Best AI tools for< Provide Cloud Security Guidance >

The website en.cloudhumans.com is a platform that utilizes Cloudflare services to manage DNS settings. It provides guidance on resolving issues related to DNS pointing to prohibited IP addresses. Users, particularly website owners, are advised on how to change DNS A records to avoid conflicts within the Cloudflare network. The platform aims to enhance website performance and security by offering solutions for managing DNS configurations effectively.

Cyguru is an all-in-one cloud-based AI Security Operation Center (SOC) that offers a comprehensive range of features for a robust and secure digital landscape. Its Security Operation Center is the cornerstone of its service domain, providing AI-Powered Attack Detection, Continuous Monitoring for Vulnerabilities and Misconfigurations, Compliance Assurance, SecPedia: Your Cybersecurity Knowledge Hub, and Advanced ML & AI Detection. Cyguru's AI-Powered Analyst promptly alerts users to any suspicious behavior or activity that demands attention, ensuring timely delivery of notifications. The platform is accessible to everyone, with up to three free servers and subsequent pricing that is more than 85% below the industry average.

SharkGate is an AI-driven cybersecurity platform that focuses on protecting websites from various cyber threats. The platform offers solutions for mobile security, password management, quantum computing threats, API security, and cloud security. SharkGate leverages artificial intelligence and machine learning to provide advanced threat detection and response capabilities, ensuring the safety and integrity of digital assets. The platform has received accolades for its innovative approach to cybersecurity and has secured funding from notable organizations.

AppSec Assistant is an AI-powered application designed to provide automated security recommendations in Jira Cloud. It focuses on ensuring data security by enabling secure-by-design software development. The tool simplifies setup by allowing users to add their OpenAI API key and organization, encrypts and stores data using Atlassian's Storage API, and provides tailored security recommendations for each ticket to reduce manual AppSec reviews. AppSec Assistant empowers developers by keeping up with their pace and helps in easing the security review bottleneck.

Darktrace is a cybersecurity platform that leverages AI technology to provide proactive protection against cyber threats. It offers cloud-native AI security solutions for networks, emails, cloud environments, identity protection, and endpoint security. Darktrace's AI Analyst investigates alerts at the speed and scale of AI, mimicking human analyst behavior. The platform also includes services such as 24/7 expert support and incident management. Darktrace's AI is built on a unique approach where it learns from the organization's data to detect and respond to threats effectively. The platform caters to organizations of all sizes and industries, offering real-time detection and autonomous response to known and novel threats.

Traceable is an AI-driven application designed to enhance API security for Cloud-Native Apps. It collects API traffic across the application landscape and utilizes advanced context-based behavioral analytics AI engine to provide insights on APIs, data exposure, threat analytics, and forensics. The platform offers features for API cataloging, activity monitoring, endpoint details, ownership, vulnerabilities, protection against security events, testing, analytics, and more. Traceable also allows for role-based access control, policy configuration, data classification, and integration with third-party solutions for data collection and security. It is a comprehensive tool for API security and threat detection in modern cloud environments.

CloudMinds is a world-leading creator, producer, and operator of cloud robot systems and services. Founded in 2015, CloudMinds has created a unique Cloud Robot Architecture based on the vision of “Cloud AI Connecting To The Future”, and launched the HARIX Cloud AI Robot Operating System and end-to-end commercial services in 2017. With the mission of “Operating Smart Robots for People”, the company aims to lead the cutting-edge technologies development for building a humanoid robot for enterprise and families. Our cloud robots will help people to do dull, dirty, dangerous or demeaning (4D) work, and thus making people’s lives more enjoyable.

Kami Home is an AI-powered security application that provides effortless safety and security for homes. It offers smart alerts, secure cloud video storage, and a Pro Security Alarm system with 24/7 emergency response. The application uses AI-vision to detect humans, vehicles, and animals, ensuring that users receive custom alerts for relevant activities. With features like Fall Detect for seniors living at home, Kami Home aims to protect families and provide peace of mind through advanced technology.

Arize AI is an AI observability tool designed to monitor and troubleshoot AI models in production. It provides configurable and sophisticated observability features to ensure the performance and reliability of next-gen AI stacks. With a focus on ML observability, Arize offers automated setup, a simple API, and a lightweight package for tracking model performance over time. The tool is trusted by top companies for its ability to surface insights, simplify issue root causing, and provide a dedicated customer success manager. Arize is battle-hardened for real-world scenarios, offering unparalleled performance, scalability, security, and compliance with industry standards like SOC 2 Type II and HIPAA.

