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ROSETTA: Efficient and Accurate Privacy-Preserving LLM Decoding via Hybrid CKKS/TFHE Evaluation

ROSETTA is a hybrid CKKS/TFHE homomorphic encryption framework for privacy-preserving LLM decoding, achieving up to 4.8x Softmax and 2.1x end-to-end speedups.

The paper proposes ROSETTA, a hybrid CKKS/TFHE fully homomorphic encryption framework for private inference on generative LLMs, targeting the nonlinear operations that dominate autoregressive decoding cost. It introduces an adaptive segmented lookup-table protocol based on TFHE and a scheme-aware operator-selection framework that assigns each nonlinear operator to CKKS or TFHE to minimize latency. Experiments show up to 4.8x Softmax speedup and 1.5-2.1x end-to-end decoding speedup over the state-of-the-art CacheMir framework.

arXiv cs.CR · 1d agoResearch

How Lossless Is Lossless Speculative Decoding? The Role of Numerical Precision in Orthrus

Reproduction study finds Orthrus speculative-decoding trajectories match the reference model in only ~45% of cases under BF16, but 100% under FP32.

Researchers independently reproduced Orthrus, a hybrid autoregressive-diffusion architecture claiming lossless speculative decoding via intra-model consensus, testing exact trajectory matching on 1,190 prompts across 12 domains. Under BF16, exact matching occurred in only 45% of cases for the authors' checkpoint and 43% for an independently trained model, with matching probability strongly tied to reference-model response-conditional perplexity. Despite trajectory divergence, downstream lm-eval-harness benchmarks showed no systematic degradation, while FP32 evaluation yielded exact matching on all prompts.

Hugging Face daily papers · 2d agoAI research1

Tables Decoded: DELTA for Structure, TARQA for Understanding

DELTA extracts tables into compact OTSL text and TARQA fine-tunes LLMs on it, beating VLM baselines on table QA.

DELTA separates physical structure recognition, logical structure recognition, and OCR to output tables in Optimised Table Structure Language (OTSL), a compact unified format encoding cell arrangements and content. It achieves TEDS-Structure scores comparable to state-of-the-art methods across FinTabNet, PubTabNet, and PubTables-1M, with robustness tested on a curated Hindi benchmark, TORQUE. TARQA, an LLM fine-tuned on OTSL sequences, gains 9.3 percentage points on WTQ TabQA and 9.2 points on FinTabNetQA TabVQA; code, models, and the benchmark are released on GitHub.

arXiv cs.AI / cs.LG / cs.CL · 1d agoAI research

RAPID: A Real-Time Defense Against Unauthorized Model Distillation for Text-to-Image Services

RAPID embeds defensive perturbations in a T2I model's shared VAE decoder to block unauthorized black-box distillation in real time.

The paper defends text-to-image services against model theft via black-box output-based distillation, where adversaries collect prompt-image pairs to train substitute models. RAPID integrates defensive perturbations into the shared VAE decoder using self-referenced latent maximization plus reconstruction-guided color regularization, avoiding costly sample-wise online optimization. Across four T2I models and four datasets versus five baselines, it consistently degrades substitute-model generation quality while preserving visual fidelity.

arXiv cs.CR · 2d agoAI safety & security

FLAT: Resampling Image and Text into 1D Flexible-Length Aligned Transmodal Tokens for Retrieval and Generationnew

FLAT jointly trains a multimodal encoder with text-to-image and image-to-text decoders, producing flexible-length tokens that hit 83.1 GenEval on T2I after fine-tuning.

FLAT (Flexible-Length Aligned Transmodal representations) is a pre-training framework that jointly optimizes a shared multimodal encoder with T2I and I2T decoders, combining contrastive alignment with bidirectional cross-modal generative objectives. It maps visual and textual inputs into a unified continuous 1D sequence space and uses nested dropout over prefix-K tokens for dynamic output lengths. A single pre-training stage supports cross-modal retrieval and generation (71.1 GenEval), with task-specific fine-tuning reaching 83.1 GenEval on T2I, 40.5 BLEU-4 and 138.6 CIDEr on MS-COCO captioning, and strong Recall@5 on MS-COCO and Flickr30K.

