OpenLIT Integrations

Fully managed ML tools allow you to build, deploy and scale machine-learning (ML) models quickly, for any use case. Vertex AI Workbench is natively integrated with BigQuery Dataproc and Spark. You can use BigQuery to create and execute machine-learning models in BigQuery by using standard SQL queries and spreadsheets or you can export datasets directly from BigQuery into Vertex AI Workbench to run your models there. Vertex Data Labeling can be used to create highly accurate labels for data collection.

The most versatile and realistic AI speech software ever. Eleven delivers the most convincing, rich and authentic voices to creators and publishers looking for the ultimate tools for storytelling. The most versatile and versatile AI speech tool available allows you to produce high-quality spoken audio in any style and voice. Our deep learning model can detect human intonation and inflections and adjust delivery based upon context. Our AI model is designed to understand the logic and emotions behind words. Instead of generating sentences one-by-1, the AI model is always aware of how each utterance links to preceding or succeeding text. This zoomed-out perspective allows it a more convincing and purposeful way to intone longer fragments. Finally, you can do it with any voice you like.

OpenAI's mission, which is to ensure artificial general intelligence (AGI), benefits all people. This refers to highly autonomous systems that outperform humans in most economically valuable work. While we will try to build safe and useful AGI, we will also consider our mission accomplished if others are able to do the same. Our API can be used to perform any language task, including summarization, sentiment analysis and content generation. You can specify your task in English or use a few examples. Our constantly improving AI technology is available to you with a simple integration. These sample completions will show you how to integrate with the API.

Claude is an artificial intelligence language model that can generate text with human-like processing. Anthropic is an AI safety company and research firm that focuses on building reliable, interpretable and steerable AI systems. While large, general systems can provide significant benefits, they can also be unpredictable, unreliable and opaque. Our goal is to make progress in these areas. We are currently focusing on research to achieve these goals. However, we see many opportunities for our work in the future to create value both commercially and for the public good.

Datadog is the cloud-age monitoring, security, and analytics platform for developers, IT operation teams, security engineers, and business users. Our SaaS platform integrates monitoring of infrastructure, application performance monitoring, and log management to provide unified and real-time monitoring of all our customers' technology stacks. Datadog is used by companies of all sizes and in many industries to enable digital transformation, cloud migration, collaboration among development, operations and security teams, accelerate time-to-market for applications, reduce the time it takes to solve problems, secure applications and infrastructure and understand user behavior to track key business metrics.

Docker eliminates repetitive, tedious configuration tasks and is used throughout development lifecycle for easy, portable, desktop, and cloud application development. Docker's complete end-to-end platform, which includes UIs CLIs, APIs, and security, is designed to work together throughout the entire application delivery cycle. Docker images can be used to quickly create your own applications on Windows or Mac. Create your multi-container application using Docker Compose. Docker can be integrated with your favorite tools in your development pipeline. Docker is compatible with all development tools, including GitHub, CircleCI, and VS Code. To run applications in any environment, package them as portable containers images. Use Docker Trusted Content to get Docker Official Images, images from Docker Verified Publishings, and more.

ChatGPT is an OpenAI language model. It can generate human-like responses to a variety prompts, and has been trained on a wide range of internet texts. ChatGPT can be used to perform natural language processing tasks such as conversation, question answering, and text generation. ChatGPT is a pretrained language model that uses deep-learning algorithms to generate text. It was trained using large amounts of text data. This allows it to respond to a wide variety of prompts with human-like ease. It has a transformer architecture that has been proven to be efficient in many NLP tasks. ChatGPT can generate text in addition to answering questions, text classification and language translation. This allows developers to create powerful NLP applications that can do specific tasks more accurately. ChatGPT can also process code and generate it.

With just a few lines, you can integrate natural language understanding and generation into the product. The Cohere API allows you to access models that can read billions upon billions of pages and learn the meaning, sentiment, intent, and intent of every word we use. You can use the Cohere API for human-like text. Simply fill in a prompt or complete blanks. You can create code, write copy, summarize text, and much more. Calculate the likelihood of text, and retrieve representations from your model. You can filter text using the likelihood API based on selected criteria or categories. You can create your own downstream models for a variety of domain-specific natural languages tasks by using representations. The Cohere API is able to compute the similarity of pieces of text and make categorical predictions based on the likelihood of different text options. The model can see ideas through multiple lenses so it can identify abstract similarities between concepts as distinct from DNA and computers.

