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product#image generation📝 BlogAnalyzed: Jan 14, 2026 00:15

AI-Powered Character Creation: A Designer's Journey with Whisk

Published:Jan 14, 2026 00:02
1 min read
Qiita AI

Analysis

This article explores the practical application of AI tools like Whisk for character design, a crucial area for content creators. While focusing on the challenges faced by non-illustrative designers, the success and failure can provide valuable insights to other AI-based character generation tools and workflows.

Key Takeaways

Reference

The article references previous attempts to use AI like ChatGPT and Copilot, highlighting the common issues of character generation: vanishing features and unwanted results.

business#voice📝 BlogAnalyzed: Jan 15, 2026 07:10

Flip Secures $20M Series A to Revolutionize Business Customer Service with Voice AI

Published:Jan 13, 2026 15:00
1 min read
Crunchbase News

Analysis

Flip's focus on a verticalized approach, specifically targeting business customer service, could allow for more specialized AI training data and, potentially, superior performance compared to general-purpose solutions. The success of this Series A funding indicates investor confidence in the growth potential of AI-powered customer service, especially if it can provide demonstrable ROI and enhanced customer experiences.
Reference

Flip, a startup that claims to offer an Amazon Alexa-like voice AI experience for businesses, has raised $20 million in a Series A funding round...

Analysis

The advancement of Rentosertib to mid-stage trials signifies a major milestone for AI-driven drug discovery, validating the potential of generative AI to identify novel biological pathways and design effective drug candidates. However, the success of this drug will be crucial in determining the broader adoption and investment in AI-based pharmaceutical research. The reliance on a single Reddit post as a source limits the depth of analysis.
Reference

…the first drug generated entirely by generative artificial intelligence to reach mid-stage human clinical trials, and the first to target a novel AI-discovered biological pathway

policy#ethics📝 BlogAnalyzed: Jan 6, 2026 18:01

Japanese Government Addresses AI-Generated Sexual Content on X (Grok)

Published:Jan 6, 2026 09:08
1 min read
ITmedia AI+

Analysis

This article highlights the growing concern of AI-generated misuse, specifically focusing on the sexual manipulation of images using Grok on X. The government's response indicates a need for stricter regulations and monitoring of AI-powered platforms to prevent harmful content. This incident could accelerate the development and deployment of AI-based detection and moderation tools.
Reference

木原稔官房長官は1月6日の記者会見で、Xで利用できる生成AI「Grok」による写真の性的加工被害に言及し、政府の対応方針を示した。

Analysis

This paper is significant because it bridges the gap between the theoretical advancements of LLMs in coding and their practical application in the software industry. It provides a much-needed industry perspective, moving beyond individual-level studies and educational settings. The research, based on a qualitative analysis of practitioner experiences, offers valuable insights into the real-world impact of AI-based coding, including productivity gains, emerging risks, and workflow transformations. The paper's focus on educational implications is particularly important, as it highlights the need for curriculum adjustments to prepare future software engineers for the evolving landscape.
Reference

Practitioners report a shift in development bottlenecks toward code review and concerns regarding code quality, maintainability, security vulnerabilities, ethical issues, erosion of foundational problem-solving skills, and insufficient preparation of entry-level engineers.

Paper#web security🔬 ResearchAnalyzed: Jan 3, 2026 18:35

AI-Driven Web Attack Detection Framework for Enhanced Payload Classification

Published:Dec 29, 2025 17:10
1 min read
ArXiv

Analysis

This paper presents WAMM, an AI-driven framework for web attack detection, addressing the limitations of rule-based WAFs. It focuses on dataset refinement and model evaluation, using a multi-phase enhancement pipeline to improve the accuracy of attack detection. The study highlights the effectiveness of curated training pipelines and efficient machine learning models for real-time web attack detection, offering a more resilient approach compared to traditional methods.
Reference

XGBoost reaches 99.59% accuracy with microsecond-level inference using an augmented and LLM-filtered dataset.

Analysis

This paper addresses the critical and growing problem of security vulnerabilities in AI systems, particularly large language models (LLMs). It highlights the limitations of traditional cybersecurity in addressing these new threats and proposes a multi-agent framework to identify and mitigate risks. The research is timely and relevant given the increasing reliance on AI in critical infrastructure and the evolving nature of AI-specific attacks.
Reference

The paper identifies unreported threats including commercial LLM API model stealing, parameter memorization leakage, and preference-guided text-only jailbreaks.

