Best Free AI Websites You Need to Know

Introduction

Artificial intelligence (AI) refers to computer systems and machines that are designed to perform tasks that would normally require human intelligence. AI encompasses a wide range of technologies like machine learning, deep learning, computer vision, natural language processing, robotics, and more.

In recent years, major tech companies have made great strides in AI research and development. Many of them are now offering free access to some of their AI tools and services for consumers and businesses to benefit from the latest advancements in the field.

Free AI tools can help individuals and organizations in many ways. For consumers, they provide easy access to powerful AI capabilities like image and text recognition, language translation, speech synthesis, predictive text generation, and more. Businesses can leverage free AI services to quickly prototype and build AI solutions for tasks like customer service chatbots, product recommendations, forecasting, and predictive analytics.

The availability of free AI services lowers the barriers to experimenting with and adopting AI. You no longer need an extensive AI/machine learning background or have to invest in hiring data scientists. With just some basic coding skills, anyone can start exploring AI and experiencing its possibilities first-hand through free online services.

Free access allows wider audiences to educate themselves about AI and its potential benefits and risks. It promotes open innovation, allowing creators, researchers, and entrepreneurs to test AI capabilities at negligible cost. Over time, this can accelerate practical AI applications that provide value to people and progress the field.

So whether you’re a casual user, developer, researcher, or business leader, leveraging free AI tools and services can open up new possibilities. This article explores the top websites providing free access to the latest AI technologies.

Google AI Services

Google offers a suite of powerful artificial intelligence services through its Google Cloud Platform. These tools make it easy for developers to build AI into their applications without needing extensive machine learning expertise.

Some of Google’s most popular AI services include:

• Cloud AI Platform – This managed service simplifies the process of training, deploying and managing machine learning models. It supports popular frameworks like TensorFlow, PyTorch, scikit-learn, XGBoost and Keras. The platform provides GPUs and TPUs to accelerate training.
• Vision API – This image recognition tool can detect objects, faces, logos and landmarks. It can also read printed and handwritten text. The Vision API makes it easy to integrate vision detection into apps.
• Natural Language API – This service analyzes text and provides information like sentiment analysis, entity analysis and content classification. It can be used to understand user input in chatbots and search applications.
• Speech-to-Text – Google’s speech recognition service can transcribe spoken audio into text in over 120 languages. It works offline and in real-time.
• Translate API – The translation API can dynamically translate text between thousands of language pairs. It also provides language detection capabilities.
• Dialogflow – This developer framework makes it easy to design and integrate conversational user interfaces like chatbots. It provides natural language understanding and response suggestion capabilities.

Google offers developer-friendly SDKs and client libraries to call these AI services from various programming languages and platforms. Most services offer a free tier and usage-based pricing.

Microsoft Azure AI services

Microsoft Azure provides a comprehensive set of AI services and capabilities to help developers and businesses solve real-world problems. Some of the key Azure AI services include:

• Azure Bot Service – Allows developers to build intelligent conversational bots using Microsoft tools like Bot Framework. Bots can understand natural language, have dialogs, access external data and services, and much more. Useful for customer service, notifications, guidance, and transactions.
• Azure Cognitive Services – A collection of pre-built AI algorithms and models to provide capabilities like vision, speech, language, search, and knowledge. For example, Computer Vision for analyzing images, Text Analytics for processing text, and Anomaly Detector for detecting abnormalities. Easy to add intelligence via REST APIs.
• Azure Machine Learning – An enterprise-grade machine learning platform to build, train, deploy, manage, and track ML models. Supports popular frameworks like PyTorch, TensorFlow, scikit-learn, ONNX, and more. Includes automated ML, model management, and ML pipelines.
• Azure Cognitive Search – Fully-managed search service with built-in AI to add robust search capabilities. Includes abilities like natural language queries, fuzzy matching, contextual understanding, and knowledge mining. Useful for search-centric apps and portals.
• Azure Bot Framework Composer – Sophisticated no-code tool to build, train, test, deploy, and manage intelligent bots visually with minimal coding. Great for quickly creating virtual agents and assistants.