DevSecCops is an AI-driven automation platform designed to revolutionize DevSecOps processes. The platform offers solutions for cloud optimization, machine learning operations, data engineering, application modernization, infrastructure monitoring, security, compliance, and more. With features like one-click infrastructure security scan, AI engine security fixes, compliance readiness using AI engine, and observability, DevSecCops aims to enhance developer productivity, reduce cloud costs, and ensure secure and compliant infrastructure management. The platform leverages AI technology to identify and resolve security issues swiftly, optimize AI workflows, and provide cost-saving techniques for cloud architecture.

Mimecast is an AI-powered email and collaboration security application that offers advanced threat protection, cloud archiving, security awareness training, and more. With a focus on protecting communications, data, and people, Mimecast leverages AI technology to provide industry-leading security solutions to organizations globally. The application is designed to defend against sophisticated email attacks, enhance human risk management, and streamline compliance processes.

Concentric AI is a Managed Data Security Posture Management tool that utilizes Semantic Intelligence to provide comprehensive data security solutions. The platform offers features such as autonomous data discovery, data risk identification, centralized remediation, easy deployment, and data security posture management. Concentric AI helps organizations protect sensitive data, prevent data loss, and ensure compliance with data security regulations. The tool is designed to simplify data governance and enhance data security across various data repositories, both in the cloud and on-premises.

Netify provides network intelligence and visibility. Its solution stack starts with a Deep Packet Inspection (DPI) engine that passively collects data on the local network. This lightweight engine identifies applications, protocols, hostnames, encryption ciphers, and other network attributes. The software can be integrated into network devices for traffic identification, firewalling, QoS, and cybersecurity. Netify's Informatics engine collects data from local DPI engines and uses the power of a public or private cloud to transform it into network intelligence. From device identification to cybersecurity risk detection, Informatics provides a way to take a proactive approach to manage network threats, bottlenecks, and usage. Lastly, Netify's Data Feeds provide data to help vendors understand how applications behave on the Internet.

Airship AI is a cutting-edge, artificial intelligence-driven video, sensor, and data management surveillance platform. Customers rely on their services to provide actionable intelligence in real-time, collected from a wide range of deployed sensors, utilizing the latest in edge and cloud-based analytics. These capabilities improve public safety and operational efficiency for both public sector and commercial clients. Founded in 2006, Airship AI is U.S. owned and operated, headquartered in Redmond, Washington. Airship's product suite is comprised of three core offerings: Acropolis, the enterprise software stack, Command, the family of viewing clients, and Outpost, edge hardware and software AI offerings.

Allwire Technologies, LLC is a boutique IT consultancy firm that specializes in building intelligent IT infrastructure solutions. They offer services such as hybrid infrastructure management, security expertise, IT helpdesk support, operational insurance, and AI-driven solutions. The company focuses on empowering clients by providing tailored IT solutions without vendor lock-in. Allwire Technologies is known for fixing complex IT problems and modernizing existing tech stacks through a combination of cloud and data center solutions.

Loata is an AI-powered platform that serves as a learning orchestrator for adaptive text analyses. It allows users to store their notes and documents in the cloud, which are then ingested and transformed into knowledge bases. The platform features smart AI agents powered by LLMs to provide intelligent answers based on the content. With end-to-end encryption and controlled ingestion, Loata ensures the security and privacy of user data. Users can choose from different subscription plans to access varying levels of storage and query capacity, making it suitable for individuals and professionals alike.

Simplilearn is an online bootcamp and certification platform that offers courses in various fields, including AI and machine learning, project management, cyber security, cloud computing, and data science. The platform partners with leading universities and companies to provide industry-relevant training and certification programs. Simplilearn's courses are designed to help learners develop job-ready skills and advance their careers.

Great Learning is an online platform offering a wide range of courses, PG certificates, and degree programs in various domains such as AI & Machine Learning, Data Science, Business Analytics, Cloud Computing, Cyber Security, Software Development, Digital Marketing, Design, MBA, and Masters. The platform provides opportunities to learn from top universities, offers career support, success stories, and enterprise solutions. With a focus on AI and Machine Learning, Great Learning aims to elevate expertise and provide transformative programs to help individuals enhance their skills and advance their careers.

Clarion Technologies is an AI-assisted development company that offers a wide range of software development services, including custom software development, web app development, mobile app development, cloud solutions, and Power BI solutions. They provide services for various technologies such as React Native, Java, Python, PHP, Laravel, and more. With a focus on AI-driven planning and Agile Project Execution Methodology, Clarion Technologies ensures top-quality results with faster time to market. They have a strong commitment to data security, compliance, and privacy, and offer on-demand access to skilled developers and tech architects.

IBM MediaCenter is an AI tool designed to provide a wide range of solutions in the fields of corporate marketing, blockchain, data, and AI. The platform offers services related to industry-specific technologies, IoT, security, supply chain management, and systems management. With a focus on Watson AI technology, IBM MediaCenter aims to help businesses modernize, collect, organize, analyze, and infuse AI into their operations. The platform also offers technical support, developer support, and training programs for various IBM products and solutions.

