Search: “smart-glasses”

Researchers Show How Meta's 'Pervert Glasses' Are Used to Harass Women

University of Sydney researchers detail how pickup artists use Meta Ray-Ban smart glasses to covertly film and harass women, then post the videos on Instagram.

Researchers Joanne Gray, Milica Stilinovic, Marcus Carter, and Ben Egliston analyzed 350 Instagram videos posted between September 2023 and March 2026 showing unsolicited approaches to women filmed with smart glasses. They found a clear correlation between covert filming and harassment severity, arguing ambient capture creates 'borderline' harassment that evades platform moderation mechanisms. Instagram head Adam Mosseri said the platform would remove harassing pickup-line content, though similar videos remain widespread a month later. Meta's safeguards, such as the recording light, were previously criticized as insufficient, and users have modded glasses to disable the light.

404 Media·Aug 12, 14:05 UTC · Aug 12, 2026AI safety & security

After accusations of selling ‘perv glasses,’ Meta prepares to sell a pair without a camera

Meta is preparing camera-less Luna smart glasses with microphones and an AI button to access its chatbot and Muse agent, per reports.

The Information reports Meta is developing Luna, a camera-free smart glasses model with six built-in microphones and a side button that activates Meta's AI chatbot and its Muse consumer agent, possibly unveiled at next week's Meta Connect event. The move follows consumer backlash over camera-equipped glasses that critics called 'perv glasses.' Meta's Reality Labs continues to post large losses despite the smart glasses line's relative market success.

TechCrunch · AI·20:12 UTC · 3h agoAI industry

Norway considers ban on camera-enabled wearable ‘pervert glasses’

Norway's government is weighing bans on camera-enabled smart glasses and facial recognition in public to protect privacy.

Norway's digital minister Karianne Tung said the government is considering regulating or banning camera-enabled wearables such as Meta and Snap smart glasses over privacy concerns. Potential measures may include banning facial recognition of other people in public places. The government plans to set up an expert group to advise on better protecting privacy rights amid a trend of combining AI with cameras and microphones in everyday devices.

TechCrunch · Security·Sep 2, 13:11 UTC · 14d agoPolicy & legal

Meta Patents AI Glasses to Use Facial Recognition to Identify People, Make Highlight Reels of Your Dinner Party

Meta filed a patent for AI glasses that identify people via facial recognition and auto-generate highlight reels of events like dinner parties.

A newly published Meta patent describes smartglasses that use facial recognition to detect people in frame, capture video clips of their actions, and compile highlight reels. The filing signals Meta's continued, controversial push to combine facial recognition with its AI glasses line. The patent was published Thursday and offers granular detail on Meta's product plans, though it does not confirm a shipping feature.

404 Media·Aug 14, 14:17 UTC · Aug 14, 2026AI industry

Canadian Start-up smartARM Uses AI to Create Intuitive Bionic Prosthetics

Toronto startup smartARM built a bionic prosthetic arm using Meta's DINOv2 vision model and AI glasses to automatically select grips for objects.

Toronto-based smartARM developed a vision-first bionic arm that uses a palm-embedded camera and Meta's open-source DINOv2 model to recognize objects from a few reference photos and automatically select suitable grips. It integrates Meta AI Glasses and the Meta Wearables Device Access Toolkit for additional egocentric context, letting users add new objects via a phone app. The arm adapts to new objects almost instantly instead of the weeks previously required, and is used by former NFL player Shaquem Griffin.

Meta Newsroom·updated 16:39 UTC · 7h ago·first 16:00 UTC · 7h agoAI industry 2 sources

Snap is launching a new Specs AI tool, and it’s coming to iOS and Macnew

Snap launches Specs Intelligence, an anticipatory AI assistant on iOS in preview with Mac early access, alongside its Specs AR glasses.

Snap introduced Specs Intelligence, an AI assistant that connects accounts like Gmail and Slack to proactively surface tasks such as meeting prep and travel planning. It is available on iOS in preview today, with a waitlisted Mac early-access experience, launching alongside Snap's first consumer AR glasses, Specs. Snap says it runs a proprietary mix of open-source models hosted in the US alongside local LLMs, and claims connected personal content will not train its models or serve personalized ads. The company must still win user trust given the assistant's broad access to personal data.

The Verge · AI·23:40 UTC · 15m agoAI industry

OpenAI buys smartphone camera maker Glass Imaging for $300 million, report says

OpenAI acquired smartphone camera startup Glass Imaging for over $300 million, deepening rumored hardware ambitions after its $6.5 billion io deal.