Our digital cards have been used to support over 8 million people in 60+ countries. They improve sales efficiency, increase quality connections, and reduce your carbon footprint. Post COVID19, handshakes and business cards made of paper are no longer acceptable. Your staff can now share contact-free digital business cards with their clients and prospects when they meet in person, via Zoom, Teams, or teleconferences. Your staff can take a picture of the cards they receive without touching them. This reduces health risks for your employees and sales team. Digital means that you can track your card and share it with others in seconds. This will leave a lasting impression on everyone you meet. Haystack is a smart marketing tool that drives traffic to your website, social networks, and key company links. You can personalize your company template with images, whitepaper links, and industry reports.

AutoTrain is a new way to automatically evaluate, deploy and train state-of-the art Machine Learning models. AutoTrain, seamlessly integrated into the Hugging Face ecosystem, is an automated way to develop and deploy state of-the-art Machine Learning model. Your account is protected from all data, including your training data. All data transfers are encrypted. Today's options include text classification, text scoring and entity recognition. Files in CSV, TSV, or JSON can be hosted anywhere. After training is completed, we delete all training data. Hugging Face also has an AI-generated content detection tool.

It is now easier than ever to create services with Go thanks to the strong ecosystem of APIs and tools available on major cloud providers. Go allows you to create elegant and fast CLIs using popular open-source packages and a robust standard repository. Go powers fast, scalable web applications thanks to its enhanced memory performance and support of several IDEs. Go supports both DevOps as well as SRE with its fast build times and lean syntax. All you need to know about Go. Get started on a project or refresh your knowledge about Go code. Three sections provide an interactive introduction to Go. Each section ends with a few exercises that allow you to put what you have learned into practice. Anyone can use a web browser to create Go code that we instantly compile, link, then run on our servers.

GPT4All provides an ecosystem for training and deploying large language models, which run locally on consumer CPUs. The goal is to be the best assistant-style language models that anyone or any enterprise can freely use and distribute. A GPT4All is a 3GB to 8GB file you can download and plug in the GPT4All ecosystem software. Nomic AI maintains and supports this software ecosystem in order to enforce quality and safety, and to enable any person or company to easily train and deploy large language models on the edge. Data is a key ingredient in building a powerful and general-purpose large-language model. The GPT4All Community has created the GPT4All Open Source Data Lake as a staging area for contributing instruction and assistance tuning data for future GPT4All Model Trains.

Meta AI is our intelligent assistant that allows people to create, connect and get things done. We've integrated Llama 3. Meta AI can be used to code and solve problems, allowing you to see the performance of Llama 3. Llama 3, in 8B or 70B, will give you the flexibility and capabilities you need to create your ideas, whether you're creating AI-powered agents or other applications. We've updated our Responsible Use Guide (RUG), to provide the most comprehensive and up-to-date information on responsible development using LLMs. Our system-centric approach includes updates for our trust and security tools, including Llama Guard 2 optimized to support MLCommons' newly announced taxonomy, code shield and Cybersec Evaluation 2.

Terraform is an open source infrastructure as code software tool. It provides a consistent CLI workflow for managing hundreds of cloud services. Terraform codifies cloud APIs into declarative configuration files. Write infrastructure as code using declarative configuration files. The HashiCorp Configuration Language allows for concise descriptions using blocks, arguments and expressions of resources. Run terraform plan before you provision or change infrastructure. To achieve the desired configuration state, apply changes to hundreds cloud providers using terraform. To manage the entire lifecycle of infrastructure, define it as code. Create new resources, manage existing ones, destroy those that are no longer needed.