AI-in-a-Box is a curated collection of solution accelerators that can help engineers establish their AI/ML environments and solutions rapidly and with minimal friction, while maintaining the highest standards of quality and efficiency. It provides essential guidance on the responsible use of AI and LLM technologies, specific security guidance for Generative AI (GenAI) applications, and best practices for scaling OpenAI applications within Azure. The available accelerators include: Azure ML Operationalization in-a-box, Edge AI in-a-box, Doc Intelligence in-a-box, Image and Video Analysis in-a-box, Cognitive Services Landing Zone in-a-box, Semantic Kernel Bot in-a-box, NLP to SQL in-a-box, Assistants API in-a-box, and Assistants API Bot in-a-box.

This repository provides guidance on building a multi-tenant SaaS solution for accessing foundation models using Amazon Bedrock and Amazon SageMaker. It helps enterprise IT teams track usage and costs of foundation models, regulate access, and provide visibility to cost centers. The solution includes an API Gateway design pattern for standardization and governance, enabling loose coupling between model consumers and endpoint services. The CDK Stack deploys resources for private networking, API Gateway, Lambda functions, DynamoDB table, EventBridge, S3 buckets, and Cloudwatch logs.

LLM App Stack, also known as Emerging Architectures for LLM Applications, is a comprehensive list of available tools, projects, and vendors at each layer of the LLM app stack. It covers various categories such as Data Pipelines, Embedding Models, Vector Databases, Playgrounds, Orchestrators, APIs/Plugins, LLM Caches, Logging/Monitoring/Eval, Validators, LLM APIs (proprietary and open source), App Hosting Platforms, Cloud Providers, and Opinionated Clouds. The repository aims to provide a detailed overview of tools and projects for building, deploying, and maintaining enterprise data solutions, AI models, and applications.

Azure OpenAI Service is a central capability with Azure API Management, providing guidance and tools for organizations to implement Azure OpenAI in a production environment with an emphasis on cost control, secure access, and usage monitoring. It includes infrastructure-as-code templates, CI/CD pipelines, secure access management, usage monitoring, load balancing, streaming requests, and end-to-end samples like ChatApp and Azure Dashboards.

AzureOpenAI-with-APIM is a repository that provides a one-button deploy solution for Azure API Management (APIM), Key Vault, and Log Analytics to work seamlessly with Azure OpenAI endpoints. It enables organizations to scale and manage their Azure OpenAI service efficiently by issuing subscription keys via APIM, delivering usage metrics, and implementing policies for access control and cost management. The repository offers detailed guidance on implementing APIM to enhance Azure OpenAI resiliency, scalability, performance, monitoring, and chargeback capabilities.

This repository provides a deployment guide for utilizing Google Cloud's Generative AI tools in marketing scenarios. It includes step-by-step instructions, examples of crafting marketing materials, and supplementary Jupyter notebooks. The demos cover marketing insights, audience analysis, trendspotting, content search, content generation, and workspace integration. Users can access and visualize marketing data, analyze trends, improve search experience, and generate compelling content. The repository structure includes backend APIs, frontend code, sample notebooks, templates, and installation scripts.

This repository does not provide a tool, but rather a collection of resources and strategies for academics in the field of artificial intelligence who are feeling depressed or overwhelmed by the rapid advancements in the field. The resources include articles, blog posts, and other materials that offer advice on how to cope with the challenges of working in a fast-paced and competitive environment.

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

This repository is a curated list of open-source libraries for production large language models. It includes tools for data preprocessing, training/finetuning, evaluation/benchmarking, serving/inference, application/RAG, testing/monitoring, and guardrails/security. The repository also provides a new category called LLM Cookbook/Examples for showcasing examples and guides on using various LLM APIs.

The LLM course is divided into three parts: 1. 🧩 **LLM Fundamentals** covers essential knowledge about mathematics, Python, and neural networks. 2. 🧑‍🔬 **The LLM Scientist** focuses on building the best possible LLMs using the latest techniques. 3. 👷 **The LLM Engineer** focuses on creating LLM-based applications and deploying them. For an interactive version of this course, I created two **LLM assistants** that will answer questions and test your knowledge in a personalized way: * 🤗 **HuggingChat Assistant**: Free version using Mixtral-8x7B. * 🤖 **ChatGPT Assistant**: Requires a premium account. ## 📝 Notebooks A list of notebooks and articles related to large language models. ### Tools | Notebook | Description | Notebook | |----------|-------------|----------| | 🧐 LLM AutoEval | Automatically evaluate your LLMs using RunPod |  | | 🥱 LazyMergekit | Easily merge models using MergeKit in one click. |  | | 🦎 LazyAxolotl | Fine-tune models in the cloud using Axolotl in one click. |  | | ⚡ AutoQuant | Quantize LLMs in GGUF, GPTQ, EXL2, AWQ, and HQQ formats in one click. |  | | 🌳 Model Family Tree | Visualize the family tree of merged models. |  | | 🚀 ZeroSpace | Automatically create a Gradio chat interface using a free ZeroGPU. |  |