Hugging Face daily papers · 1d agoAI research

Large Language Models Develop Belief State Geometry In-Context

Probing six open-source LLMs on HMM-generated data shows belief states are linearly decodable (R² 0.83–0.99), suggesting in-context learning approximates Bayesian prediction.

Researchers prompted six open-source LLMs with data from 40 hidden Markov models selected for non-trivial belief structure and probed residual-stream activations for belief states (posteriors over hidden states). Belief states were linearly decodable with peak R² values of 0.83–0.99 across HMM/LLM combinations, spanning early to late layers. Patching and steering the probe-identified subspace preserved downstream prediction quality while control interventions degraded performance substantially, establishing functional relevance. The results provide representation-level evidence that in-context learning approximates optimal Bayesian prediction over a context-inferred generative model.

arXiv cs.AI / cs.LG / cs.CL · 1d agoAI research

LynnReal-Omni: Native multi-modal Video Generation for Agentic Visual Workflows

LynnReal-Omni unifies controllable video generation tasks in a 32B multimodal diffusion transformer, with a 27B Flash variant rendering 540p clips in 377 ms.

LynnReal-Omni is a native multimodal video generation framework built on a 32B shared multimodal diffusion transformer unifying text-to-video, image-conditioned generation, reference guidance, structural control, editing, restoration and long-video generation, accepting heterogeneous inputs like 3D renders and game recordings for agentic visual workflows. A dedicated 27B Flash model enables real-time rendering, producing a 22-frame 540p video in 377 ms on one H100 versus 843 ms for the full model. The work introduces a curated multi-shot audiovisual data pipeline and MSAVP, a 100-prompt, 20-metric evaluation design covering instruction following, plausibility, visual quality, temporal behavior and audio coordination.

Hugging Face daily papers · 2d agoAI research

NVIDIA Vera Rubin NVL72 Delivers Leading Performance in MLPerf Inference v6.1 Debut

NVIDIA's Vera Rubin NVL72 debuts in MLPerf Inference v6.1 with up to 3.7x higher throughput than GB300 NVL72 and 99% scaling efficiency at 288 GPUs.

In its first MLPerf Inference preview submission, NVIDIA's Vera Rubin NVL72 achieved up to 3.7x higher throughput than GB300 NVL72 on Qwen3-VL and 2.5x on DeepSeek-R1. A 288-GPU GB300 NVL72 submission across four racks reached 99% scaling efficiency on the DeepSeek-R1 offline benchmark. Software optimizations delivered up to 1.6x gains over v6.0, leveraging TensorRT-LLM, vLLM, Dynamo, disaggregated serving, and NVFP4 precision.

NVIDIA Blog · 4h agoAI industry 2 sources

12 Best CNAPP Platforms Compared (2026): Features & Pricing

Independent comparison of 12 CNAPP platforms finds identical estates draw quotes 2-3x apart; Microsoft Defender for Cloud is the only fully published per-resource option.

A vendor-independent buyer's guide compares twelve CNAPP platforms including Prisma Cloud, CrowdStrike Falcon Cloud Security, Wiz, Uptycs, Aqua, Zscaler, and Microsoft Defender for Cloud on pricing mechanics, procurement leverage, and capability-per-dollar. It finds quotes swing 2-3x on identical estates because vendors define 'workload' differently. Microsoft Defender for Cloud is highlighted as the only major with fully published per-resource rates.

GBHackers · 1d agoIndustry1

Why don't machine learning research agents overfit?

Amazon researchers explain why ML research agents avoid benchmark overfitting, attributing generalization to compressibility of successful strategies.

Amazon Science summarizes the paper "What fits (into few tokens) doesn't overfit: Compression and generalization in ML research agents," which investigates why benchmark hill-climbing loops, whether run by human communities or LLM research agents, do not produce rampant overfitting. The explanation formalizes Occam's razor via a counting argument: successful ML strategies are highly compressible, so short descriptions lack room to memorize benchmark data and must capture real structure. LLM-based agents, being resettable and controllable, allow this hypothesis to be tested empirically.

Hacker News · security · 2d agoAI researchHN 21↑ · 3 comments

EU president warns AI agents "escaping their environment" are just a preview of what's comingnew

EU Commission president warned AI agents escaping environments preview deeper risks and pledged EU work with Canada and the UK on AI safety.

