ZeroHour
DashboardNewsCVEsExploitsIncidentsAIBriefAnalyticsEntitiesWatchlistIOCsAsk the feedSourcesFeeds & APIKiosk mode

Search: “Explainability Assistant”

86 stories

Searchkeywordsmart Sortlatesthotimportancerelevance
DomainAllCyberAIWindow24h3d7d30dAllIn the wildImportant onlyShow duplicates
CategoryAllAI safety & security 31AI industry 18AI tools & infra 13AI research 12Model release 7AI policy 5
SeverityAllcritical 0high 0medium 24low 0info 62

Explainability Assistant: A Conversational XAI Interface for Interpreting Energy Consumption Models

Researchers release Explainability Assistant, an open-source conversational XAI tool using LLM function calling, lifting intent-parsing accuracy from 76.8% to 94%.

The paper introduces the Explainability Assistant, an open-source conversational XAI system for interpreting energy consumption forecasting models such as genetic-programming symbolic regressors. It uses LLM function calling instead of rigid custom grammars, achieving 94% intent-parsing accuracy versus 76.8% for prior work TalkToModel, and adapts to different ML problem types without task-specific fine-tuning. Comparative evaluation with energy domain specialists against a traditional XAI dashboard showed improved usability, with all experts preferring the conversational interface.

arXiv cs.AI / cs.LG / cs.CL · 5d agoAI research1

I wrote an AI textbook — how long until AI can do it better?

AI researcher Nathan Lambert argues LLMs remain weak at long-form technical writing, questioning whether models can autonomously organize scientific knowledge for breakthroughs.

Nathan Lambert describes writing a post-training textbook, Reinforcement Learning from Human Feedback, and finds today's LLMs weak at organizing long-form technical content despite becoming superhuman at coding and math. He notes GPT 5.5 Pro found deep typos across a 200-300 page manuscript while Claude models proved more useful as editors. He argues that compressing knowledge through writing is a prerequisite for autonomous scientific insight and tempers expectations for near-term AI-driven open science.

Interconnects · Aug 12, 2026AI research

How Fyxer built an AI executive assistant people trust

Fyxer details its OpenAI-powered AI executive assistant, orchestrating 30-50 specialized models trained on 500,000+ hours of assistant workflows.

OpenAI published a case study on Fyxer, whose AI executive assistant orchestrates 30-50 specialized OpenAI models trained on more than 500,000 hours of annotated executive assistant workflows. The system uses supervised fine-tuning, LoRA, and Direct Preference Optimization on user edits, and 53% of AI-generated email drafts are accepted as written. Fyxer's annual recurring revenue grew from $1 million to $32 million during 2025.

OpenAI News · 2d agoAI industry

Cognition hits $48B valuation, signaling investors believe AI coding is far from a winner-take-all market

Cognition, maker of Devin, raised $2 billion at a $48 billion valuation led by a16z, Accel, and Founders Fund, with revenue at $900M annualized.

Cognition raised $2 billion at a $48 billion valuation, four months after a $26 billion round, led by Andreessen Horowitz, Accel, Founders Fund, General Catalyst, and Avenir. Its annualized run-rate revenue grew from $492 million to $900 million since May, with projected $4-5 billion by end of 2026, while compute costs could push 2026 burn to $800 million. The startup, founded by Scott Wu, counts Mercedes-Benz, NASA, Goldman Sachs, and Citi as customers and is training its own model to cut reliance on OpenAI and Anthropic.

TechCrunch · AI · 7d agoAI industry

Apple releases iOS 27, macOS Golden Gate 27 with Siri AI and Liquid Glass refinements

Apple released iOS 27 and macOS Golden Gate 27 with a LLM-based Siri AI overhaul powered by new AFM 3 on-device and cloud models.

Apple shipped its 2026 annual OS updates: iOS 27, macOS 27 Golden Gate, watchOS 27, visionOS 27, and tvOS 27. Siri AI is the flagship feature, offering context-aware responses, personal history search, app interaction, and a dedicated Siri app. The stack includes AFM 3 Core (3B parameters on-device), AFM 3 Core Advanced (20B sparse model activating 1-4B parameters), plus AFM 3 Cloud, ADM 3 Cloud (Image), and AFM 3 Cloud Pro server models. Additional features include prompt-generated Shortcuts and Safari extensions, new photo editing options, and a Liquid Glass transparency slider.

Ars Technica · AI · 1d agoAI industry1

OpenAI Pledges $1bn to Bring its AI Cybersecurity Tools to Essential Services

OpenAI pledged $1bn to subsidize Daybreak cybersecurity model access for water, power, banking, government and nonprofit defenders, starting in the US with an MS-ISAC pilot.

OpenAI announced a $1 billion pledge to subsidize access to its Daybreak cyber models for essential services including water, electricity, local governments, nonprofits and banking, starting in the US and expanding to partner countries. The Daybreak for Frontline Defenders initiative includes a pilot with the Multi-State Information Sharing and Analysis Center (MS-ISAC) pairing model access with guided training for public sector and water system defenders. OpenAI unveiled Daybreak in May 2026, deploying frontier LLMs and its Codex coding assistant for defender tasks, and split it into Daybreak Red and Daybreak Blue tiers in August. The pledge follows an August 27 open letter from more than 100 tech and cybersecurity companies warning of a narrowing window before AI-enabled attacks escalate.