Analysis

This article likely presents a novel AI-based method for improving the detection and visualization of defects using active infrared thermography. The core technique involves masked sequence autoencoding, suggesting the use of an autoencoder neural network that is trained to reconstruct masked portions of input data, potentially leading to better feature extraction and noise reduction in thermal images. The source being ArXiv indicates this is a research paper, likely detailing the methodology, experimental results, and performance comparisons with existing techniques.
Reference

Analysis

This paper addresses the challenge of long-range weather forecasting using AI. It introduces a novel method called "long-range distillation" to overcome limitations in training data and autoregressive model instability. The core idea is to use a short-timestep, autoregressive "teacher" model to generate a large synthetic dataset, which is then used to train a long-timestep "student" model capable of direct long-range forecasting. This approach allows for training on significantly more data than traditional reanalysis datasets, leading to improved performance and stability in long-range forecasts. The paper's significance lies in its demonstration that AI-generated synthetic data can effectively scale forecast skill, offering a promising avenue for advancing AI-based weather prediction.
Reference

The skill of our distilled models scales with increasing synthetic training data, even when that data is orders of magnitude larger than ERA5. This represents the first demonstration that AI-generated synthetic training data can be used to scale long-range forecast skill.

Analysis

This paper addresses a critical challenge in deploying AI-based IoT security solutions: concept drift. The proposed framework offers a scalable and adaptive approach that avoids continuous retraining, a common bottleneck in dynamic environments. The use of latent space representation learning, alignment models, and graph neural networks is a promising combination for robust detection. The focus on real-world datasets and experimental validation strengthens the paper's contribution.
Reference

The proposed framework maintains robust detection performance under concept drift.

Research#AI in Space🔬 ResearchAnalyzed: Jan 4, 2026 09:54

LeLaR: First In-Orbit AI Satellite Attitude Controller Demonstrated

Published:Dec 22, 2025 17:00
1 min read
ArXiv

Analysis

The article reports on the successful in-orbit demonstration of an AI-based satellite attitude controller, LeLaR. This represents a significant advancement in satellite technology, potentially leading to improved performance and autonomy. The use of AI for attitude control could enable more efficient operations and faster response times. The source, ArXiv, suggests this is a research paper, indicating a focus on innovation and scientific rigor.
Reference

Analysis

This article describes a research paper on using a Vision-Language Model (VLM) for diagnosing Diabetic Retinopathy. The approach involves quadrant segmentation, few-shot adaptation, and OCT-based explainability. The focus is on improving the accuracy and interpretability of AI-based diagnosis in medical imaging, specifically for a challenging disease. The use of few-shot learning suggests an attempt to reduce the need for large labeled datasets, which is a common challenge in medical AI. The inclusion of OCT data and explainability methods indicates a focus on providing clinicians with understandable and trustworthy results.
Reference

The article focuses on improving the accuracy and interpretability of AI-based diagnosis in medical imaging.

Analysis

This research explores the application of AI, specifically attention mechanisms and Grad-CAM visualization, to improve tea leaf disease recognition. The use of these techniques has the potential to enhance the accuracy and interpretability of AI-based disease detection in agriculture.
Reference

The study utilizes attention mechanisms and Grad-CAM visualization for improved disease detection.

Analysis

This article likely explores the psychological underpinnings of student trust in AI learning tools. It would likely investigate factors such as perceived competence, transparency, and user experience. The source, ArXiv, suggests this is a research paper, focusing on empirical evidence and analysis.

Key Takeaways

    Reference

    Research#Fetal Biometry🔬 ResearchAnalyzed: Jan 10, 2026 09:58

    New Benchmark Dataset Aims to Improve Fetal Biometry Accuracy with AI

    Published:Dec 18, 2025 16:13
    1 min read
    ArXiv

    Analysis

    This research focuses on improving fetal biometry using AI, a critical application for prenatal health monitoring. The development of a multi-center, multi-device benchmark dataset is a significant step towards standardizing and advancing AI-driven analysis in this field.
    Reference

    A multi-centre, multi-device benchmark dataset for landmark-based comprehensive fetal biometry.

