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Hand-picked stories worth reading right now101 articles found · page 1 of 2
My yard is dying, so I made an app for that
Verge senior reviewer Allison Johnson recounts using Google's AI tools to vibe-code an Android app that helps her manage her neglected yard. After ignoring their yard for years and losing a long battle with weeds, she decided to build an app instead of hiring help again. Using Google's AI Studio and Gemini, she produced a working app from a single natural-language prompt within minutes, then iterated on its design and bugs. The piece is a first-person account of what vibe-coding feels like for a non-developer.
Apple's new AI photo editing tools mostly work, for better and worse
Apple is adding generative AI photo editing tools to the iPhone for the first time as part of the iOS 27 developer beta. The Verge tested three new features: a much-improved Clean Up tool for removing objects, an Extend tool that paints in extra space at the edges of a photo, and Spatial Reframing, which mimics moving the camera to recompose a shot. The reviewer found the tools mostly work, with Clean Up being the most reliable and Spatial Reframing being the most ambitious and most problematic.
Siri is good now??
On an episode of The Verge's Vergecast podcast, hosts David Pierce and Nilay Patel discuss their first experiences with Apple's new Siri AI, which they found to be surprisingly good after years of the assistant being unreliable. They argue that Siri AI does not feel cutting-edge but works well enough at most tasks, which could be significant for users and the wider AI industry. The episode also covers changes in social networking and a lightning round of other tech news.
Built from the inside out: How AWS Professional Services became a frontier team first
AWS Professional Services (AWS ProServe) says it compressed engagement timelines from months to days. According to the post, it achieved this not by adding AI tools to an existing process but by fundamentally rebuilding how it delivers work from the inside out. The post promises to share how AWS ProServe became what it calls a frontier team, the practices that enabled it, and what other engineering organizations can take from the experience.
Save Big and Play Bigger: GeForce NOW Summer Sale Brings Major Membership Savings
NVIDIA confirmed that its top GeForce NOW cloud gaming tier now runs on RTX 5080-class servers worldwide, streaming demanding PC games at up to 4K resolution and up to 120 frames per second to ordinary devices. The company also added eight new games this week and scheduled more for the weeks ahead. The update shows how cloud streaming moves heavy graphics processing off the user's device and onto remote data centers.
The $100M+ Round Is Now Just Your Typical Late-Stage Financing
The median U.S. late-stage startup funding round reached exactly $100 million in 2026, according to new Crunchbase data. That figure is roughly double the just-over-$50-million median from 2020, meaning a nine-figure raise no longer marks a standout deal. So far in 2026, U.S. companies have closed 250 rounds of $100 million or more, with half of those at $200 million or above.
How frontier teams are reinventing AI-native development
AWS says the largest gains from AI in software development come from teams that redesign how they work around AI agents, not from teams that treat AI as a faster way to type. Across more than 50 internal teams studied, the 25 groups that adopted both new tools and new practices reached a 4.5x median productivity gain, and some passed 10x in deployment velocity. AWS calls these its frontier teams and lays out five habits behind the results.
For Robotaxis, Safety Must Be Built In, Not Bolted On
NVIDIA introduced Halos OS, a unified safety foundation designed to build vehicle safety into the core of robotaxi systems rather than adding it later. The system runs on NVIDIA DRIVE Hyperion, meets the ISO 26262 ASIL D automotive safety standard, and is structured in layers that isolate safety-critical software from the rest of the driving stack. NVIDIA frames the move as a response to robotaxis shifting from test pilots to paid commercial rides in dozens of cities.
LLM Routing: From Strategy Selection to Production Architecture
LLM routing is a design pattern where a control layer reads each incoming AI request and sends it to the best-fit model instead of pushing everything to one expensive default. A new guide from n8n explains how this trims cost and response time by matching simple questions to cheaper, faster models while reserving premium models for hard work. The guide cites Berkeley's RouteLLM, which holds 95% of GPT-4 quality while cutting cost by more than 85% on one benchmark, and FrugalGPT, which matched GPT-4 quality at up to 98% lower cost.