There are also niche services like Form Recognizer for automating data extraction from forms and documents using machine learning. Microsoft is rapidly expanding Azure’s AI capabilities to democratize AI and make it accessible to every developer and organization.

Amazon AI Services

Amazon offers a suite of AI services that enable developers to easily add intelligence to applications. Some of the key services include:

• Amazon Lex – Lets developers build conversational interfaces into applications using the same technology that powers Alexa. It provides automatic speech recognition (ASR) for converting speech to text and natural language understanding (NLU) to recognize intents.
• Amazon Polly – Turns text into lifelike speech using advanced deep learning technologies. Developers can create applications that speak to users naturally.
• Amazon Rekognition – Provides analysis of images and videos to recognize objects, people, text, scenes and activities. This can be used to build image and video analysis into apps.
• Amazon Comprehend – A natural language processing (NLP) service that uses machine learning to find insights and relationships in text. It can be used for a range of applications from analyzing customer sentiment to extracting key phrases and entities.
• Amazon Forecast – Uses machine learning to generate highly accurate time-series forecasts based on historical data. This allows developers to add forecasts to their applications.
• Amazon SageMaker – A fully managed service that enables developers and data scientists to quickly build, train, and deploy machine learning models at scale. It removes the heavy lifting from each step of the machine learning process.

Amazon’s AI services provide pre-trained capabilities that can be easily integrated into applications without requiring machine learning expertise. The pay-as-you-go pricing model allows these capabilities to be added without any upfront costs.

IBM Watson AI services

IBM Watson offers some of the most robust and advanced AI services available to developers for free. Some key Watson AI services to highlight:

• Watson Discovery – This service provides intelligent search and analytics through natural language processing and machine learning. It can understand unstructured data like documents, articles, labels, questions etc. You can use it to build chatbots, virtual agents and find insights from data.
• Watson Visual Recognition – This image and video analysis service can tag, classify and detect objects, faces and text in images/videos through deep learning models. Useful for moderation, cataloging, pattern detection and more.
• Watson Assistant – Build conversational interfaces like chatbots with this service. It provides natural language processing and ML to understand conversations and respond intelligently.
• Watson Language Translator – Quickly translate text, documents and speech into different languages. Supports over 25 languages and dialects.
• Watson Speech to Text – Convert audio and voice into written text quickly and accurately. Useful for transcription and taking audio meeting notes.
• Watson Text to Speech – Convert written text into natural sounding audio in different languages and voices. Great for building voice interfaces and apps.

IBM provides free tier access to these and other Watson services through IBM Cloud with limited usage per month. Beyond that, paid plans are available based on usage. Overall, Watson AI provides enterprise-grade AI capabilities for developers for free.

Facebook AI Tools

Facebook has developed and open sourced several useful AI tools and resources that are available for free. Some of the key offerings include:

• PyTorch – A popular open source machine learning framework based on the Torch library. It offers flexible tensor computation and dynamic neural networks. Facebook uses PyTorch for its AI research and production.
• Detectron – A powerful computer vision codebase for object detection, segmentation and other visual recognition tasks. It is written in Python and powered by the Caffe2 deep learning framework.
• Spectrum – A decentralized platform for AI model training and deployment. It helps coordinate distributed workers for data labeling, model training, and more.
• PyText – A natural language processing framework focused on prodcutizing deep learning models. It aims to help deploy NLP models to real-world applications.
• CommerceAI – A framework to help developers build conversational interfaces for ecommerce. It provides intent recognition and slot filling to enable natural chat experiences.
• ReAgent – A platform for building reinforcement learning agents using PyTorch. It provides building blocks to help train and deploy RL algorithms.
• ParlAI – A dialog research ecosystem that provides a large suite of dialog datasets, models and model training tools. It aims to enable dialog AI research.

Overall, Facebook open sources many of its internal AI research projects. Developers can leverage these tools to more easily build models for computer vision, NLP, recommendation systems, dialog systems and more. The open source nature promotes experimentation and contribution from the wider AI community.

OpenAI Models and API

OpenAI offers free access to some of their state-of-the-art AI models through their API. The most well-known is GPT-3, their large language model that can generate human-like text.