    Finance#AI Insurance📝 BlogAnalyzed: Dec 28, 2025 21:58

    Nirvana Insurance Raises $100M Series D, Valuation Nearly Doubles to $1.5B

    Published:Dec 18, 2025 14:30
    1 min read
    Crunchbase News

    Analysis

    Nirvana Insurance, an AI-powered commercial insurance platform for the trucking industry, has secured a significant $100 million Series D funding round. This investment catapults the company's valuation to $1.5 billion, representing a substantial increase from its $830 million valuation just nine months prior. The rapid valuation growth underscores the increasing investor confidence in AI applications within the insurance sector, particularly in niche markets like trucking. This funding will likely fuel further expansion, product development, and potentially strategic acquisitions, solidifying Nirvana Insurance's position in the competitive landscape.
    Reference

    N/A (No direct quote in the provided text)

    Analysis

    The article analyzes the performance of Convolutional Neural Networks (CNNs) and VGG-16 in detecting pornographic content. This research contributes to the ongoing efforts to develop robust AI-powered content moderation systems.
    Reference

    The study compares CNN and VGG-16 models.

    Research#Medical Imaging🔬 ResearchAnalyzed: Jan 10, 2026 10:42

    Optimizing AI for Medical Image Registration: A Faster Approach

    Published:Dec 16, 2025 16:29
    1 min read
    ArXiv

    Analysis

    This ArXiv article likely presents a novel method to improve the speed of AI-based medical image registration. Efficiency gains in this area can significantly benefit clinical workflows and improve patient care.
    Reference

    The article focuses on optimizing a generalized AI-based medical image registration method.

    Analysis

    This article describes a research paper proposing an AI-based framework. The focus is on applying AI to analyze and address sustainability challenges within the medical device development lifecycle. The use of AI suggests potential for automated analysis and identification of conflicts, which could lead to more sustainable practices.

    Key Takeaways

      Reference

      The article likely discusses the specific AI techniques used, the types of sustainability conflicts considered, and the potential benefits of the framework.

      Analysis

      This ArXiv article presents a novel AI approach for segmenting coronary arteries from CCTA scans, leveraging spatial frequency joint modeling for improved accuracy. The research offers a potentially valuable advancement in medical image analysis and could lead to more precise diagnosis.
      Reference

      The article's context indicates the research focuses on coronary artery segmentation from CCTA scans.

      Research#Image🔬 ResearchAnalyzed: Jan 10, 2026 11:41

      Evaluating AI Image Fingerprint Robustness: A Systemic Analysis

      Published:Dec 12, 2025 18:33
      1 min read
      ArXiv

      Analysis

      This ArXiv article likely investigates the vulnerability of AI-generated image fingerprints to various attacks and manipulations. The research aims to understand how robust these fingerprints are, which is crucial for applications like image authentication and copyright protection.
      Reference

      The article is sourced from ArXiv, indicating a research paper.

      Research#llm🔬 ResearchAnalyzed: Jan 4, 2026 10:04

      Three methods, one problem: Classical and AI approaches to no-three-in-line

      Published:Dec 12, 2025 11:12
      1 min read
      ArXiv

      Analysis

      The article likely discusses different methods, both classical and AI-based, for solving the "no-three-in-line" problem. This suggests a comparison of traditional algorithmic approaches with those leveraging AI, potentially including machine learning or other AI techniques. The focus is on the problem itself and the diverse strategies employed to tackle it.

      Key Takeaways

        Reference

        Analysis

        This article, sourced from ArXiv, focuses on improving diffusion models by addressing visual artifacts. It utilizes Explainable AI (XAI) techniques, specifically flaw activation maps, to identify and refine these artifacts. The core idea is to leverage XAI to understand and correct the imperfections in the generated images. The research likely explores how these maps can pinpoint areas of concern and guide the model's refinement process.

        Key Takeaways

          Reference

          Research#Evaluation🔬 ResearchAnalyzed: Jan 10, 2026 12:53

          AI Evaluators: Selective Test-Time Learning for Improved Judgment

          Published:Dec 7, 2025 09:28
          1 min read
          ArXiv

          Analysis

          The article likely explores a novel approach to enhance the performance of AI-based evaluators. Selective test-time learning suggests a focus on refining evaluation capabilities in real-time, potentially leading to more accurate and reliable assessments.
          Reference

          The article is sourced from ArXiv, indicating it's a research paper.