OpenAI bought Glass Imaging, a Los Altos startup founded in 2019 by former Apple engineers Ziv Attar and Tom Bishop who led Apple's Portrait Mode team, per a Wall Street Journal report. Glass Imaging had raised about $30 million and uses neural networks that learn individual camera systems to improve image quality at capture time. The acquisition fuels speculation about OpenAI hardware plans including smartphones, earbuds, and AI companion devices, following its $6.5 billion purchase of Jony Ive's io startup in 2025.

TechCrunch · AI·Sep 14, 20:44 UTC · 2d agoAI industry

Meta makes AI glasses slightly less creepy with limit on nonconsensual recording

Meta updated its AI glasses to stop recording whenever users cover the safety light, addressing nonconsensual-recording complaints while broader privacy risks remain.

Meta released a change to its AI glasses that halts recording whenever users physically cover the device's safety light, closing a loophole that allowed nonconsensual capture. The tweak follows criticism that bystanders could be recorded without consent. Ars Technica notes the fix reduces but does not eliminate the privacy risks posed by AI-enabled eyewear.

Ars Technica · AI·Aug 28, 15:42 UTC · 19d agoAI industry

Stopping the smart TV from being used against you

Guide describes practical hardening steps to prevent smart TVs from spying on their owners or being used against them.

A tutorial-style post walks through defensive measures to keep a smart TV from collecting user data or being leveraged against its owner. The piece is a consumer IoT privacy and hardening guide rather than a disclosure of a specific vulnerability.

Lobsters · security·Aug 28, 19:32 UTC · 19d agoResearch

LG smart TVs caught logging audio with screen off and snooping on local devices

Gamers Nexus found LG smart TVs record microphone audio in standby, scan home networks, and feed LG Ad Solutions ad targeting.

A 135-minute Gamers Nexus investigation with Level1Techs and independent researchers found retail LG OLED TVs running webOS sweep local networks, gather device names and Wi-Fi metadata, and run Automated Content Recognition. Tests showed the TVs capture clean microphone audio while appearing powered down and store it offline, uploading once reconnected. The team also found RCE vulnerabilities in webOS now moving through responsible disclosure; LG claims 216 million smart TV sales, and its ad unit claims access to 363 million addressable devices in the US.

Hacker News · security·Sep 7, 07:03 UTC · 9d agoResearchHN 1151↑ · 3 comments

Mozilla's new Smart Window assistant runs on Mistral's models

Mozilla's Firefox Smart Window beta AI browsing assistant, powered by Mistral's models, launches in France and North America with no conversation storage.

Mozilla and Mistral partnered to power the Firefox Smart Window beta, an AI browsing assistant for complex searches, content recall, and tab summarization. The feature is available first in France and North America, with the UK and Germany to follow later this year. Mistral commits to storing no conversation data, and chats are not kept on Mozilla's servers by default.

The Decoder·15:01 UTC · 8h agoAI industry 2 sources1

The Roboguard Revolution is Short

404 Media·Aug 10, 13:04 UTC · Aug 10, 2026Industry

SlipSense: Multimodal Tactile Learning for Low-Latency and Generalized Slip Detection

SlipSense fuses a 32x32 piezoresistive array and MEMS accelerometer to detect robotic grip slips within 23.1 ms, generalizing zero-shot across platforms.

SlipSense is a multimodal tactile slip-detection framework built on TacV5, a sensor combining a 32x32 piezoresistive array at 240 Hz and a 3-axis MEMS accelerometer at 8 kHz. It performs modality-specific encoding, intra-sensor fusion, and cross-modal attention with causal temporal prediction at 240 Hz. On a 1.4-million-frame dataset spanning 37 objects it achieves 96.7% Macro F1 with a false-positive rate below 1.6%, detecting 76% of slip events within 23.1 ms. Trained solely on UMI data, it transfers zero-shot to a Tesollo dexterous hand across unseen objects, sensor units, and platforms.

arXiv cs.AI / cs.LG / cs.CL·Sep 14, 17:23 UTC · 2d agoAI research

SenseNova-U1.5: Towards Native Unified Visual Intelligence

SenseTime releases SenseNova-U1.5, an 8B-MoT encoder-free multimodal model unifying visual understanding, reasoning, and generation with native 4K resolution.