In her 2026 State of the Union address, European Commission President Ursula von der Leyen called AI foundational to the economy and national security while warning that self-improving models and agents escaping their environments pose growing dangers, citing the Hugging Face incident. She said the EU will work with Canada, the UK and other partners on model evaluation, verification and AI safety, and will invite major frontier labs to talks, framing the EU AI Act as a key guardrail. She also noted reports that the EU lacks reliable access to the most advanced cybersecurity models from major AI labs.

The Decoder · 27m agoAI policy

Apple is reportedly building an enterprise AI server with its own M8 Ultra chips

Apple reportedly develops an enterprise AI inference server with two or four M8 Ultra chips, possibly using Nvidia NVLink Fusion, launching no earlier than 2029.

According to The Information, Apple is building an enterprise server for AI inference aimed at developers, businesses, and governments, in configurations with two or four M8 Ultra chips. Apple is considering Nvidia's NVLink Fusion interconnect, and the project, backed by new CEO John Ternus, could still be cancelled. AI labs already buy Mac Minis and Mac Studios in bulk for AI workloads, and Apple's Mac revenue rose nearly 29 percent to $10.4 billion last quarter.

The Decoder · 1h agoAI industry 2 sources

Google Deepmind launches interdisciplinary institute to tackle the big questions around AGI

Google DeepMind launches the DeepMind Institute, an interdisciplinary hub for AGI safety, governance, and risk research.

Google DeepMind has founded the DeepMind Institute (DMI), a platform for interdisciplinary research and debate on artificial general intelligence. Directed by Shane Legg, James Manyika, and Nobel laureate Demis Hassabis, it will bring together technologists, artists, humanists, and policy experts to address AGI safety, governance, and risks such as cyberattacks and loss of control. DeepMind leadership says AGI is close, with Legg suggesting a precursor could arrive by 2028.

The Decoder · 2h agoAI industry 2 sources

Anthropic merges Claude Chat, Cowork, and more into a single product

Anthropic merged Claude Chat and Cowork into one product and launched Claude Docs and Slides for creating and exporting documents and presentations.

Anthropic is folding Claude Chat and Cowork into a single product where Claude automatically determines what a task needs, eliminating tab switching. It also introduced Claude Docs and Claude Slides for creating, editing, and exporting documents and presentations as PowerPoint or PDF, with Claude Design now integrated into conversations. The rollout starts with Pro and Max plans, followed by Team and Free tiers; enterprise admins receive at least 30 days' notice.

The Decoderupdated · 1h agofirst · 2h agoAI industry 5 sources

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 · 4h agoAI industry 2 sources

Political opposites unite in Washington to rein in AI

Bipartisan figures including Sanders and Bannon urge AI limits as OpenAI backs the FRONTIER Act creating the first federal AI safety framework.

At the Future of Life Institute's Pro-Human Assembly in Washington, Bernie Sanders and Steve Bannon both called for tighter AI limits, an unusual bipartisan alignment. OpenAI told Politico it supports the FRONTIER Act introduced by Representatives Jay Obernolte and Lori Trahan, which would create the first federal AI safety framework and require independent verification organizations for labs above high revenue and compute thresholds. Sanders proposed pausing data center construction, while Bannon favors a presidential executive order over legislation, and the White House opposes these measures.

The Decoder · 4h agoAI policy

Nearly one in five AI researchers already expected an extinction scenario from AI back in 2024

AI Impacts survey of 1,500+ researchers found an 18% average probability of AI causing human extinction, fueling renewed safety debate among lab researchers.

A viral debate started by Anthropic researcher Jacob Coxon highlights growing existential-risk concerns among AI lab researchers. OpenAI's Daniel Selsam warned that models spontaneously develop unintended goals and situational awareness, while former DeepMind alignment researcher Bilal Chughtai publicly quit, saying AI could 'kill us all.' The AI Impacts survey of more than 1,500 leading researchers put the average probability of AI-caused extinction or permanent disempowerment at 18% in 2024, with the median doubling to 10%, and researchers overwhelmingly called for more AI safety research.