          Research#Recycling🔬 ResearchAnalyzed: Jan 10, 2026 13:03

          AI-Powered Recycling System Automates WEEE Sorting with X-ray Imaging and Robotics

          Published:Dec 5, 2025 10:36
          1 min read
          ArXiv

          Analysis

          This research outlines a promising advancement in waste electrical and electronic equipment (WEEE) recycling, combining cutting-edge AI techniques with robotic manipulation for improved efficiency. The paper's contribution lies in integrating these technologies into a practical system, potentially leading to more sustainable and cost-effective recycling processes.
          Reference

          The system employs X-ray imaging, AI-based object detection and segmentation, and Delta robot manipulation.

          Ethics#Agent🔬 ResearchAnalyzed: Jan 10, 2026 13:40

          Multi-Agent AI Collusion Risks in Healthcare: An Adversarial Analysis

          Published:Dec 1, 2025 12:17
          1 min read
          ArXiv

          Analysis

          This research from ArXiv highlights crucial ethical and safety concerns within AI-driven healthcare, focusing on the potential for multi-agent collusion. The adversarial approach underscores the need for robust oversight and defensive mechanisms to mitigate risks.
          Reference

          The research exposes multi-agent collusion risks in AI-based healthcare.

          Analysis

          This article likely presents a novel approach to improve the demodulation of communication signals in challenging environments. The focus is on using Masked Symbol Modeling, a technique potentially leveraging AI, to address the problem of impulsive noise. The use of oversampled baseband signals suggests a focus on signal processing techniques. The source, ArXiv, indicates this is a research paper.
          Reference

          Research#llm🔬 ResearchAnalyzed: Jan 4, 2026 12:04

          Domain-Specific Foundation Model Improves AI-Based Analysis of Neuropathology

          Published:Nov 30, 2025 22:50
          1 min read
          ArXiv

          Analysis

          The article discusses the application of a domain-specific foundation model to improve AI-based analysis in the field of neuropathology. This suggests advancements in medical image analysis and potentially more accurate diagnoses or research capabilities. The use of a specialized model indicates a focus on tailoring AI to the specific nuances of neuropathological data, which could lead to more reliable results compared to general-purpose models.
          Reference

          Research#llm🔬 ResearchAnalyzed: Jan 4, 2026 07:55

          Smart-TCP: An Agentic AI-based Autonomous and Adaptive TCP Protocol

          Published:Nov 29, 2025 13:55
          1 min read
          ArXiv

          Analysis

          The article introduces Smart-TCP, a new TCP protocol leveraging agentic AI for autonomous and adaptive network management. This suggests a move towards more intelligent and self-optimizing network infrastructure. The use of 'agentic AI' implies a focus on proactive decision-making and learning within the protocol itself, potentially leading to improved performance and resilience compared to traditional TCP implementations. The source being ArXiv indicates this is a research paper, likely detailing the technical aspects, performance evaluations, and potential limitations of Smart-TCP.
          Reference

          Analysis

          This article proposes an AI-based method for analyzing errors in English writing, specifically for English as a Foreign Language (EFL) learners. The focus is on creating a taxonomy of errors to improve writing instruction. The use of AI suggests potential for automated error detection and feedback.

          Key Takeaways

          Reference

          Research#llm🔬 ResearchAnalyzed: Jan 4, 2026 07:14

          AI for software engineering: from probable to provable

          Published:Nov 28, 2025 13:14
          1 min read
          ArXiv

          Analysis

          This article likely discusses the application of AI, specifically in the context of software engineering. The title suggests a progression from AI-based solutions that offer probable outcomes to those that can provide provable guarantees. This implies a focus on areas like formal verification, automated testing, or code generation with verifiable correctness. The source, ArXiv, indicates this is a research paper, suggesting a technical and in-depth analysis of the topic.