SenseNova-U1.5 is an 8B mixture-of-transformers multimodal model with an encoder-free, VAE-free architecture that understands, reasons about, and generates visual content at native resolutions up to 4K. Post-training optimizes specialized experts for visual aesthetics, bilingual text rendering, infographic generation, and image editing, consolidated through multi-expert on-policy distillation. Evaluations report gains in image fidelity, text rendering, multi-reference editing, and instruction following. The team plans to open-source training code including supervised fine-tuning, reinforcement learning, and on-policy distillation.

Hugging Face daily papers·Sep 9, 20:00 UTC · 7d agoModel release

Fashion app Daydream uses Apple Intelligence to help you shop the outfits in your camera roll

Fashion app Daydream uses iOS 27 Apple Intelligence APIs to turn saved outfit photos into shoppable matches and enable Siri voice search.

Daydream launched photo-based outfit shopping and Siri natural-language search built on Apple's iOS 27 developer tools, matching images against roughly 3 million products from 325+ retailers and 10,000 brands. The app claims over 1.5 million shoppers and frames the features as steps toward a cross-surface shopping agent. Competitors include Google, Amazon, Onton, and Alta.

TechCrunch · AI·Sep 14, 17:00 UTC · 2d agoAI industry

The hinge for Apple’s new foldable phone was built with AI

Apple's first foldable phone, the Duo, uses AI algorithms and 3D printing to manufacture its precision-matched hinge and durability coatings.

Apple introduced its first foldable phone, the Duo, at its Surprise and Shine event on September 9. Chief hardware officer Johny Srouji said AI algorithms match each hinge with its best-fit housing, while confocal laser scans guide 3D printing of up to 25 micro layers of custom photopolymer to eliminate residual waviness. The device also features a nano-texture anti-glare finish and multi-layer lamination aimed at improving foldable durability.

TechCrunch · AI·Sep 9, 19:21 UTC · 7d agoAI industry

SAFIRE: Safety-Critical Benchmark for Fine-grained Fire and Smoke Understanding in Multimodal LLMs

SAFIRE, an 83K-image fire and smoke benchmark, shows open-source multimodal LLMs average only 61.9% accuracy on safety-critical fire reasoning.

SAFIRE is a large-scale benchmark for fire-smoke understanding in multimodal LLMs with 83K captioned images across 20 scenarios and 193K multiple-choice VQA questions spanning 10 evaluation dimensions from perception to higher-order reasoning. Annotations were built via a GPT-5.4-assisted multi-stage pipeline with MLLM majority voting. Ten open-source MLLMs (8B-38B) average 61.9% accuracy, exposing major gaps in safety-critical reasoning. Adapting vision encoders on 7% of the domain data raises fire-scene classification from 20.1% to 64.5%.

arXiv cs.AI / cs.LG / cs.CL·Sep 7, 17:59 UTC · 9d agoAI research

Jalapeño’s first results show industry-leading speed and efficiency in AI inference

OpenAI's Jalapeño custom inference chip shows faster, more power-efficient inference with higher throughput and lower latency.

OpenAI announced first results for Jalapeño, its custom AI inference chip. The company claims industry-leading speed and efficiency, delivering higher throughput and lower latency for modern models compared with existing options. The chip targets more power-efficient serving of large models at scale.

OpenAI News·Aug 25, 07:00 UTC · 22d agoAI industry

Design Docs Are All You Need: An AI-native Machine-Learning Performance Tool

Researchers present SMART, an ML performance-modeling library regenerated by AI coding agents from natural-language design docs instead of code.

The paper describes SMART, a symbolic performance-modeling library whose main branch contains almost no code: the repository is a DAG of self-contained design documents, and coding sub-agents regenerate implementations from only the docs on version updates. Reliability rests on a worked-example doc style used as in-context demonstrations and a minimal operator IR with SymPy cost expressions, offering both fast analytical roll-up and fine-grained modulo-scheduling modes. Regenerated implementations reproduce hand-audited reference models, including DeepSeek-V3 serving on a TPU pod slice, to round-off precision.

arXiv cs.AI / cs.LG / cs.CL·Sep 4, 17:08 UTC · 12d agoAI research1

Researchers built a $7 gadget for anyone paranoid about hidden cameras in hotel rooms

KAIST-led researchers built SweepLED, a sub-$7 smartphone LED clip using AI to detect hidden cameras with 93.9-95.1% accuracy.

