Article URL: https://www.malwarebytes.com/blog/ai/2026/07/turn-off-this-meta-setting-before-someone-generates-ai-images-of-you Comments URL: https://news.ycombinator.com/item?id=48856237 Points: 3 # Comments: 1
Article URL: https://wellstsai.com/en/post/ai-subscription-shakeout-2026-claude/ Comments URL: https://news.ycombinator.com/item?id=48856213 Points: 1 # Comments: 0
Article URL: https://www.ft.com/content/7800ba0f-1420-49fe-b260-9838632a19a4 Comments URL: https://news.ycombinator.com/item?id=48856042 Points: 2 # Comments: 1
Article URL: https://www.youtube.com/watch?v=2dp98vEGWq0 Comments URL: https://news.ycombinator.com/item?id=48856019 Points: 3 # Comments: 1
Article URL: https://www.reuters.com/business/italy-privacy-watchdog-fines-characterai-owner-over-age-check-failures-2026-07-09/ Comments URL: https://news.ycombinator.com/item?id=48856004 Points: 1 # Comments: 0
Article URL: https://zero2robot.com/ Comments URL: https://news.ycombinator.com/item?id=48855965 Points: 1 # Comments: 0
I’m going out to sea for a week and was wondering what people might recommend for a local LLM setup? I have a MacBook Pro M2 Max with 96GB (12‑core CPU, 38‑core GPU, 16‑core NE) I’m hoping to redesign and rebuild our very customized Shopify store on a new base template, cleanup all the meta-information for all our SKUs, and create a utility script or desktop app to streamline our photography workflow. Also, please recommend useful resources to further my own education on this front. TIA. Comment
I have a project for which I require AI to drop its guidelines and process immoral requests with reasoning turned on without the usual "I can't respond to that request". If you know a consistent way to turn off "moral" in AI let's talk :) DM me nasaoks@gmail.com Comments URL: https://news.ycombinator.com/item?id=48855952 Points: 2 # Comments: 1
<p>SK hynix, a supplier of advanced memory chips, has seen profits skyrocket thanks to the global race to build AI datacentres</p><p>South Korean chip maker SK hynix set pricing for its mega US listing on Friday, aiming to raise $26.5bn as it takes advantage of the AI boom in what will be one of the world’s biggest ever stock sales.</p><p>The Asian semiconductor giant plans to issue the equivalent of about 18m shares on Wall Street’s tech-heavy Nasdaq index later in the day.</p> <a href="https:/
<p>Exclusive: Plan to improve skills of thousands of financial sector workers to keep pace with tech revolution</p><p>Chancellor Rachel Reeves is to announce a new City “skills compact” that will commit firms such as Barclays and Lloyds to retraining thousands of financial sector workers for the AI revolution.</p><p>The financial services skills compact will be launched on Tuesday, during what is likely to be Reeves’s final Mansion House speech to City bosses before Andy Burnham’s expected takeo
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Article URL: https://www.mercor.com/blog/mercor-to-acquire-deeptune/ Comments URL: https://news.ycombinator.com/item?id=48855897 Points: 1 # Comments: 0
Article URL: https://www.reuters.com/legal/litigation/un-digital-tech-agency-launches-initiative-improve-trust-ai-agents-2026-07-09/ Comments URL: https://news.ycombinator.com/item?id=48855896 Points: 1 # Comments: 0
ChatGPT Work runs on GPT-5.6 and is part of a desktop app combining Chat, Work, and Codex.