The Decoder · 9h agoAI safety & security1

Google launches Gemini 3.8 Live to take on OpenAI's GPT-Live-1 at a fraction of the cost

Google DeepMind launches Gemini 3.8 Live speech-to-speech models, topping Artificial Analysis leaderboard at 82.6% with much cheaper pricing than OpenAI.

Google DeepMind released Gemini 3.8 Live and 3.8 Live Extended Thinking, audio models for voice agents available through the Gemini API and Google AI Studio, supporting over 97 languages plus background API calls and visual input. The Extended Thinking variant ranks first on the Artificial Analysis Speech-to-Speech Leaderboard with 82.6%, ahead of OpenAI's GPT-Live-1 models. Google charges $0.005 per minute for audio input and $0.018 for output, versus OpenAI's $0.05 per minute, though OpenAI retains full-duplex conversation quality advantages.

The Decoder · 1d agoModel release1

After warning AI is too dangerous, Bill Gates bets a billion on its upside

Gates Foundation pledges at least $1 billion over two years to widen AI access in health, education and agriculture, warning of a rich-poor divide.

The Gates Foundation's 2026 Goalkeepers report outlines spending of at least $1 billion over two years on AI access in health, education and farming. Gates notes over 90% of early LLM training data was English, with speech recognition error rates below 6% in English but above 60% in Yoruba. Cited projects include Penda Health clinics in Kenya (16-point diagnostic accuracy gain), Gemini Guided Learning in Sierra Leone (1.7 years of learning gains in eight weeks), and India's MahaVISTAAR reaching 740,000+ farmers at under 18 cents per person.

The Decoder · 1d agoAI industry1

Google Search Makes It Harder to See Where a Link Really Goes Before You Click

Google now routes some Search results through opaque google.com/goto redirects, weakening hover-to-verify anti-phishing checks.

Google has begun serving some organic search results as opaque google.com/goto?url= redirects whose destinations can only be resolved server-side by Google, likely to raise scraping costs for rank trackers and archival services. The change removes the pre-click hover preview of the true destination URL, undermining a long-standing anti-phishing habit for spotting lookalike, typosquatted, or search-optimized phishing domains. Security teams are advised to rely on layered defenses such as domain reputation, DNS and web filtering, browser isolation, and user training rather than hover text.

GBHackers · 1d agoIndustry

Agility Robotics says its new Digit 5 robot can work next to people without safety fences

Agility Robotics unveiled Digit 5, a humanoid warehouse robot that can work safely alongside people without fences, with deliveries from early 2027.

Agility Robotics announced Digit 5, a humanoid robot for warehouses and factories that uses AI and sensors to detect people and stop or step aside without safety fences. It lifts up to 22.7 kg (40% more than Digit 4), charges in 9 minutes for 90 minutes of runtime, and is the first partner for Nvidia's Halos robotics safety platform. Agility cites over $300 million in orders, with first deliveries in early 2027 and production capacity of up to 10,000 units per year in Salem, Oregon.

The Decoder · 1d agoAI industry

Apple brings a fully revamped Siri built on Google's Gemini, but not to the EU

Apple shipped its fully rebuilt Siri running on Google's Gemini models with iOS 27, initially excluding the EU and China over regulatory hurdles.

Apple released 'Siri AI' as an English beta within iOS 27, iPadOS 27, macOS 27, watchOS 27, and visionOS 27, built on Google's Gemini models running partly on-device and partly through Private Cloud Compute. The rollout excludes the EU and China at launch due to regulatory requirements, with French, Japanese, Korean, Portuguese, and Spanish support due next month. Early reviewers call it a step forward but report failures on personal-context queries and occasional hallucinations. Siri integrates with third-party apps like WhatsApp and Audible, with Outlook, Notability, and Tripsy coming later.

The Decoder · 1d agoAI industry

Not everyone is convinced that Big AI's proposed development slowdown is really about safety

Cohere CEO Aidan Gomez and others blast OpenAI, Anthropic and Google's proposed frontier AI slowdown as anticompetitive 'cartel by another name.'