SweepLED, built by KAIST with the National University of Singapore and Singapore Management University, clips 15 LEDs to a smartphone camera and sweeps multi-angle light while the phone films reflections. A spatio-temporal AI model compares LED-on and LED-off frames to distinguish lens reflections from glossy surfaces across three viewpoints. Testing on 30 objects, 12 with hidden cameras, achieved 93.9% accuracy handheld and 95.1% static. Core components cost under $7, targeting privacy checks in hotels and short-term rentals.

Help Net Security·Sep 3, 00:00 UTC · 13d agoResearch1

CARDEA: Auditable Reasoning Grounded in Spatial Evidence for End-to-End Coronary Angiography Interpretation

CARDEA, a vision-language model trained only on public data, matches cardiologists on coronary angiography complexity assessment while exposing auditable bounding-box evidence.

CARDEA is a unified large vision-language model serving as the inference core of an end-to-end coronary angiography pipeline from multi-view videos to study-level diagnosis. It was trained on public datasets through visual alignment, self-distilled Chain-of-Box cold start, and reinforcement learning with verifiable rewards encouraging bounding-box reasoning. It reached 0.91 accuracy on dominance classification under domain shift and 0.90 on complexity assessment, comparable to two interventional cardiologists. RLVR raised zero-shot report generation vessel-severity macro-F1 from 0.513 to 0.686, while supervised imitation alone did not.

Hugging Face daily papers·Sep 6, 20:00 UTC · 10d agoAI research

Watch out: Apple timepiece can grab snippets of conversation without both speakers' consent

Apple's Watch Series 12 Live Rewind and Siri Recap transcribe nearby conversations without bystander consent, drawing EFF criticism over all-party-consent laws.

Apple Watch Series 12's Audio Intelligence features on the S11 chip include Live Rewind, which transcribes the last 15 seconds of a conversation after a Digital Crown double-press, processing audio in a Secure Exclave and routing it to a nearby iPhone. Siri Recap generates AI summaries of daily conversations without retaining raw audio or attributing speakers. Apple says an audible chime and visual cue alert bystanders, but privacy advocates including the EFF note that 11 US states require all-party consent for recording and that bystanders have no practical way to opt in or decline.

The Register · Security·Sep 10, 19:50 UTC · 6d agoAI safety & security

DeCAL: Towards Physically-Grounded Dexterous Vision-Language-Action Models via Contact-Aware Latent Co-Imagination

DeCAL, a contact-aware dexterous vision-language-action model with visuo-tactile fusion, reports 71% average task success.

DeCAL is a physically-grounded dexterous vision-language-action (VLA) model built on a Mixture-of-Transformers architecture with specialized experts for understanding, imagination, and action generation. It introduces Adaptive Visuo-Tactile Fusion with contact-aware gating and Visuo-Tactile Latent Co-Imagination to jointly model visual and tactile dynamics. It reports state-of-the-art results with a 71% average success rate and 83.4% progress success rate, plus generalization to unseen scenarios.

arXiv cs.AI / cs.LG / cs.CL·Sep 8, 17:47 UTC · 8d agoAI research1

The AI policy window is open. We need to act.

OpenAI calls for mandatory national AI safety regulation and backs four California AI safety bills as capabilities accelerate.

OpenAI argues the rapid pace of AI progress, including signs of AI-accelerated research, requires urgent policy action through mandatory, capability-based national regulation. The company endorses four California bills (SB 813, AB 1405, SB 1119, AB 1864) covering independent safety assessments, AI auditor standards, youth protections, and safeguards against AI-enabled biological threats. It also commits to industry-led frontier standards, international coordination, and strengthening internal safeguards such as universal trajectory monitoring and mandatory alignment-evaluation gates for its Astra model. The post references chief scientist Jakub Pachocki's warning about recursive self-improvement and Greg Brockman's "defenders window" concept.

OpenAI News·Sep 9, 13:00 UTC · 7d agoAI policy

Knowing What Not to Answer: Selective Non-Compliance in Vision-Language Models

Researchers introduce KoNA, a benchmark exposing vision-language models' failures at selective non-compliance, plus fine-tuning that improves refusal and abstention accuracy.

KoNA is a benchmark for evaluating selective non-compliance in vision-language models across five categories: False Premise, Visual Inaccessibility, Universal Unknown, Task Feasibility and Safety. It tests both query-level and component-level non-compliance using paired single and compound queries, and evaluations across diverse VLMs show models often fail to refuse, correct or abstain appropriately, with failures worsening on compound queries. Fine-tuning VLMs on KoNA examples substantially improves non-compliance accuracy while largely maintaining performance on fully answerable tasks.