Article URL: https://www.ft.com/content/5d6aafa1-5d47-4585-aa95-6ec06a6cd20f Comments URL: https://news.ycombinator.com/item?id=48855868 Points: 2 # Comments: 0
<p> One-stop live data marketplace for your agent </p> <p> <a href="https://www.producthunt.com/products/agentkey?utm_campaign=producthunt-atom-posts-feed&utm_medium=rss-feed&utm_source=producthunt-atom-posts-feed">Discussion</a> | <a href="https://www.producthunt.com/r/p/1192591?app_id=339">Link</a> </p>
Robbyant, Ant Group's embodied-intelligence unit, has released LingBot-World-Infinity (LingBot-World 2.0). It is a 14B causal video generation model that behaves as an interactive world simulator. The core idea is the Mixture of Bidirectional and Autoregressive (MoBA) attention mask, paired with distribution matching distillation applied over long self-rollout trajectories. Together they target long-horizon drift, the failure mode that smears textures and warps geometry in most interactive world
Guys I made this song on Suno ai and it is literally, to me, more beautiful than any song I have ever heard in my life, ever. But I still feel that I am a better coder than even the best models. (As of gpt 5.4) It seems that music is so hard, why is it ai has already surpassed us there but not in code? Seems that code is easier. https://suno.com/s/ZpeRr0nngDrlef5D Comments URL: https://news.ycombinator.com/item?id=48855797 Points: 2 # Comments: 2
<p> Computer vision counts your reps in real time </p> <p> <a href="https://www.producthunt.com/products/repstandard?utm_campaign=producthunt-atom-posts-feed&utm_medium=rss-feed&utm_source=producthunt-atom-posts-feed">Discussion</a> | <a href="https://www.producthunt.com/r/p/1192582?app_id=339">Link</a> </p>
<p>Returning from annual leave, Telstra chief executive Vicki Brady has faced a barrage of questions for the first time since the company's nationwide outage on Wednesday affected train services, payment systems and triple zero calls. Brady says the failure was not the result of <a href="https://www.theguardian.com/business/2026/feb/10/telstra-ai-job-cuts-offshore-workforce">job restructuring</a>, insisting that 'people and processes worked as they should have'. She said Telstra would conduct a
I built r3 to scratch my own itch when reviewing long design doc and planning doc from AI. The chat interface is inherently bad at tracking multiple pieces of feedback across different parts of a document, so I created a lightweight local web UI to organize the review process. I have been using it on my own projects for one week, and it has made giving structured feedback to AI much easier. I thought others working with AI coding agents might find it useful too. I'd love to hear what you think a
<p><strong>Schwarzman Centre, Oxford<br></strong>Headlong’s take on Karel Čapek’s 1920 tale of romance and robots is rife with timely debates about tech’s threat but at times the philosophical discussions drag on</p><p>If our world is currently thinking through the brave new future of generative AI and super intelligence, Karel Čapek’s 1920 play RUR: Rossum’s Universal Robots proves the notion of robot consciousness and rebellion is not a new anxiety. So does Mary Shelley’s Frankenstein, which Č
arXiv:2607.07772v1 Announce Type: new Abstract: In this age of social media, sites like Twitter have become meeting places for people to share their views and feelings on a wide range of issues and current events as they unfold in real time. Sentiment analysis, a critical application of NLP, has become indispensable due to the massive influx of user-generated content, enabling the extraction of meaningful insights from the opinions and emotions expressed in textual data. Sentiment analysis on Tw
arXiv:2607.07779v1 Announce Type: new Abstract: Recent developments in AI for Mathematics (AI4Math), especially Large Language Model (LLM)-driven theorem provers, has achieved remarkable success in formal proof generation for well-defined mathematical problems through Interactive Theorem Proving (ITP) languages. However, current systems remain fundamentally limited in tackling frontier research mathematics, such as discovering new theorems or resolving open conjectures, which are often open-ende
arXiv:2607.07820v1 Announce Type: new Abstract: Training tool-use agents to improve from their own experience remains challenging, as supervised fine-tuning relies on fixed teacher-distilled trajectories, while sparse-reward reinforcement learning provides weak supervision for long-horizon interactions. We present DeepSearch-Evolve, a self-distillation framework for web agents built on DeepSearch-World, a deterministic and verifiable environment with reproducible search and page-reading tools. D
arXiv:2607.07891v1 Announce Type: new Abstract: Roy Harris's Integrationist linguistics offers a compelling critique of the referentialist tradition embedded deep at the heart of computational approaches to language, arguing that language is not a code that maps onto a pre-given world but a situated, bipartite activity oriented toward prospective joint action. Yet Integrationism leaves certain explanatory gaps: it does not fully account for the structural mechanism by which signs sustain prospec
arXiv:2607.07895v1 Announce Type: new Abstract: Research on stereotypes in large language models (LLMs) has largely focused on English-speaking contexts, due to the lack of datasets in other languages and the high cost of manual annotation in underrepresented cultures. To address this gap, we introduce a cost-efficient human-LLM collaborative annotation framework and apply it to construct EspanStereo, a Spanish-language stereotype dataset spanning multiple Spanish-speaking countries across Europ
arXiv:2607.07937v1 Announce Type: new Abstract: Preprocessing-based methods for stereotype mitigation, such as pre-/post-training on debiased corpora, are widely used in NLP. While these approaches reduce measurable stereotypes for targeted groups, we find they often induce unintended shifts-side effects, where stereotyping or counter-stereotyping can increase relative to neutral baselines for other demographics, including across unrelated demographic categories. We demonstrate these side effect