          Key Takeaways

            Reference

            Research#llm📝 BlogAnalyzed: Dec 26, 2025 13:53

            Import AI 432: AI malware, frankencomputing, and Poolside's big cluster

            Published:Oct 20, 2025 13:38
            1 min read
            Jack Clark

            Analysis

            This newsletter excerpt highlights emerging trends in AI, specifically focusing on the concerning development of AI-based malware. The mention of "frankencomputing" suggests a growing trend of combining different computing architectures, potentially to optimize AI workloads. Poolside's large cluster indicates significant investment and activity in AI research and development. The potential for AI malware that can operate autonomously and adapt to its environment is a serious security threat that requires immediate attention and proactive countermeasures. The newsletter effectively raises awareness of these critical areas within the AI landscape.
            Reference

            A smart agent that ‘lives off the land’ is within reach

            Research#llm📝 BlogAnalyzed: Dec 29, 2025 09:02

            Scaling AI-based Data Processing with Hugging Face + Dask

            Published:Oct 9, 2024 00:00
            1 min read
            Hugging Face

            Analysis

            This article from Hugging Face likely discusses how to efficiently process large datasets for AI applications. It probably explores the integration of Hugging Face's libraries, which are popular for natural language processing and other AI tasks, with Dask, a parallel computing library. The focus would be on scaling data processing to handle the demands of modern AI models, potentially covering topics like distributed computing, data parallelism, and optimizing workflows for performance. The article would aim to provide practical guidance or examples for developers working with large-scale AI projects.
            Reference

            The article likely includes specific examples or code snippets demonstrating the integration of Hugging Face and Dask.

            Software#AI Inference👥 CommunityAnalyzed: Jan 3, 2026 16:17

            Nitro: A fast, lightweight inference server with OpenAI-Compatible API

            Published:Jan 6, 2024 01:50
            1 min read
            Hacker News

            Analysis

            The article highlights a new inference server, Nitro, emphasizing its speed, lightweight nature, and compatibility with the OpenAI API. This suggests a focus on efficiency and ease of integration for developers working with large language models. The mention of OpenAI compatibility is a key selling point, as it allows for seamless integration with existing OpenAI-based applications.
            Reference

            Product#Emoji Gen👥 CommunityAnalyzed: Jan 10, 2026 16:00

            AI-Powered Emoji Generation Emerges

            Published:Sep 8, 2023 13:54
            1 min read
            Hacker News

            Analysis

            This article discusses an AI-based system for generating emojis, representing a potential intersection of artificial intelligence and creative expression. The focus on emoji generation suggests a move towards more personalized and nuanced digital communication.
            Reference

            The article's source is Hacker News.

            Research#llm👥 CommunityAnalyzed: Jan 4, 2026 10:17

            Free AI-based music demixing in the browser

            Published:Jul 13, 2023 12:03
            1 min read
            Hacker News

            Analysis

            This article announces a free AI-based music demixing tool accessible in a web browser. The focus is on accessibility and the use of AI for a specific audio processing task. The source, Hacker News, suggests a tech-savvy audience and a potential for community discussion and feedback.
            Reference

            Analysis

            The article's title suggests an exploration of the impact of AI, specifically ChatGPT and AI-based program generation, on the future of software development. It implies a discussion of potential changes, challenges, and opportunities within the software industry.

            Key Takeaways

              Reference

              Analysis

              This article highlights a significant application of AI in conservation efforts. The development of an AI-based mobile app for identifying shark and ray fins is a promising step towards combating the illegal wildlife trade. The app's potential to streamline identification processes and empower enforcement agencies is noteworthy. However, the article lacks detail regarding the app's accuracy, training data, and accessibility to relevant stakeholders. Further information on these aspects would strengthen the assessment of its overall impact and effectiveness. The source being Microsoft AI suggests a focus on the technological aspect, potentially overlooking the socio-economic factors driving the illegal trade.

              Key Takeaways

              Reference

              Singapore develops Asia’s first AI-based mobile app for shark and ray fin identification to combat illegal wildlife trade

              Analysis

              This article summarizes a podcast episode featuring Prashanth Chandrasekar, CEO of Stack Overflow. The discussion covers the impact of the pandemic on Stack Overflow, community management strategies for over 100 million monthly users, and Stack Overflow's AI journey. The episode explores their current use of machine learning, their role in AI-based code generation, and emerging trends. The article highlights the challenges of managing a large online community and the company's forward-looking approach to AI and technology.
              Reference

              In our discussion with Prashanth, we explore the impact the pandemic has had on Stack Overflow...

