Exploring additional AI services

Now that we’ve spent a little bit of time learning about some of the features of Generative AI and Power Platform, let’s look at a few of the AI services currently in the marketplace.

Working with Azure AI Services

Microsoft offers a wide array of AI and machine learning capabilities under the Azure AI Services (formerly Azure Cognitive Services) umbrella. These services enable developers to add intelligent capabilities to their applications without needing to build complex AI algorithms from scratch. With Azure Cognitive Services, developers can tap into pre-built models and application programming interfaces (APIs) to incorporate functionalities such as vision, speech, language, and decision-making into their applications.

The vision-capable services include the following:

• Computer Vision: This service enables image analysis and object detection. Computer Vision can do things such as identify objects in a scene (dog, frisbee, and tree) as well as perform contextual image analysis (There is a dog catching a frisbee by the tree) and optical character recognition.
• Face: The Face service is used to identify the presence of faces in image data, as well as identify and analyze faces in images. You might use the Face service to verify someone’s identity against a government-issued identification card or to blur out face content in a picture or video.
• Custom Vision: The Custom Vision service, now part of Image Analysis 4.0, enables developers to create custom image recognition models for tagging and applying labels to content based on visual characteristics.

Azure Cognitive Services includes several language and speech APIs, which provide the following features:

• Speech: The Speech service provides a broad array of speech-to-text, text-to-speech, content translation, and speaker recognition capabilities.
• Language: This service has several sub-services and capabilities based on natural language understanding, including the ability to perform key phrase extraction, named entity recognition, and the ability to detect personally identifiable information (PII). The Language service can also provide text translation between two languages, classify bodies of text and determine their sentiment, and perform content summarization.
• Translator: While the Language service handles text-to-text content conversion, the Translator service can provide machine-based translation in real time.
• Language Understanding (LUIS): The LUIS service is a machine learning model that can predict overall meaning and content extraction from natural language conversation.
• QnA Maker: You can think of the QnA Maker service as a bot or answering service that can reason over semi-structured content and provide answers to customers.

The decision models that are available alongside Azure AI Services also provide unique capabilities:

• Content Moderator: The Content Moderator service provides analysis for potentially offensive, undesirable, unsafe, or otherwise risky content
• Personalizer: Using behavior and habits analysis, the Personalizer service helps select which content experiences to choose for your customers
• Anomaly Detector: The Anomaly Detector service allows you to monitor and detect inconsistencies in time-based datasets

Azure AI Services also includes the Azure OpenAI service, which has several language models, including GPT-3 and Codex, to support content generation, summarization, and natural language-to-code translation.

Change is a-comin’

If there’s anything constant, it’s change. As the AI landscape evolves, newer features, services, or capabilities replace older counterparts. Over the next few years, you’ll need to say “goodbye” to the LUIS and QnA Maker services, as they’ll be retired. Microsoft recommends transitioning LUIS-enabled applications and services to Conversational Language Understanding and retooling services by using QnA Maker with the question-and-answer capability in the Azure AI Language service.

Together, this family of services provides developers with the mechanisms to programmatically add AI-based capabilities to their applications without having lots of experience in AI modeling, improving user experiences, and driving innovation in areas such as healthcare and customer service.

Further reading

For more information on the complete lineup of Azure Cognitive Services, go to https://learn.microsoft.com/en-us/azure/cognitive-services/what-are-cognitive-services.

Working with OpenAI models

OpenAI is the organization behind popular models such as GPT-3, GPT-4, and the DALL-E image generation platform.

OpenAI offers a range of advanced AI technologies and services that aim to empower individuals and organizations to leverage the power of AI. Let’s look at some of their offerings:

• Generative Pre-trained Transformer (GPT): This is OpenAI’s flagship language model. It can generate coherent and contextually relevant text, making it useful for tasks such as natural language processing, text completion, and chatbot development.
• OpenAI API: This offering provides developers with easy access to OpenAI’s models, enabling them to integrate language generation capabilities into their applications or services.
• Images API: The Images API provides methods for creating or editing new and existing images based on text prompts.
• OpenAI Gym: This is a toolkit for developing and comparing reinforcement learning algorithms. It provides a wide range of pre-built environments and tools to train and evaluate AI agents.
• OpenAI Platform: OpenAI Platform offers a suite of tools and resources for researching, developing, and deploying AI models. It includes model training infrastructure, collaboration features, and model management tools.
• OpenAI Scholars Program: This is a research internship program that supports aspiring AI researchers from underrepresented backgrounds. It provides mentorship, stipends, and resources to help participants advance their AI knowledge and contribute to the field.

OpenAI, like Microsoft, emphasizes ethical considerations and responsible AI development.

Further reading

In this book, we’ll mainly be focusing on the OpenAI services that are exposed through Power Platform directly or via Azure AI Services. OpenAI’s products are available separately, as well. For more information on developing with the OpenAI platform, go to https://platform.openai.com/overview.

Working with services from Google, Anthropic, and more

While we’re mainly going to focus on services offered in the Microsoft cloud (Power Platform AI Builder, Azure AI Services, and OpenAI, to be more specific), they aren’t the only big names in AI right now. There are several other AI platforms – both general and specific – that are currently being developed. Some are even open for you to experiment with now!

Here’s a list of a few services that you might come across:

• Google Bard: Based on Google’s Language Model for Dialogue Applications (LaMDA), Bard is an advanced language model that’s developed by Google’s research team. LaMDA’s training involves dialogues instead of isolated prompts, allowing it to grasp the underlying meaning and engage in more conversational exchanges. You can start a conversation with Bard at https://bard.google.com.
• Anthropic Claude: Claude is another type of conversational AI model. Anthropic approaches their AI models a bit differently, however, training with a method they call Constitutional AI. Constitutional AI involves supervised learning and review so that the AI learns from the feedback to generate harmless outputs. Talk to Claude at https://claude.ai.
• Midjourney: Whereas ChatGPT, Bard, and Claude use text for both input and output, Midjourney is an AI-based art generation platform. Midjourney can be used to create high-quality art using text prompts. Experience Midjourney at https://www.midjourney.com/.

AI has also found its way into countless plugins and extensions. A quick internet search or two will quickly reveal new ad hoc tools you can try out.