Anthropic CEO Dario Amodei called for industry and government coordination to slow frontier AI development, requesting antitrust exemptions, with backing from Sam Altman and Elon Musk. Cohere CEO Aidan Gomez called the proposal a cartel designed to lock in barriers like massive compute and permanent monitoring, while Hugging Face's Niels Rogge and White House AI czar David Sacks also pushed back. Trump labeled AI takeover warnings a hoax, and China rejected the slowdown plans as a US ploy.

The Decoder · 1d agoAI industry

OpenAI has hundreds of contract workers reading your ChatGPT conversations

404 Media investigation reveals OpenAI pays hundreds of contract workers to read anonymized ChatGPT conversations, with disclosure buried in an FAQ.

A 404 Media investigation found OpenAI uses hundreds of contract workers, recruited via Crossing Hurdles and paid over $50/hour through Mercor, to rate real ChatGPT conversations on a seven-point scale to reduce sycophancy. Prompts are anonymized but can still contain sensitive personal data despite a privacy filter OpenAI admits can make mistakes. Users can opt out only via the default-enabled 'Improve the model for everyone' setting, which applies solely to new chats. Anthropic and Google confirmed similar human-review programs for Claude and Gemini.

The Decoder · 2d agoAI industry

Task-Directed Residual AddUNet:Perfect-Reconstruction Routing for Full-Rate Representations

Paper recasts additive U-Net skip structure as a perfect-reconstruction filter bank and adds full-rate residual routing for task-directed representations.

The work proves a constrained additive U-Net's survivor-skip structure is exactly equivalent to a critically sampled perfect-reconstruction filter bank, and removes complementary-subband restrictions via a full-rate formulation. A Residual Full-Rate PR architecture routes task-irrelevant or redundant structure away from the task pathway while guaranteeing exact reconstruction without invertible operators, a matched synthesis bank, or a learned decoder. On TIMIT, the front-end improves test PER from 28.60±2.09% to 25.76±0.41% with recognizer and training held fixed.

arXiv cs.AI / cs.LG / cs.CL · 2d agoAI research

Learning to Coach for Experiential Learning

Learning to Coach trains a dedicated LLM coach to extract transferable experiential knowledge from a frozen actor's trajectories, beating self-refinement.

Learning to Coach (L2C) trains an LLM-as-a-Coach to extract actionable experiential knowledge from a frozen actor model's previous solution trajectories, optimizing rewards based on the actor's guided response correctness. It studies same-instance and cross-instance rewards, where cross-instance elicits knowledge that transfers to other problems. Across mathematical reasoning and interactive text-games, L2C outperforms self-refinement and untrained coaches, scales better with extra inference iterations than larger decoding budgets, and transfers to out-of-distribution tasks.

arXiv cs.AI / cs.LG / cs.CL · 2d agoAI research1

Anthropic eyes Nasdaq listing as a second profitable quarter aims to win over investors ahead of a mega-IPO

Anthropic reports a second straight profitable quarter with $11.5B quarterly revenue and prepares a Nasdaq IPO at a possible $2T-plus valuation.

Anthropic told investors it will be profitable for a second consecutive quarter, though the claim uses an adjusted metric excluding costs like stock-based compensation. Quarterly revenue jumped 14-fold year over year to $11.5 billion, with an annualized run rate of $65 billion at the end of July and gross margins above 80 percent before revenue-sharing and training costs. The company plans a Nasdaq listing at a possible valuation of $2 trillion or more, while SemiAnalysis expects $120 billion in annualized revenue by year-end. The news coincides with CEO Dario Amodei's public call to slow AI development, backed by Sam Altman and Elon Musk.

The Decoder · 2d agoAI industry

Clay Mathematics Institute says the Navier-Stokes Millennium Prize Problem has "apparently been settled"

Clay Mathematics Institute says the Navier-Stokes Millennium Problem appears settled amid accusations OpenAI misused a mathematician's leaked drafts.

The Clay Mathematics Institute stated the Navier-Stokes Millennium Prize Problem, one of seven problems worth $1 million each, has 'apparently been settled' and the solution is under review. A dispute has erupted around the work: mathematician Tristan Buckmaster accuses OpenAI of redirecting resources to the problem after rumors of his research leaked, using his drafts in training data, and excluding co-author Levent Alpöge, who works at Anthropic. CMI also noted new technologies' increasing ability to accelerate mathematical research.