              Analysis

              The article likely explores the dual nature of AI code generation, highlighting both its potential benefits (fun) and potential risks or negative consequences (dystopia). The use of GPT-J-6B suggests a focus on a specific large language model and its capabilities in this domain. The Hacker News source implies a technical and potentially critical audience.

              Key Takeaways

              Reference

              AI in Business#Conversational AI📝 BlogAnalyzed: Dec 29, 2025 08:24

              Conversational AI for the Intelligent Workplace with Gillian McCann - TWiML Talk #167

              Published:Jul 26, 2018 13:49
              1 min read
              Practical AI

              Analysis

              This podcast episode from Practical AI features Gillian McCann, Head of Cloud Engineering and AI at Workgrid Software. The discussion centers on Workgrid's application of cloud-based AI services. McCann provides insights into the underlying systems, engineering pipelines, and the development of high-quality systems that integrate external APIs. The conversation also touches upon user experience, specifically addressing factors that contribute to user misunderstandings and impatience with AI-based products. The focus is on practical applications and the challenges of implementing AI in the workplace.
              Reference

              Gillian details some of the underlying systems that make Workgrid tick, their engineering pipeline & how they build high quality systems that incorporate external APIs and her view on factors that contribute to misunderstandings and impatience on the part of users of AI-based products.

              Research#llm📝 BlogAnalyzed: Dec 29, 2025 08:27

              Exploring AI-Generated Music with Taryn Southern - TWiML Talk #139

              Published:May 17, 2018 17:02
              1 min read
              Practical AI

              Analysis

              This article discusses an interview with Taryn Southern, a singer and digital storyteller, about her upcoming AI-generated album "I AM AI." The interview explores the process of creating music using AI tools, including Google Magenta, Watson Beat, AMPer, and Landr. The discussion covers various aspects of AI music creation, offering insights into the tools and techniques used. The article highlights the innovative use of AI in music production and provides a glimpse into the future of music creation.

              Key Takeaways

              Reference

              Taryn and I explore all aspects of what it means to create music with modern AI-based tools, and the different processes she’s used to create her singles Break Free, Voices in My Head, and more.

              Business#AI Applications📝 BlogAnalyzed: Dec 29, 2025 08:36

              Nexus Lab Cohort 2 - Bowtie - TWiML Talk #64

              Published:Nov 7, 2017 23:54
              1 min read
              Practical AI

              Analysis

              This article summarizes a podcast episode featuring Ron Fisher and Mike Wang, founders of Bowtie Labs. Bowtie Labs is an AI-powered receptionist designed to boost retail conversion rates for businesses in the beauty, wellness, and fitness industries. The discussion focuses on the challenges of building and scaling conversational AI, including outgrowing commercial platforms and optimizing machine learning models for responsiveness. The article highlights the founders' experiences and the techniques they employ. It provides a glimpse into the practical aspects of developing AI solutions for specific business needs.
              Reference

              Ron and Mike shared their own experiences with decision, and shared some of the challenges they’re trying to overcome with their ML models, as well as some of the techniques they use to make their system as responsive as possible.

              Analysis

              This article summarizes a podcast episode discussing Intel's AI strategy, particularly focusing on the Nervana Systems acquisition. The conversation highlights Intel's plans to leverage its general-purpose compute leadership to dominate the AI market. Key areas of focus include specialized AI silicon, end-to-end solutions across cloud, enterprise, and edge computing, and tools to facilitate the rapid productization and scaling of AI-based solutions. The article also mentions the release of new tools like Neon 2.0 and Nervana Graph, emphasizing the latter's potential and encouraging readers to explore its GitHub repository.
              Reference

              N/A

              AI News#Audio AI📝 BlogAnalyzed: Dec 29, 2025 08:42

              From Particle Physics to Audio AI with Scott Stephenson - TWiML Talk #19

              Published:Apr 14, 2017 15:58
              1 min read
              Practical AI

              Analysis

              This article summarizes a podcast episode featuring Scott Stephenson, the co-founder and CEO of Deepgram. The discussion spans a wide range of topics, including the application of machine learning in particle physics, Stephenson's experience in a deep underground lab, and the use of neural networks for audio processing. The episode also touches upon Deepgram's open-sourced Deep Learning Framework, Kur. The article provides a glimpse into the diverse background of Stephenson and the innovative work being done at Deepgram in the field of audio AI.
              Reference

              The article doesn't contain a direct quote.