Open-source monitoring solutions are able to power your alerting and metrics. Prometheus stores all data in time series. These are streams of timestamped value belonging to the same metric with the same labeled dimensions. Prometheus can also generate temporary derived times series as a result of queries. Prometheus offers a functional query language called PromQL, which allows the user to select and aggregate time series data real-time. The expression result can be displayed as a graph or tabular data in Prometheus’s expression browser. External systems can also consume the HTTP API. Prometheus can be configured using command-line flags or a configuration file. The command-line flags can be used to configure immutable system parameters such as storage locations and the amount of data to be kept on disk and in memory. . Download: https://sourceforge.net/projects/prometheus.mirror/

We are an intelligent HelpDesk. We will optimize your management processes, increase productivity of your team, and increase the efficiency in your support. Your customers will have more options by opening tickets from different devices. You have more control over how you configure your customers' SLA. The inventory management app can be used to monitor and control the entire equipment park of customers. You can increase the productivity of your technical support staff with intelligent and automated inventory management. Optimize your customer relationship and management! Receive alerts about key machine features via your dashboard. Automation, workflow and ticket triggers. Password Vault, satisfaction survey and ticket scheduling. Follow customer, service catalog, follow tickets, ticket conference, advanced dashboard.

The NVIDIA GPU Optimized AMI is a virtual image that accelerates your GPU-accelerated Machine Learning and Deep Learning workloads. This AMI allows you to spin up a GPU accelerated EC2 VM in minutes, with a preinstalled Ubuntu OS and GPU driver. Docker, NVIDIA container toolkit, and Docker are also included. This AMI provides access to NVIDIA’s NGC Catalog. It is a hub of GPU-optimized software for pulling and running performance-tuned docker containers that have been tested and certified by NVIDIA. The NGC Catalog provides free access to containerized AI and HPC applications. It also includes pre-trained AI models, AI SDKs, and other resources. This GPU-optimized AMI comes free, but you can purchase enterprise support through NVIDIA Enterprise. Scroll down to the 'Support information' section to find out how to get support for AMI.

You can use advanced language models and coding to solve a variety of problems. To build cutting-edge applications, leverage large-scale, generative AI models that have deep understandings of code and language to allow for new reasoning and comprehension. These coding and language models can be applied to a variety use cases, including writing assistance, code generation, reasoning over data, and code generation. Access enterprise-grade Azure security and detect and mitigate harmful use. Access generative models that have been pretrained with trillions upon trillions of words. You can use them to create new scenarios, including code, reasoning, inferencing and comprehension. A simple REST API allows you to customize generative models with labeled information for your particular scenario. To improve the accuracy of your outputs, fine-tune the hyperparameters of your model. You can use the API's few-shot learning capability for more relevant results and to provide examples.

The AI Knowledge Platform. The Pinecone Database, Inference, and Assistant make building high-performance vector search apps easy. Fully managed and developer-friendly, the database is easily scalable without any infrastructure problems. Once you have vector embeddings created, you can search and manage them in Pinecone to power semantic searches, recommenders, or other applications that rely upon relevant information retrieval. Even with billions of items, ultra-low query latency Provide a great user experience. You can add, edit, and delete data via live index updates. Your data is available immediately. For more relevant and quicker results, combine vector search with metadata filters. Our API makes it easy to launch, use, scale, and scale your vector searching service without worrying about infrastructure. It will run smoothly and securely.

Start using large language models in your locality.

Qdrant is a vector database and similarity engine. It is an API service that allows you to search for the closest high-dimensional vectors. Qdrant allows embeddings and neural network encoders to be transformed into full-fledged apps for matching, searching, recommending, etc. This specification provides the OpenAPI version 3 specification to create a client library for almost any programming language. You can also use a ready-made client for Python, or other programming languages that has additional functionality. For Approximate Nearest Neighbor Search, you can make a custom modification to the HNSW algorithm. Search at a State of the Art speed and use search filters to maximize results. Additional payload can be associated with vectors. Allows you to store payload and filter results based upon payload values.