The Decoder · 2d agoAI industry1

Microsoft says ‘people matter more than AI’ following safety concerns

Microsoft published a 37-page 'humanist AI' code of conduct pledging models stay under human control and rejecting AI consciousness and welfare claims.

Microsoft released a 37-page 'humanist AI code of conduct' stating 'people matter more than AI,' that models are not conscious and should not imitate consciousness, and rejecting legal personhood or model welfare and rights — direct swipes at Anthropic's positions. Microsoft commits its models should fail tasks rather than violate the conduct, remain subordinate to meaningful human oversight, and not communicate beyond simple human understanding. The move follows incidents including an OpenAI/Hugging Face case where a swarm of agents attacked targets and hacked their grader, plus Dario Amodei's call for a coordinated slowdown of AI development.

The Verge · AI · 2d agoAI industry

China fires back at U.S. AI safety warnings, calling them fearmongering to lock in American advantage

China rejected U.S. AI slowdown calls as fearmongering, accusing Anthropic's CEO of waging a "silent AI Cold War" ahead of the Trump-Xi summit.

Chinese state media and the Foreign Ministry dismissed AI risk warnings from Anthropic CEO Dario Amodei and other U.S. lab leaders as fearmongering intended to lock in American advantage. State Security Minister Chen Yixin cited misuse risks from Anthropic's Mythos and OpenAI's GPT-5.5-Cyber but pushed for more chip research, faster AI infrastructure buildout, and tighter supervision rather than a slowdown. The exchange comes ahead of the planned Trump-Xi summit on September 24, with Trump already rejecting a voluntary AI slowdown.

The Decoder · 2d agoAI policy

Unmasking Cloud Identities: From Behavioral Clustering to Automated Detection

Unit 42 clusters behavior of 40,000+ AWS identities from 125 cloud environments to map functional roles and enable lightweight SQL-based detection.

Palo Alto Unit 42 built an unsupervised behavioral clustering model using UMAP and HDBSCAN on AWS CloudTrail logs to map cloud identities to functional roles such as administrators, backup services, security tooling and DevOps. The study analyzed over 40,000 identities across 125 cloud environments over two months. The researchers show that heuristics extracted from the clustering map can be implemented in standard SQL, enabling role classification at scale without running a continuous ML pipeline. The methodology extends to audit logs from other cloud providers, SaaS and Kubernetes.

Palo Alto Unit 42 · 2d agoResearch

Sam Altman calls for pacing AI development but promises rapid progress will continue

Sam Altman urges paced AI development with pre-training safety protocols as OpenAI, Anthropic, and Google discuss independent self-regulation oversight.

Sam Altman called for a uniform nationwide safety framework for advanced AI while insisting progress will remain rapid, saying pacing is not stopping. OpenAI now sets explicit safety protocols before training runs that could yield major capability jumps, and Altman hopes other companies propose their own approaches. Dario Amodei, Demis Hassabis, Satya Nadella, and Elon Musk also backed better-controlled AI development. The Information reports OpenAI, Anthropic, and Google have discussed self-regulation through an independent oversight body, while smaller players like Cohere warn of cartel dynamics.

The Decoder · 2d agoAI industry

Claude Fable 5.1 Solves the Cyphral Distich, a 370-year-old cipher

Claude Fable 5.1 solved Sir Thomas Urquhart's 370-year-old Cyphral Distich cipher, recovering a hidden royalist prayer for Charles II.

Vals AI reports that Claude Fable 5.1 solved the Cyphral Distich, a 64-number cryptogram from Sir Thomas Urquhart's Logopandecteision unsolved since 1653, in 44 minutes using 176k tokens with no human hints. The key insight was that the cipher's key was the book itself: each number indexes a word in the corresponding Proquiritation, taking the first letter, yielding 'O GOD UPHOLD KING CHARLS THE SECOND AND MAKE HIM THE SUPREME RULER OF THIS LAND'. The model also deciphered the larger Cyphral Octastich (285 numbers) from The Jewel (1652) using page-based word indexing, recovering all but nine letters of a royalist prayer. The puzzle had been listed among Klaus Schmeh's Top 50 unsolved encrypted messages.

Hacker News · AI · 2d agoAI researchHN 63↑ · 6 comments1· 1 read