While access to the full GPT-3 model requires approval, OpenAI provides a free playground where you can experiment with different sized versions of GPT-3. The playground lets you enter text prompts and see GPT-3’s responses. It’s an easy way to get a feel for what this advanced AI is capable of.

Another free offering from OpenAI is Codex, which can generate code in multiple languages from natural language prompts. There’s a playground for Codex as well to try it out. Codex is trained on billions of lines of public code so it can suggest entire functions or classes when given a comment describing what you want to achieve.

Beyond the playgrounds, OpenAI offers limited free access to the GPT-3 and Codex models through their API. You need to sign up for an account to get an API key. The free tier has usage limits but allows you to incorporate these models into your own applications and websites.

Overall, OpenAI’s free offerings like the playgrounds and API give everyone access to test and build with cutting-edge AI, even if you can’t afford the paid tier. It’s an exciting way to get hands-on experience with models like GPT-3 that showcase the possibilities of large language models.

Hugging Face Models

Hugging Face is an AI community best known for its open source repository of pretrained models called Transformers. The repository contains implementations of cutting-edge NLP architectures like BERT, GPT-2, T5, and more.

With over 18,000 models available, the Hugging Face hub makes it easy for anyone to leverage state-of-the-art AI. You can fine-tune models for your own applications or use them for inference through Hugging Face’s APIs.

Some highlights of Hugging Face models:

• Natural language processing models for text classification, question answering, summarization, translation, text generation and more.
• Speech recognition and audio classification models.
• Vision models for image classification, object detection and segmentation.

The models are open source and freely usable for any purpose under their original licenses. Hugging Face provides model cards with details on performance metrics to help you select the right architecture.

With just a few lines of code, you can load and use models like BERT and GPT-2. Fine-tuning is also straightforward by adding task-specific layers. The Transformers library handles much of the complexity behind the scenes.

Overall, Hugging Face provides an immense collection of SOTA models to deploy in your own projects and products. Their commitment to open source AI lowers barriers for accessing advanced models.

Conclusion

The free AI services offered by major tech companies provide tremendous value for developers, researchers, and anyone looking to experiment with AI.

Google Cloud’s AI services give access to pre-trained models for vision, language, conversation, and structured data. This allows for quickly adding AI capabilities to applications without needing to develop custom models. Microsoft Azure Cognitive Services make it easy to embed vision, speech, language, search, and knowledge capabilities into software. Amazon SageMaker helps build, train, and deploy ML models with fully managed infrastructure.

IBM Watson’s suite of AI services allows building various intelligent applications powered by machine learning. Facebook provides frameworks for computer vision and natural language processing to advance AI research. OpenAI and Hugging Face offer models and APIs to generate text, summarize, classify, and more.

Overall these free services lower the barriers to get started with AI by providing access to state-of-the-art models. Developers and researchers can leverage them to prototype and validate ideas faster. While the free tiers have usage limits, they enable exploring AI capabilities at no cost. For many needs, the free options will suffice without having to pay. With powerful AI available freely, the potential to innovate and create intelligent applications is now open to all.

Further Resources

There are many other great free AI resources available beyond the main providers listed in this article. Here are some additional options to check out:

• Datasets: Kaggle, UC Irvine Machine Learning Repository, Google Dataset Search
• Code Libraries: PyTorch, TensorFlow, Keras, Scikit-Learn, OpenCV
• Computing Resources: Google Colab, Kaggle Notebooks, Gradient
• Research Labs: OpenAI, DeepMind, FAIR, Allen Institute for AI
• Education: Fast.ai courses, Analytics Vidhya, CS231N Convolutional Neural Networks for Visual Recognition
• Development Tools: Hugging Face, Streamlit, Gradio
• Pre-trained Models: Hugging Face Hub, TensorFlow Hub, ONNX Model Zoo
• Research Papers: arXiv.org, Papers With Code
• Conferences: NeurIPS, ICML, ICLR, CVPR
• Communities: Reddit’s r/MachineLearning, AI Stack Exchange, Hacker News

There are new exciting resources popping up all the time in AI. Make sure to keep exploring, learning and building! The world of AI is advancing rapidly with many free tools to leverage.

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