Learn how to run parallel agents in the GitHub Copilot app, and experience the moment it stops feeling scary and starts feeling powerful.

Google is adding AI voice assistant modes to Gmail, Docs, and Keep, called Live experiences, letting users ask questions, create notes, and generate documents conversationally. The features are rolling out in English on mobile.

Nvidia has introduced PAIR (Personal AI Router), free open-source software that discovers idle, compatible PCs on a home network and pools their power for local AI inference and agentic workloads. It supports Nvidia GeForce RTX 20-series and newer, RTX Pro GPUs, DGX Spark systems, and Apple M4 or newer chips. The beta is available today for Windows, Linux, and macOS.

Clockwork is a calendar where AI agents show up for work, giving them a shared schedule to carry out tasks. Listed on Product Hunt, its page currently offers discussion and link entry points.

Discussion | Link

Google has launched WeatherNext 3, an updated AI weather model designed to improve rainfall and snowfall forecasts. Using live satellite observations, it can generate forecasts hourly with up to 5-kilometer resolution for some variables, and Google says precipitation forecasts improve by up to 50 percent at least a day in advance.

More than a billion people are suddenly talking to AI chatbots designed to connect with us. We are sharing with them our deepest secrets, trusting them with our wellbeing and acting on their advice. Across two powerful stories – a woman who was struggling to leave a relationship, and a man who was desperate to quit drinking – the Guardian journalist Michael Safi explores what this new way of living looks like.

In experiments with three small datasets, ChatGPT repeatedly produced plausible but flawed analyses: swapped date columns yielding a 2.6-day average instead of 6.09, uncomputed/inflated figures in prose, ignored missing-data patterns that reversed trends, and a self-review pass that approved wrong conclusions.

Omarchy is presented on Product Hunt as “the malleable OS for the age of agents,” emphasizing an adaptable computing environment that flexes around AI agents and their tasks. The listing is minimal, offering Discussion and Link entry points for further exploration.

OpenAI introduces Daybreak for Frontline Defenders, a $1 billion commitment to expand access to frontier cyber AI, training, and support for essential services.

John Lewis is launching an online chatshow called Gift List, hosted by TV presenter Angela Scanlon, to boost its visibility in AI search results and chatbots. The YouTube vodcast will be promoted through other social media channels, following the success of its sister chain Waitrose's Dish podcast.

GeForce NOW is adding 26 games in September, led by NBA 2K27 with NVIDIA DLSS 5 3D-Guided Neural Rendering. The Blood of Dawnwalker and Onimusha: Way of the Sword also arrive at launch, with Ultimate members able to stream on RTX 5080-class cloud rigs.

Nvidia has agreed to acquire open-source AI platform Hugging Face for $12.93 billion. The platform, often called the 'GitHub of AI,' hosts a vast library of open-source models, datasets, and tools. The deal would give Nvidia a strategic position in the open-source AI ecosystem as it looks to defend its dominance in AI hardware, while open-source developers race to catch up with closed AI systems.

In this article, you will learn the key differences between single-agent and multi-agent AI systems, and how to decide which architecture fits your problem. Topics...

Legora used GPT-6 Astra to review 41 documents in minutes, find all four planted errors, and improve performance by nearly 40% in this financial-review workflow.

NVIDIA has agreed to acquire Hugging Face for $12,930,300,000, planning to scale the platform while keeping it open and multi-cloud. The deal underscores NVIDIA's support for open-weight models and expands its role in the AI ecosystem.

OpenAI introduces GPT-6 Astra, described as its most intelligent and aligned model yet, with state-of-the-art capabilities in computer use, coding, cybersecurity, and science.

Inline is a multiplayer work product that brings AI, teammates, and friends together for collaborative tasks. Its current page is minimal, featuring the tagline, a discussion section, and a link.

Discussion | Link

Omi Desktop is a Mac companion for the open-source Omi AI necklace, letting you ask your Mac questions about things you've seen or heard.

This paper investigates lightweight methods to detect GAN-generated synthetic faces, a common basis for face-centric deepfakes. It compares compact and ImageNet-pretrained Swin Transformer variants with an EfficientNet-B0 + Swin hybrid on the 140K Real and Fake Faces dataset. The hybrid model achieves 99% accuracy and 99.44% recall on 5,000 test images while remaining computationally efficient.