Hugging Face daily papers·Sep 3, 20:00 UTC · 13d agoAI research1

[AINews] DeepSeek v4.1-Flash: 763B-P8B-D16B novel causal Encoder–Decoder architecture with vision marks the Return of the Whale

DeepSeek released V4.1-Flash, an open-weight 763B-parameter model with a novel causal encoder-decoder architecture, 1M context, vision input, and MIT license.

DeepSeek launched V4.1-Flash, an open-weight MIT-licensed model using a novel causal encoder-decoder architecture with 763B total parameters and asymmetric active parameters: 8B for prefill and 16B for decode. It supports 1M-token context and text+image input, priced at $0.30 per 1M input and $1.20 per 1M output tokens with a 50% off-peak discount. Artificial Analysis scored it 40 on its Intelligence Index, above DeepSeek V4 Pro 0813, and Vals ranked it the #1 open-weight model ahead of Kimi K3. Baseten shipped day-0 support and Ollama began rolling it out to paid subscribers.

Latent Space·Sep 12, 05:56 UTC · 4d agoModel release 4 sources1

Reward AI Releases OM-1: A Robot Policy Trained on Human Demonstrations Only, With No Teleoperation or On-Robot Data

Reward AI released OM-1, a general-purpose manipulation policy trained solely on human demonstrations from a sensorized glove, with no teleoperation or robot data.

Reward AI announced OM-1 (Omnibody Model 1), a general-purpose robot manipulation policy trained only on human demonstrations captured via Omnibody Hand, a 7-DoF wearable glove with tactile, proximity, and in-hand camera sensing. The system uses electromagnetic hand-pose tracking, cutting mean overshoot error to 9.5 mm versus 24.9 mm for visual-inertial at 67 cm/s (a 60% reduction), and reportedly learns brand-new tasks from under 30 minutes of human data. A separate RL-trained control layer runs on its own clock so policy inference latency never stalls motion, and the policy spans industrial arms, legged humanoids, and wheeled mobile manipulators. No weights, code, dataset, API, paper, or benchmark comparisons have been released, so claims are demonstration-backed only.

MarkTechPost·Sep 14, 21:08 UTC · 2d agoAI research

LG TV flaws could let attackers listen in, even in standby mode

Researchers found LG smart TVs collect network data and ACR viewing profiles, and demonstrated microphone audio capture plus undisclosed RCE vulnerabilities.

An investigation by Gamers Nexus with Level1Techs and independent researchers found LG TVs performing network discovery, collecting nearby Wi-Fi names and device identifiers, and conducting Automated Content Recognition (ACR) tracking. They demonstrated microphone audio capture even when the TV appeared off, and audio buffering while the TV was unplugged from the internet. Remote-code-execution vulnerabilities were reported to LG under ongoing responsible disclosure, with full details not yet public.

Malwarebytes Labs·Sep 7, 13:34 UTC · 9d agoVulnerability

Apple Watch’s new AI features are normalizing the idea that technology is always listening

TechCrunch argues Apple Watch's Live Rewind and Siri Recap normalize always-listening AI, raising consent and legal questions despite privacy safeguards.

Analysis of Apple's new Apple Watch AI features contends that Live Rewind, which transcribes the previous 15 seconds of audio, and Siri Recap, which generates high-level conversation notes, are pushing consumers toward accepting always-listening technology. The piece acknowledges the accessibility value of on-device Audio Intelligence, which alerts deaf or hard-of-hearing users to sounds like sirens, alarms, doorbells, and crying babies. It also raises concerns about consent, the evidentiary status of text-only transcripts in court, and cultural effects of pervasive capture, noting competitors like Friend, Amazon's Bee, and Plaud in the AI transcription space.

TechCrunch · AI·Sep 9, 20:24 UTC · 7d agoAI industry

OpenAI supports California’s bill to advance youth AI safety

OpenAI announces support for California SB 1119, a bill mandating age-appropriate AI safeguards for teenage users.

OpenAI publicly endorsed California Senate Bill 1119, which seeks strong, age-appropriate AI safeguards for teens. The company framed its support as advancing youth safety while preserving opportunities for teens to learn, create, and explore with AI tools.

OpenAI News·Aug 31, 07:00 UTC · 16d agoAI policy