The Amazon Transcribe Live Call Analytics (LCA) with Agent Assist Sample Solution is designed to help contact centers assess and optimize caller experiences in real time. It leverages Amazon machine learning services like Amazon Transcribe, Amazon Comprehend, and Amazon SageMaker to transcribe and extract insights from contact center audio. The solution provides real-time supervisor and agent assist features, integrates with existing contact centers, and offers a scalable, cost-effective approach to improve customer interactions. The end-to-end architecture includes features like live call transcription, call summarization, AI-powered agent assistance, and real-time analytics. The solution is event-driven, ensuring low latency and seamless processing flow from ingested speech to live webpage updates.

The AI-Gateway repository explores the AI Gateway pattern through a series of experimental labs, focusing on Azure API Management for handling AI services APIs. The labs provide step-by-step instructions using Jupyter notebooks with Python scripts, Bicep files, and APIM policies. The goal is to accelerate experimentation of advanced use cases and pave the way for further innovation in the rapidly evolving field of AI. The repository also includes a Mock Server to mimic the behavior of the OpenAI API for testing and development purposes.

The Enterprise Azure OpenAI Hub is a comprehensive repository designed to guide users through the world of Generative AI on the Azure platform. It offers a structured learning experience to accelerate the transition from concept to production in an Enterprise context. The hub empowers users to explore various use cases with Azure services, ensuring security and compliance. It provides real-world examples and playbooks for practical insights into solving complex problems and developing cutting-edge AI solutions. The repository also serves as a library of proven patterns, aligning with industry standards and promoting best practices for secure and compliant AI development.

The Artificial Intelligence Controller Interface (AICI) lets you build Controllers that constrain and direct output of a Large Language Model (LLM) in real time. Controllers are flexible programs capable of implementing constrained decoding, dynamic editing of prompts and generated text, and coordinating execution across multiple, parallel generations. Controllers incorporate custom logic during the token-by-token decoding and maintain state during an LLM request. This allows diverse Controller strategies, from programmatic or query-based decoding to multi-agent conversations to execute efficiently in tight integration with the LLM itself.

Open Data QnA is a Python library that allows users to interact with their PostgreSQL or BigQuery databases in a conversational manner, without needing to write SQL queries. The library leverages Large Language Models (LLMs) to bridge the gap between human language and database queries, enabling users to ask questions in natural language and receive informative responses. It offers features such as conversational querying with multiturn support, table grouping, multi schema/dataset support, SQL generation, query refinement, natural language responses, visualizations, and extensibility. The library is built on a modular design and supports various components like Database Connectors, Vector Stores, and Agents for SQL generation, validation, debugging, descriptions, embeddings, responses, and visualizations.

This sample shows how to build a serverless chat experience with Retrieval-Augmented Generation using LangChain.js and Azure. The application is hosted on Azure Static Web Apps and Azure Functions, with Azure Cosmos DB for MongoDB vCore as the vector database. You can use it as a starting point for building more complex AI applications.

llama.cpp is a C++ implementation of LLaMA, a large language model from Meta. It provides a command-line interface for inference and can be used for a variety of tasks, including text generation, translation, and question answering. llama.cpp is highly optimized for performance and can be run on a variety of hardware, including CPUs, GPUs, and TPUs.

SGLang is a structured generation language designed for large language models (LLMs). It makes your interaction with LLMs faster and more controllable by co-designing the frontend language and the runtime system. The core features of SGLang include: - **A Flexible Front-End Language**: This allows for easy programming of LLM applications with multiple chained generation calls, advanced prompting techniques, control flow, multiple modalities, parallelism, and external interaction. - **A High-Performance Runtime with RadixAttention**: This feature significantly accelerates the execution of complex LLM programs by automatic KV cache reuse across multiple calls. It also supports other common techniques like continuous batching and tensor parallelism.

I'm an always-on-call cloud expert, specializing in solving GCP problems.

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Identifies API keys in text and provides service details and usage instructions.

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Orientações e directrizes no domínio da regulamentação nacional e da UE e regulação das comunicações electrónicas móveis e fixas (e infraestruturas associadas) e serviços digitais (incluindo cloud, IA, metaverso ou IoT)

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