Aquin

Creating safe artificial general intelligence that benefits all of humanity. Our work to create safe and beneficial AI requires a deep understanding of the potential risks and benefits, as well as careful consideration of the impact.

A fully-managed service that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale.

Azure Machine Learning is a fully-managed cloud service that enables data scientists and developers to efficiently embed predictive analytics into their applications, helping organizations use massive data sets and bring all the benefits of the cloud to machine learning.

It is a next-generation AI assistant. It is accessible through chat interface and API. It is capable of a wide variety of conversational and text-processing tasks while maintaining a high degree of reliability and predictability.

This new AWS service helps you to use all of that data you’ve been collecting to improve the quality of your decisions. You can build and fine-tune predictive models using large amounts of data, and then use Amazon Machine Learning to make predictions (in batch mode or in real-time) at scale. You can benefit from machine learning even if you don’t have an advanced degree in statistics or the desire to setup, run, and maintain your own processing and storage infrastructure.

It is Google’s largest and most capable AI model. It is built to be multimodal, it can generalize, understand, operate across, and combine different types of info — like text, images, audio, video, and code.

It is a state-of-the-art foundational large language model designed to help researchers advance their work in this subfield of AI.

It is a large multimodal model (accepting text inputs and emitting text outputs today, with image inputs coming in the future) that can solve difficult problems with greater accuracy than any of our previous models, thanks to its broader general knowledge and advanced reasoning capabilities.

It lets you run machine learning models with a few lines of code, without needing to understand how machine learning works.

Makes it easy for machine learning developers, data scientists, and data engineers to take their ML projects from ideation to production and deployment, quickly and cost-effectively.

Build And Run Predictive Applications For Streaming Data From Applications, Devices, Machines and Wearables

Amazon Elastic Inference allows you to attach low-cost GPU-powered acceleration to Amazon EC2 and Amazon SageMaker instances to reduce the cost of running deep learning inference by up to 75%. Amazon Elastic Inference supports TensorFlow, Apache MXNet, and ONNX models, with more frameworks coming soon.

It offers an API to add cutting-edge language processing to any system. Through training, users can create massive models customized to their use case and trained on their data.

It is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multi-task model that can perform multilingual speech recognition as well as speech translation and language identification.

It is a small, yet powerful model adaptable to many use cases. It is better than Llama 2 13B on all benchmarks, has natural coding abilities, and 8k sequence length. We made it easy to deploy on any cloud.

Machine learning service that makes it easy for developers to add individualized recommendations to customers using their applications.

Build a custom machine learning model without expertise or large amount of data. Just go to nanonets, upload images, wait for few minutes and integrate nanonets API to your application.

It lets you run or deploy machine learning models, massively parallel compute jobs, task queues, web apps, and much more, without your own infrastructure.

It is an advanced language model comprising 67 billion parameters. It has been trained from scratch on a vast dataset of 2 trillion tokens in both English and Chinese.

BigML provides a hosted machine learning platform for advanced analytics. Through BigML's intuitive interface and/or its open API and bindings in several languages, analysts, data scientists and developers alike can quickly build fully actionable predictive models and clusters that can easily be incorporated into related applications and services.

It is composed of a series of code language models, each trained from scratch on 2T tokens, with a composition of 87% code and 13% natural language. There are various sizes of the code model, ranging from 1B to 33B versions.

Firebase Predictions uses the power of Google’s machine learning to create dynamic user groups based on users’ predicted behavior.

Machine learners share, stress test, and stay up-to-date on all the latest ML techniques and technologies. Discover a huge repository of community-published models, data & code for your next project.

Platform-as-a-Service for training and deploying your DL models in the cloud. Start running your first project in < 30 sec! Floyd takes care of the grunt work so you can focus on the core of your problem.

Building an intelligent, predictive application involves iterating over multiple steps: cleaning the data, developing features, training a model, and creating and maintaining a predictive service. GraphLab Create does all of this in one platform. It is easy to use, fast, and powerful.

It is the base model weights and network architecture of Grok-1, the large language model. Grok-1 is a 314 billion parameter Mixture-of-Experts model trained from scratch by xAI.

