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Threads has a VR app now

Meta has launched a Threads app for Meta Quest VR headsets, the company announced on Tuesday. The launch follows Meta bringing the app to its Ray-Ban Display AR glasses last month and the recent news that the platform has crossed 500 million monthly active users. It seems like a pretty full-featured app. Meta says that […]

2026-08-12 原文 →
AI 资讯

‘Zoomsday’ hack uncovered using fewer than 20 AI prompts

Zoom has patched a major security vulnerability that could allow an attacker to hijack anyone's device during a meeting. In a blog post on Tuesday, researchers at A Security say they uncovered the flaw using "fewer than 20 prompts on publicly available AI models," as reported earlier by Wired. The exploit involved Zoom's annotation feature, […]

2026-08-11 原文 →
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Bumble now lets men make the first move

Bumble was famously built around exclusively giving women the power to initiate messages in heterosexual matches when it first launched in 2014 - but now the times they are a-changin' for the dating app. Today, Bumble has announced a "global evolution to its signature conversation experience": anyone can now send the first message, and the […]

2026-08-11 原文 →
AI 资讯

The AI takeover of mathematics has begun

Mathematician James Maynard has spent a lot of time this past year "soul searching." A professor at the University of Oxford and winner of the prestigious Fields Medal, Maynard told The Verge he's been grappling with the future of his field as the traditionally slow-moving discipline hurries to adapt to AI. Days before we spoke, […]

2026-08-11 原文 →
AI 资讯

How I Built a Self-Hosted Family AI Health Steward (Your Health Data, on Your Shelf)

TL;DR — I built and open-sourced AI Health Steward , a self-hosted, private AI health manager for families. It reads photos of lab reports with multimodal LLMs, builds a structured per-person health profile, shows trends on a dashboard, and answers health questions grounded in your actual data — all running on your own server. Privacy isn't a feature; it's the whole point. Star it on GitHub . The problem: your health data is a product Every family has a shoebox — or a folder — of medical reports: blood tests, blood-pressure logs, prescriptions, scan findings. And every "convenient" health app wants to hold those records for you. But hold them where ? On someone else's cloud, to be monetized, analyzed, or lost when the startup pivots. Health records are the most sensitive data you own. They shouldn't be a product. They should live on your shelf. So I built the opposite: a self-hosted AI health steward where the data never leaves your server. What it does 📄 Take a photo of a lab report → structured data. A multimodal LLM extracts key metrics (BP, glucose, lipids, CBC…) with your confirmation before anything is filed. 🧬 A person-level health profile as the single source of truth — basics, metrics, diagnoses, medications, allergies, lifestyle, family history, and data provenance (where each value came from). 📈 Trend visualization with anomaly markers and clinical critical-value alerts (e.g. BP ≥ 180/110 triggers a "see a doctor" banner). 💬 AI consultation grounded in real data — not a generic chatbot. Intent routing + function calling means answers reflect your profile, not Wikipedia. 🗓️ Personalized checkup plans via a 1+X+Y framework, with budget tiers and safety/contraindication screening. 📋 Periodic health summaries (weekly/monthly/yearly), risk scales (PHQ-9, GAD-7, diabetes, ASCVD), and follow-up/medication reminders . 🧠 RAG over your own history — archived reports are vectorized so you can ask "what did my A1C trend look like over 3 years?" The architecture ┌────

2026-08-11 原文 →
AI 资讯

Tennis Players Can Now Improve Strokes Without Coaches Using AI-Powered Feedback Technology

Introduction Tennis players often find themselves in a feedback vacuum. Without a coach physically present, pinpointing what’s wrong with a stroke becomes a guessing game. This gap in immediate, stroke-specific guidance is a silent killer of progress, leaving players to rely on sporadic coaching sessions or self-diagnosis, which often misses the mark. The problem isn’t just about lack of access to coaches—it’s about the inability to see and correct subtle technique flaws in real time. Enter Rallylens , a web app born out of personal frustration. As a student and tennis player, I built this tool to address the disconnect between practice and feedback. It uses video analysis powered by AI to break down uploaded tennis videos frame by frame, identify stroke types (forehand, backhand, serve), and compare them against ideal technique benchmarks. The system doesn’t just flag errors—it explains them. For instance, if a backhand stroke shows an inconsistent racket angle, the feedback highlights this deviation and suggests adjustments, focusing on mechanics like wrist rotation or body alignment. The Mechanism Behind the Feedback Rallylens operates through a multi-step process that mimics a coach’s eye but with the precision of machine learning: Video Segmentation: Uploaded videos are split into frames, allowing the AI to analyze micro-movements that might be invisible to the naked eye. Stroke Classification: Using computer vision techniques , the model identifies the stroke type with an accuracy rate currently at 85%, though unusual playing styles can still cause misclassification. Pattern Analysis: The algorithm compares detected patterns against biomechanical benchmarks , flagging deviations like improper weight transfer or late racket contact. Feedback Generation: Instead of generic advice, the system generates actionable insights , such as “Adjust your shoulder tilt by 10 degrees to optimize power transfer.” Edge Cases and Limitations While Rallylens bridges a critical g

2026-08-11 原文 →
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YouTube is making it harder to earn money on YouTube

Starting February 1st, 2027, creators who want to monetize their channel through YouTube's Partner Program (YPP) will need at least 1,000 subscribers and either 8,000 qualified watch hours over the past year, or 20 million qualified Shorts views in the last 90 days. That's a sizeable jump from YouTube's current requirement of 1,000 subscribers with […]

2026-08-11 原文 →