Top Process Orchestration Tools and Their Key Benefits
A guide from n8n reviews seven process orchestration platforms and the features that set them apart: n8n, Camunda, Appian, Microsoft Power Automate, Pega, Temporal, and Salesforce Flow. Process orchestration coordinates the steps, systems, and people inside a larger business workflow, going beyond the single isolated tasks that simple automation handles. The guide cites a 2025 Camunda survey of 800 IT leaders, in which 93 percent said AI must be fully integrated into orchestrated processes to maximize return. Because swapping an orchestration platform is hard once a team is trained on it, the guide urges consolidating on one tool rather than fragmenting governance across several.
Fluid, natural voice translation with Gemini 3.5 Live Translate
Google released Gemini 3.5 Live Translate on June 9, 2026, an audio model that turns spoken words into spoken words in another language within a few seconds. It covers more than 70 languages, detects each one automatically, and keeps the original speaker's intonation, pacing and pitch so the output sounds human rather than robotic. The model ships at once across three products: Google AI Studio for developers, Google Meet for business customers, and the Google Translate app for everyday users.
LLM Observability: What To Instrument and How To Act on It
LLM observability is the practice of capturing what an AI model saw, why it decided, and what it returned, so silent failures become debuggable. Unlike traditional software where errors are obvious, language models can run perfectly while producing wrong or made-up answers, which makes a visible trail of each decision the only reliable way to catch problems. The approach pairs traces, metrics, and logs with feedback loops so teams fix issues where their AI agents actually run.
Voice AI Systems Are Vulnerable to Hidden Audio Attacks
AI-powered voice and audio tools are becoming increasingly embedded in daily life, from digital assistants to smart speakers and customer service bots. Advances in large audio-language models (LALMs), which can both analyze and generate audio, now make it possible to control devices using voice commands, transcribe meetings automatically, or identify a song playing in the background. These models are also increasingly equipped with the ability to communicate with external services and operate other applications and tools. But these tools can be "hijacked" through imperceptible sounds embedded
Archivists Turn to LLMs to Decipher Handwriting at Scale
When I sat down with bell hooks' personal journals at an archive at Berea College in Kentucky, I expected an intimate peek into her private thoughts, her voice before the editing. What I got instead was frustration. Her handwriting was dense cursive, all loops that looked identical to my eye, and there were years of journals to go through. I found myself photographing pages and feeding them to ChatGPT just to read what she'd written. My tool of choice worked well, and it turns out I'm not the first person in an archive to have figured this out. Getting computers to reliably read human handwrit
Adaptive Parallel Reasoning: The Next Paradigm in Efficient Inference Scaling
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Gradient-based Planning for World Models at Longer Horizons
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Bringing the best of AI search to Copilot
At Copilot Sessions, we reaffirmed our commitment to a human-centered AI strategy focused on making technology work in service of people, not the other way around. At the heart of that vision is trust, and delivering a safe, secure, and relevant search experience is a critical part of that vision. The post Bringing the best of AI search to Copilot appeared first on Microsoft Copilot Blog.
Human-centered AI
Today, we're dropping the Copilot Fall Release, a big step forward in making AI more personal, useful, and human-centered. There's a lot of noise around AI. Headlines, hype, fear. At Microsoft AI, we want to change the outlook. We're betting on optimism in a time of cynicism. The post Human-centered AI appeared first on Microsoft Copilot Blog.
Whole-Body Conditioned Egocentric Video Prediction
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Repurposing Protein Folding Models for Generation with Latent Diffusion
PLAID is a multimodal generative model that simultaneously generates protein 1D sequence and 3D structure, by learning the latent space of protein folding models. The awarding of the 2024 Nobel Prize to AlphaFold2 marks an important moment of recognition for the of AI role in biology. What comes next after protein folding? In PLAID, we develop a method that learns to sample from the latent space of protein folding models to generate new proteins. It can accept compositional function and organism prompts, and can be trained on sequence databases, which are 2-4 orders of magnitude larger than st
Scaling Up Reinforcement Learning for Traffic Smoothing: A 100-AV Highway Deployment
Training Diffusion Models with Reinforcement Learning We deployed 100 reinforcement learning (RL)-controlled cars into rush-hour highway traffic to smooth congestion and reduce fuel consumption for everyone. Our goal is to tackle "stop-and-go" waves, those frustrating slowdowns and speedups that usually have no clear cause but lead to congestion and significant energy waste. To train efficient flow-smoothing controllers, we built fast, data-driven simulations that RL agents interact with, learning to maximize energy efficiency while maintaining throughput and operating safely around human driv