It is the machine learning platform for developers to build better models faster. Use W&B's lightweight, interoperable tools to quickly track experiments, version and iterate on datasets, evaluate model performance, reproduce models, visualize results and spot regressions, and share findings with colleagues.

It is an open-source library for fast LLM inference and serving. It delivers up to 24x higher throughput than HuggingFace Transformers, without requiring any model architecture changes.

Lamina helps you integrate Deep Learning models like Sentiment Analysis and Entity Extraction into your products with a simple API call. Relieving you of getting data, creating a model and training them which would be compute-intensive.

It provides all you need to build and deploy computer vision models, from data annotation and organization tools to scalable deployment solutions that work across devices.

It is a Recommender as a Service with easy integration and powerful Admin UI. The Recombee recommendation engine can be applied to any domain that has a catalog of items and is interacted by a large number of users. Applicable to web and mobile apps, It improves user experience by showing the most relevant content for individual users.

It is an autoregressive Large Language Model (LLM), trained to continue text from a prompt on vast amounts of text data using industrial-scale computational resources. It is able to generate text in 46 natural languages and 13 programming languages.

It is a state-of-the-art LLM capable of generating code, and natural language about code, from both code and natural language prompts. It is built on top of Llama 2 and is available for free.

It is a set of models that improve on GPT-3 and can understand as well as generate natural language or code.

Gradient° is a suite of tools for exploring data and training neural networks. Gradient° includes 1-click Jupyter notebooks, a powerful job runner, and a python module to run any code on a fully managed GPU cluster in the cloud. Gradient is also rolling out full support for Google's new TPUv2 accelerator to power even more newer workflows.

It is a high-performance cloud computing and ML development platform for building, training and deploying machine learning models. Tens of thousands of individuals, startups and enterprises use it to iterate faster and collaborate on intelligent, real-time prediction engines.

Try Grok 4 on GPT Proto. Access xAI’s most advanced 1.7T LLM with 130K context, multimodal support, and real-time data integration for dynamic analysis.

Delight your users with personalised content recommendations. It's easy to set up and works with or without collaborative data. The Lateral API is trained on 10s of millions of high quality documents from law, academia and journalism. It can understand any document and provide intelligent recommendations.

Dasha is a conversational AI as a Service platform. Dasha lets you create conversational apps that are more human-like than ever before, quicker than ever before and quickly integrate them into your products.

It is the easiest way to deploy Machine Learning models. Start deploying Tensorflow, Scikit, Keras and spaCy straight from your notebook with just one extra line.

It is a machine learning profiler. It helps data scientists and ML engineers make model training and inference faster and more efficient.

It is a development environment and hosting solution for machine learning models. No servers to manage, no configuration, no headaches. It just works. It is the fastest way to add production-ready ML into an app.

It is a collection of open-source models for generating various types of media.

It is a robust & flexible API to build unique product recommendations into any digital ecommerce experience. Developers can use a simple and flexible API to build machine learning powered recommendations on your company’s digital storefronts using as few as 6 lines of code, driving better conversions and increasing average order value. It comes with advanced flexibility so you can completely customize the recommendations displayed on your online stores.

It accelerates ML development. It provides an instant infrastructure for your ML projects. You can think of it as the Heroku of MLOps or the AWS lambda functions for ML, all powered by GPUs.

Wise.io builds machine intelligence products that make it easy for companies to derive actionable insight from their greatest corporate resource: their data.

It is an open-source language model. It is trained with 1.5 trillion tokens of content. The richness of dataset gives StableLM surprisingly high performance in conversational and coding tasks.

Enhance your photos with our AI Photo Enhancer. Restore colors, sharpen details, remove noise, and upscale low-resolution images to stunning 4K quality.

It is a platform that makes it really easy to build, track and deploy models. It is deployed on a cluster on your own cloud so that the data never leaves your environment and you don't incur any data egress costs.

It is a fully-managed, cloud native feature platform that operates and manages the pipelines that transform raw data into features across the full lifecycle of an ML application.