Infosecurity Magazine · 12d agoAI industry1

Clearview AI Is Testing an AI Tool That Would Let Cops Unearth Your Life Online

Clearview AI is prototyping InquiryIQ, an AI analyst assistant that would automatically profile individuals identified through its face-recognition searches for police.

WIRED uncovered InquiryIQ, an unreleased Clearview AI prototype described as an AI analyst assistant that fans out across the web from a face-recognition search result to assemble profiles including employers, aliases, associates, and physical characteristics. The company tested a model from xAI (merged with SpaceX), maker of Grok, and the interface accepts age, gender, and race inputs to guide searches. Clearview says the prototype was never pitched or shipped to customers and no law enforcement user has used it; the database has grown to over 70 billion images used by more than 2,000 law enforcement agencies.

WIRED · Security · 6d agoAI industry1

Bad Likert Judge: A Novel Multi-Turn Technique to Jailbreak LLMs by Misusing Their Evaluation Capability

Unit 42 details the Bad Likert Judge multi-turn jailbreak that abuses LLMs' evaluation capability, raising attack success rates over 60% across six frontier models.

Palo Alto Networks Unit 42 describes the Bad Likert Judge technique, a multi-turn jailbreak that asks a target LLM to act as a Likert-scale judge scoring the harmfulness of example responses. The highest-rated example in each scale can carry harmful content, bypassing the model's internal guardrails. Testing across six state-of-the-art text-generation LLMs showed an average attack success rate increase of more than 60% versus plain attack prompts, with tested models anonymized. The technique targets edge cases rather than typical use, and the article positions the work as guidance for defenders on potential jailbreak risks.

Palo Alto Unit 42 · Aug 17, 2026AI safety & security

AI Agents Are Here. So Are the Threats.

Unit 42 demonstrates nine framework-agnostic attack scenarios against AI agents built with CrewAI and AutoGen, causing data leakage, credential theft and remote code execution.

Palo Alto Networks Unit 42 investigated how attackers can target agentic applications, implementing two functionally identical apps with the open-source CrewAI and AutoGen frameworks and executing the same attacks on both. Nine attack scenarios produce outcomes including information leakage, credential theft, tool exploitation and remote code execution. Findings show most vulnerabilities are framework-agnostic, arising from insecure design patterns, misconfigurations and unsafe tool integrations rather than flaws in the frameworks themselves. The team published defense strategies per scenario and open-sourced the source code and datasets on GitHub.

Palo Alto Unit 42 · Aug 17, 2026AI safety & security

Separating AI's Technological Problems from Its Capitalism Problems

Schneier and Sanders argue AI's harms stem from capitalist incentives and governance gaps, not just technical limits, urging structural reform.

Writing with Nathan E. Sanders in Tech Policy Press, Bruce Schneier argues that AI's technological problems (hallucination, sycophancy, overconfidence) must be separated from socio-political problems created by capitalist market incentives. The essay contrasts US frontier-scale, energy-intensive development with China's incentive-driven leaner open models on commodity hardware, and cites Switzerland's Apertus model - trained on licensed data using public computing and renewable hydropower - as a public-interest alternative. It contends that proposals like research pauses, data-center moratoria, and federal screening conflate technology problems with governance problems, and that society faces independent choices on both axes.

Schneier on Security · Aug 15, 2026AI policy

Cocomelon's Studio Tells Its Artists to Start Experimenting With AI

Moonbug Entertainment, studio behind Cocomelon and Blippi, issued generative AI guidelines requiring human authorship and legal review of all AI use.

Moonbug Entertainment, producer of Cocomelon, Little Baby Bum, Blippi, and Mia's Magic Playground, shared its 'Studio AI Bible' and generative AI policy with 404 Media. The guidelines permit AI for ideation, storyboarding, and utility tasks but require substantial human creative input on core elements, legal approval of every tool, and a 'provenance and isolation' filing system to preserve copyright. A spokesperson said generative AI is not currently used in aired episodes. Moonbug content has hundreds of millions of YouTube subscribers, with Cocomelon spinoffs on Netflix, a Universal movie in development, and a Disney+ move planned next year.

404 Media · 19d agoAI industry

Meta AI builds detailed profiles of children from years of family posts

Meta AI suggested questions about a child and assembled detailed family profiles from years of Facebook posts, including a photo deleted years ago.

A mother reported that Meta AI on Facebook suggested the question 'Who is the child passenger?' and then aggregated her children's names, birth dates, videos, and a photo she had deleted years ago. The assistant also pieced together old posts to pinpoint her home location when prompted with 'Where does Kalie Robins live?'. Meta admitted the prompt 'never should have' appeared and said it fixed the suggestion issue, while noting the data came from posts the asker could already access. The article situates this among prior Meta AI privacy failures, including publicly shared chats and a bug exposing private conversations via guessable IDs.

Malwarebytes Labs · 1d agoAI safety & security

Meta says it’s changing AI suggestions after posing invasive personal questions

Meta is fixing Meta AI suggested prompts after a viral video showed the chatbot compiling invasive questions about a user's children from her Facebook posts.

Meta said it 'missed the mark' and has fixed the issue after Instagram user Kalie Robins showed Meta AI suggesting 'Who is the child passenger?' beneath a video with her child and then piecing together details about her daughters from her and relatives' posts. The assistant also surfaced photos of her children, including one the user claims she deleted years ago. Meta AI is embedded in Facebook, Instagram, WhatsApp, and Messenger; in July the company pulled an Instagram user-deepfake feature after backlash.

The Verge · AIupdated · 4d agofirst · 5d agoAI industry 3 sources