starts at $0.10 per million cached input tokens (a token is roughly one word).

Honest read: Worth serious attention from developers already in OpenAI's ecosystem — the cost reduction is substantial if the benchmark scores hold under independent testing, which has not happened yet.

Microsoft has officially launched a redesigned Copilot app, according to The Verge. Copilot is Microsoft's AI assistant, built into Windows and its Office products. The new version organises everything into three tabs: Home (chat and task management), Code (build simple apps and dashboards without programming knowledge), and Autopilot.

Autopilot is the one worth understanding. Previously called Scout, it is a cloud-based AI agent — a system that runs tasks on your behalf continuously, even when your computer is off. It can monitor email threads, respond to Teams messages, and handle recurring tasks. Microsoft has built in enterprise-level permissions and audit controls, which is the main pitch to businesses.

Pricing has changed too: the base licence covers Copilot in Word, Excel, and Outlook, but the agentic features bill by usage, so heavy use will cost more.

This is available to Microsoft 365 users now, though agentic features are rolling out to enterprise customers first.

Honest read: Worth watching if you live in Microsoft's ecosystem — Autopilot is a genuinely different kind of assistant — but the usage-based pricing means costs could climb fast for teams that actually use it.

Google has launched an early-preview feature for Pixel 11 that lets Gemini — Google's AI assistant — make phone calls to local businesses on your behalf, according to The Verge.

Tell it to make a reservation, check if a product is in stock, or reschedule an appointment. Gemini dials the number, navigates hold music and automated menus, and holds a conversation with whoever picks up. You watch a live transcript the whole time and can take the call over at any point.

Google trialled something similar last year, but that version did not let you jump in. This one does.

It is available now, but only for Gemini paid subscribers who have enrolled in the Phone by Google Public Beta on Pixel 11 in the US.

Honest read: Worth trying if you are on Pixel 11 and hate hold queues — but the narrow eligibility means most readers will be watching from the sidelines for now.

Hugging Face has updated its Transformers library — a widely used software toolkit for working with AI models — to support GGUF files natively, according to Hugging Face's blog.

GGUF is a file format (developed by the team behind llama.cpp, a tool for running AI models locally) that packages a model's weights, settings, and templates into a single download. Crucially, GGUF supports quantization — a process that compresses model files by using lower-precision numbers, trading a small amount of quality for a much smaller memory footprint. That is what makes running capable models on a laptop realistic.

Previously, using GGUF models meant going through separate applications like Ollama or LM Studio. Now you can load them directly in Python with a single line of code. For now, this works on Apple Silicon Macs and focuses on the Qwen3.5 model family.

Who it's for: developers and technically comfortable users who want more control over how they run local AI models without switching between tools.

Honest read: Genuinely useful if you already work with Transformers — one fewer tool in the chain. If you're a non-developer who runs local models through Ollama or LM Studio, those apps still work fine and nothing here changes your setup.

Claude Code is Anthropic's AI coding tool. Its revamped Projects feature, detailed by The Verge, lets you run a team of AI coding agents simultaneously in the cloud rather than managing one at a time.

Each project has a coordinator agent that assigns work across multiple threads — individual agents each working on their own copy of the codebase in parallel. When threads touch the same code, clashes are handled the same way a standard code merge works. You can talk to individual threads or oversee everything from a single project chat.

It is aimed squarely at developers handling large or complex coding tasks, not casual users. Free tier details are not confirmed; it launches in beta for select Claude Pro and Max subscribers, with broader access coming later. Enterprise users are also included in the rollout.

The local tools and code support is listed as "coming very soon" — not available today.

Honest read: Worth watching if you use Claude Code professionally — parallel agents on complex tasks is a genuine workflow improvement — but the beta access restrictions and missing local support mean most users cannot get full value from it yet.

Google Home MCP is a new integration that lets third-party AI agents — tools like Claude, rather than Google's own assistant — read your smart home data and control your devices directly, according to The Verge.

MCP stands for Model Context Protocol (a standardised way for AI agents to connect to external systems, like a universal plug socket for software). The integration means you could ask Claude to review your camera footage from the last hour, track how many laundry cycles ran last week, or build a custom control dashboard — in plain English, through a chat window.

It is aimed at people who already pay for Google Home Premium Advanced ($20 a month or $200 a year) and are comfortable setting up a Google Cloud project to get it running. That is not a weekend-click-through setup.

Google says safety limits are in place — an agent cannot unlock your front door — but the company's own product manager notes that connecting an agent to your home "can result in unexpected or even undesired behavior."

Honest read: Worth watching if you run a Google Home setup and enjoy tinkering, but the setup friction and the $20/month requirement make this a tool for enthusiasts rather than most users — and the security implications of giving a third-party AI agent access to your locks and cameras deserve more scrutiny than a blog post caveat.