ZipTok3D is a 3D tokenizer designed for high-fidelity reconstruction from extremely short token sequences. It organizes object geometry into progressively informative global-token prefixes, using nested dropout to prioritize essential information in leading tokens, then iteratively decodes each prefix with a parameter-shared Transformer block—no separate generative sampling stage is needed. With the same token dimension, it matches the reconstruction quality of the 32-token COD-VAE baseline using just one token on ShapeNet and four on TRELLIS, achieving 32x and 8x shorter token sequences, respectively.

This survey proposes feedback-driven Test-Time Intelligence (TTI), a unified framework for understanding how AI systems improve during deployment. It relates test-time adaptation, test-time learning, and test-time scaling, surveys both state-modifying and computation-scaling approaches, and reviews applications across vision, language, multimodal learning, generative models, robotics, and healthcare, as well as open challenges.

A new arXiv paper by Marc Bara warns that in multi-agent AI, spawning more agents does not create new evidence. The paper formalizes this as an “epistemic Sybil problem,” proves that text-only aggregators cannot separate replication from independent corroboration, and uses more than 20,000 controlled LLM-agent experiments to show that naive posterior coverage collapses when report multiplicity grows without new evidence roots. A correlated-extraction aggregator restores calibration, and the authors recommend tracking evidential ancestry rather than agent count or report similarity.

This paper introduces Belief-Calibrated Optimization (BCO), a method that writes an agentic optimizer's implicit beliefs into a persistent, continually revised in-context document. This document acts as an explicit world model, and adding it to an otherwise standard optimization loop improves training pass rate over a matched control across five agent benchmarks. The improvement holds on held-out splits and after swapping the frozen target model; an offline ablation confirms the document's content—not just its form—carries reusable predictive information.

An arXiv preprint on persistent-memory agents shows that stale stored facts can override current authoritative evidence without warning. Across a Qwen3 scale series (0.6B–8B), the authors find this 'Memory Trust Gap' reflects over-trust rather than confusion, harms are capability-gated, and effective mitigations differ by model size.

A new benchmark and evaluation framework, FAIRLENS, tests whether vision-language models make fair and valid decisions in hiring, legal, and healthcare contexts. Using over 100,000 image-question pairs per model built from real face images across gender, race, and age groups, the study evaluates eight VLMs through four complementary lenses. The dominant failure, it finds, is unwarranted inference rather than unequal treatment: models infer qualifications, threat, illness, or professional roles from faces instead of abstaining, with the weakest model doing so on 99% of the question-image pairs that do not support an answer. The authors warn that parity metrics alone miss these harms, and that bias in free-text generation is only loosely tied to structured-answer accuracy. Fair high-stakes…

FORGE introduces a forward-only test-time adaptation method for convolutional vision models deployed on microcontrollers in a quantization-friendly, inference-only setting. Because integer deployment fuses batch-normalization layers into convolutions, it destroys the statistics that normalization-based adaptation needs. FORGE restores adaptation by re-normalizing each folded convolution's per-channel outputs to clean training statistics using only forward-pass estimates. It recovers most of TENT's accuracy gain (+20.9 vs +24.9 points), needs just 3 of 21 layers to capture 93% of the benefit, works with single-sample streaming, and costs only 8.3 mJ / 21.9 ms on an ESP32-S3.

Researchers introduce VakyArth, claimed to be the first pragmatic benchmark for Indic languages, covering Hindi, Punjabi, Tamil, and Malayalam. Using multiple-choice questions, natural language inference, and translation to probe five pragmatic phenomena, they find that multilingual LLMs consistently fail on meanings rooted in Indic linguistic and cultural conventions, and that automatic translation metrics can miss fluent but pragmatically unfaithful outputs.

SpeakPay is a voice-first digital wallet that addresses graphical interface accessibility barriers in Nepal's mobile payment ecosystem. The paper introduces NepFinSpeech-403, a 403-utterance Nepali financial voice command dataset spanning send, load, and balance operations with 237 numerals, and applies LoRA-based domain adaptation to Whisper large-v2. This adaptation cuts Word Error Rate from 129.95% to 42.58% (67.2% relative reduction), raises Devanagari numeral accuracy from 0% to 73.9%, and improves Transaction Success Rate from 1.67% to 33.33% — roughly a 20x gain. As few as 100 domain utterances halve zero-shot WER, and performance plateaus around 300.