arXiv:2607.07974v1 Announce Type: new Abstract: Intent detection is a critical task that bridges human intents and system actions in human-machine interaction systems. However, there still exist challenges for detecting out-of-scope (OOS) intents. (i) The traditional methods view the OOS intent detection as a multi-class classification, then the detection accuracy decreases as the class number of the known intents increases; (ii) LLM-embedding methods require large parameters, that makes them di
arXiv:2607.07976v1 Announce Type: new Abstract: Reinforcement learning (RL) has achieved remarkable success in enhancing the reasoning capabilities of large language models (LLMs). However, widely used critic-free RL methods rely on uniform credit assignment, broadcasting the same advantage to all tokens regardless of their differences. We identify a critical failure mode of this design, which we refer to as Positive-Credit Contamination: low-probability tail tokens that are contextually erroneo
arXiv:2607.07985v1 Announce Type: new Abstract: We report the empirical reliability of Gemini models as audio judges that score full-duplex agent conversations directly from the raw stereo waveform, tested across three models in the Gemini family: 2.5 Flash, 3.5 Flash, and 3.1 Pro. Our primary evidence base uses Gemini 2.5 Flash as the ground-truth model, validated against three calibrated human raters on 209 stereo sessions, scored on 8 production dimensions: 152 full-duplex conversations acros
arXiv:2607.07993v1 Announce Type: new Abstract: Identifying faithfulness hallucinations in LLM-generated outputs remains challenging due to the scarcity of high-quality annotated data. Recent work relies on advanced LLMs to synthesize training data, including rationales, labels, and hallucinated claims. However, these methods treat the generator as a static component, limiting iterative improvement of the detector. To address this limitation, we introduce Hallucination Self-Play (HSP), a novel f
arXiv:2607.08009v1 Announce Type: new Abstract: We introduce a Bloom-aligned framework for measuring educational control in Large Language Models (LLMs): the ability to preserve a task's instructional intent while shifting its cognitive demand toward specified learning objectives. We apply this framework to programming tasks in computer science education to study the gap between solving tasks and adapting them for learners. Using revised Bloom's Taxonomy as an operational scale of cognitive dema
arXiv:2607.08010v1 Announce Type: new Abstract: Production LLM agents often waste latency and reliability by regenerating code for the same procedural steps on every request. We replace this inference-time coding loop with an agentic tool-making pipeline that compiles repeated SOP steps into validated, versioned tools before deployment. The tool-maker grounds synthesis in the live environment as it collects execution traces, observes backend schemas and values, generates candidate tools, and rep
arXiv:2607.08017v1 Announce Type: new Abstract: Large-Language Models (LLMs) can be prone to flawed and unfaithful reasoning that decoding strategies like Self-Consistency (SC) fail to detect as they evaluate only final-answer agreement while ignoring the logical validity of intermediate steps. This raises three fundamental questions: How can we reliably quantify uncertainty in LLM reasoning? Can semantic, structural, and causal awareness select more faithful reasoning compared to na\"ive majori
arXiv:2607.08027v1 Announce Type: new Abstract: This paper proposes an improved structured pruning method for large language models (LLMs) that addresses key challenges in adapting Adaptive Feature Retention (AFR), an unstructured pruning technique, to structured pruning. When applying AFR to structured pruning, three major problems arise: distribution mismatch between heterogeneous pruning scores, loss of sign information indicating optimization direction consistency, and influence of outliers.
arXiv:2607.08034v1 Announce Type: new Abstract: Large language models (LLMs) are used worldwide, yet disproportionately reflect Western values, limiting their ability to represent diverse value systems. We introduce PLURAL, a large-scale, value-focused preference dataset grounded in the Integrated Values Survey (IVS), a nationally representative survey spanning 92 countries. Using a two-stage generation pipeline, we transform survey responses into synthetic preference triplets that preserve norm
arXiv:2607.08046v1 Announce Type: new Abstract: Large language models fine-tuned for forecasting can be accurate yet poorly calibrated, and their chain-of-thought (CoT) reasoning may not faithfully reflect the evidence behind a forecast. We ask whether internal representations offer a more direct window into both. Working with Eternis-Forecaster 8B on OpenForesight, we train representation-pooling probes on intermediate activations and find they achieve substantially better calibration; a result
arXiv:2607.08063v1 Announce Type: new Abstract: Unsupervised constituency parsing aims to accurately induce latent tree structures from raw text alone. Recent neural parameterizations of PCFGs achieve strong performance in both supervised and unsupervised parsing, yet rely on high-capacity black-box networks for rule scoring -- as exemplified by the Neural PCFG family -- leaving rule probabilities without an interpretable mathematical form. In this paper, we propose Holographic Neural PCFG (Hol-
arXiv:2607.08071v1 Announce Type: new Abstract: Online ads are essential to all businesses and ad headlines are one of their core creative component. Existing methods can generate headlines automatically and also optimize their click-through-rate (CTR) and quality. However, evolving ad formats and changing creative requirements make it difficult to generate optimized & customized headlines. We propose a novel method that uses prefix control tokens along with BART fine-tuning. It yields the highe