LlamaIndex, a "dataframework", is designed to help you create LLM apps. Connect semi-structured API data like Slack or Salesforce. LlamaIndex provides a flexible and simple data framework to connect custom data sources with large language models. LlamaIndex is a powerful tool to enhance your LLM applications. Connect your existing data formats and sources (APIs, PDFs, documents, SQL etc.). Use with a large-scale language model application. Store and index data for different uses. Integrate downstream vector stores and database providers. LlamaIndex is a query interface which accepts any input prompts over your data, and returns a knowledge augmented response. Connect unstructured data sources, such as PDFs, raw text files and images. Integrate structured data sources such as Excel, SQL etc. It provides ways to structure data (indices, charts) so that it can be used with LLMs.

We solve the most difficult problems to make AI models efficient, helpful and reliable. We are the pioneers of open models. We give them to our users, and empower them to share their ideas. Mistral-7B is a powerful, small model that can be adapted to many different use-cases. Mistral 7B outperforms Llama 13B in all benchmarks. It has 8k sequence length, natural coding capabilities, and is faster than Llama 2. It is released under Apache 2.0 License and we made it simple to deploy on any cloud.

Enterprise plugins such as Splunk, ServiceNow and Datadog allow you to view all your data in one place. Collaboration features built-in allow teams to collaborate from one dashboard. Advanced security and compliance features ensure that your data remains secure. Access to Prometheus, Grafite, Grafana experts, and hands-on support. Other vendors will try and sell you an "everything is in my database" mentality. Grafana Labs has a different approach. We want to help with your observation, not own it. Grafana Enterprise gives you access to enterprise plugins. These plugins allow you to import your data sources into Grafana. This allows you to visualize all data in a more efficient and effective manner, allowing you to get the most out of expensive and complex monitoring systems.

Foundation models (FMs), the easiest way to create and scale generative AI apps, are available. Amazon Bedrock gives you the freedom to choose from a variety of FMs created by leading AI startups as well as Amazon. This allows you to find the best model for your needs. Bedrock's serverless environment allows you to get started quickly and customize FMs using your own data. You can then integrate and deploy these FMs into your applications with the AWS tools you are already familiar with. Choose FMs from AI21 Labs (Anthropic), Stability AI (Amazon), and Amazon to find FMs that are right for your application.

Groq's mission is to set the standard in GenAI inference speeds, enabling real-time AI applications to be developed today. LPU, or Language Processing Unit, inference engines are a new end-to-end system that can provide the fastest inference possible for computationally intensive applications, including AI language applications. The LPU was designed to overcome two bottlenecks in LLMs: compute density and memory bandwidth. In terms of LLMs, an LPU has a greater computing capacity than both a GPU and a CPU. This reduces the time it takes to calculate each word, allowing text sequences to be generated faster. LPU's inference engine can also deliver orders of magnitude higher performance on LLMs than GPUs by eliminating external memory bottlenecks. Groq supports machine learning frameworks like PyTorch TensorFlow and ONNX.

Software is what transforms a vehicle into a smart machine. Open source software stack NVIDIA DRIVE™, enables developers to quickly build and deploy a variety state-of the-art AV applications. This includes perception, localization, mapping, driver monitoring, planning and control, driver monitoring and natural language processing. DRIVE OS, the foundation of the DRIVE SoftwareStack, is the first secure operating system for accelerated computation. It includes NvMedia to process sensor input, NVIDIACUDA®, libraries for parallel computing implementations that are efficient, NVIDIA TensorRT™ for real time AI inference, as well as other tools and modules for accessing hardware engines. NVIDIA DriveWorks®, a SDK that provides middleware functions over DRIVE OS, is essential for autonomous vehicle development. These include the sensor abstraction layer (SAL), sensor plugins, data recorder and vehicle I/O support.

Telemetry that is portable, ubiquitous, and high-quality to allow effective observation. OpenTelemetry is an open-source collection of APIs and SDKs. It can be used to instrument, generate logs, logs, or traces telemetry data to analyze the performance and behavior of your software. OpenTelemetry can be used in many languages. You can create and collect telemetry data using your software and services, and then forward them to various analysis tools. OpenTelemetry can be integrated with popular frameworks and libraries like ASP.NET Core Express, Quarkus, Spring, and ASP.NET Core. Integration is as easy as writing a few lines. OpenTelemetry is 100% free and open source. It is supported by industry leaders in observability.