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The best AI APIs everyone should know about

From image recognition to natural language processing, we'll look at the top APIs for each use case and what makes them stand out.

23 March, 2023
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Everyone can now observe how Artificial Intelligence has evolved from being just a buzzword to an indispensable tool for driving innovation across industries. As a result, at this point, today's fast-paced digital world straight-up compels businesses to use AI to stay competitive. And there's nothing wrong with that. Change is the only constant.

However, building AI systems from scratch is nothing short of challenging, requiring a deep understanding of machine learning and related technologies. This is where AI Application Programming Interfaces (APIs) come in.

They provide pre-built and ready-to-use solutions for various AI-related tasks causing the barrier to entry to significantly drop for businesses looking to leverage AI. In addition to common use cases, AI APIs also offer a range of other functionalities, such as chatbot functionality for customer service and custom AI solutions for specific business needs.

What’s more, healthcare AI companies have also been leveraging AI APIs to develop solutions for disease detection, diagnosis, and treatment. So, explore with us the best AI APIs available today that can help you take your applications to the next level.

From image recognition to natural language processing, we'll look at the top APIs for each use case and what makes them stand out.

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Our favorite AI APIs

Let’s now dive into the top AI APIs that can help you supercharge your applications with cutting-edge Artificial Intelligence capabilities. These selected APIs are the cream of the crop, selected based on their features, ease of use, and overall impact.

Our favorite AI APIs
Our favorite AI APIs

IBM Watson

IBM Watson AI API is a comprehensive suite of APIs that provide a full range of AI-powered services to help businesses build intelligent applications. With its recent collaboration with Hugging Face, IBM now offers a vast array of capabilities, including natural language processing, speech-to-text transcription, text-to-speech conversion, and sentiment analysis, alongside thousands of open-source models and datasets, making it an excellent choice for improving customer experience, automating processes, and enhancing decision-making.

A standout feature of the Watson API is Watsonx platform, introduced at the middle of 2023, which includes components like Watsonx.data and Watsonx.governance. Watsonx.data, a fit-for-purpose data store, is optimized for governed data and AI workloads and offers significant cost reductions in data management.

IBM also integrated generative AI functions into its platform post the ChatGPT surge, creating a system that combines IBM's data-processing capabilities with GenAI. Looking ahead, IBM plans to infuse Watsonx.ai foundation models across all major software products. 

This includes the Watson Code Assistant for generative AI-powered coding, AIOps Insights for enhanced IT operations, and the integration of advanced NLP models in Watson Assistant and Watson Orchestrate for improved digital labor efficiency.

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Microsoft’s Azure Cognitive Services

Microsoft's Azure Cognitive Services AI API is a set of pre-built machine learning models and algorithms that empowers developers to integrate intelligent features into their applications. These services enable developers to seamlessly incorporate advanced AI capabilities like emotion detection, facial recognition, speech and vision recognition, as well as speech and language understanding into their applications.

A highlight of these services includes new additions such as Text Analytics for health, Form Recognizer, Custom Commands, and innovative Neural Text to Speech voices. These advancements demonstrate Microsoft's commitment to expanding AI applications across various industries, including healthcare, insurance, and sustainable farming.

Alongside these developments, Azure Cognitive Services maintains robust integration with Microsoft products like Azure Data Lake, PowerApps, and Power BI. Developers are supported through an array of updated learning resources, tutorials, and community support, ensuring easy adoption and integration of these AI capabilities into diverse applications.

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Google Cloud AI

Google Cloud AI’s machine learning API services enhance intelligent application development with capabilities such as natural language processing, image/video analysis, and speech-to-text transcription. It excels in dynamic scalability for processing vast data volumes. Recent innovations include GenAI products, especially for retail, improving online shopping and back-office efficiency. 

The Conversational Commerce Solution, using GenAI agents, offers natural interactions and tailored product recommendations on retail platforms. The Catalog and Content Enrichment toolset, utilizing GenAI models like PaLM and Imagen, automates product descriptions, categorization, and image creation, easing product catalog maintenance.

Integration with Google Cloud Platform services like BigQuery and Dataflow enhances Google Cloud AI's machine learning offerings. Notable additions are the PaLM API and MakerSuite, simplifying generative AI application development. 

The enhanced Vertex AI platform provides over 100 foundational and industry-specific models, fostering customization across various sectors. Google Cloud AI's AutoML, a key feature, enables easy creation of custom machine-learning models with minimal coding.

Amazon AI Services

Another great suite of machine learning APIs is offered by Amazon Web Services (AWS), and it’s called Amazon AI Services. Amazon AI Services AI API, just like others, helps build intelligent, AI-powered apps thanks to natural language processing, chatbots, demand forecasting, speech-to-text transcription, and image and video analysis.

Recently, AWS has been focusing more on generative AI, integrating it into various services. They announced Amazon Q, an AI-powered chatbot, designed to engage in conversations, generate content, and take actions, informed by an understanding of company systems, data repositories, and operations. AWS is also increasing its focus on LLMs, introducing new capabilities and enhancements to existing services.

Other features and announcements:

  • SageMaker HyperPod, a service optimized for training large language models..
  • Titan Image Generator, which can create new images from text descriptions or customize existing images. 
  • Amazon Neptune Analytics, combining graph and vector databases.
  • AWS Clean Rooms ML, a privacy-preserving service allowing the deployment of AI models without sharing proprietary data​​.

New chips, Graviton4 and Trainium2, designed to accelerate the building, training, and deploying of generative AI models.

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Open AI

The next AI API on our list has seen significant advancements since last year, thanks to OpenAI's continuous progress with its GPT models. OpenAI's GPT, standing for Generative Pre-trained Transformer, remains a leader in enabling businesses and developers to build natural language processing applications.

Their API offers state-of-the-art language models, like GPT-4, that continue to generate human-like text, summarize articles, and perform language translation, among other tasks. 

OpenAI GPT maintains its user-friendly design with an intuitive API and clear documentation for developers. One of the standout features of the latest models is enhanced fine-tuning capabilities, allowing for more customized and effective applications.

Furthermore, OpenAI's collaboration with Microsoft has brought GPT-4 Turbo to Microsoft 365 users through Copilot Pro, offering advanced AI capabilities across various applications. Additionally, OpenAI has introduced ChatGPT Team, a subscription plan aimed at small teams, providing access to the latest models and collaborative tools.

ParallelDots

ParallelDots ParallelDots AI API, known for its AI-powered NLP and image recognition services, has significantly expanded its focus and capabilities this year. The company has developed a specialized AI platform for retail, particularly focusing on computer vision. Their flagship product, 'ShelfWatch', helps FMCG companies and retailers enhance brand visibility on retail shelves by analyzing images for product availability, pricing compliance, and more.

One of the standout features of ParallelDots is its advanced natural language processing capabilities, including text classification, entity extraction, and emotion analysis. Another notable feature is its pricing model, which is based on usage rather than a fixed subscription fee, allowing you to pay for only what you use and making it an attractive option for those with limited budgets.

ParallelDots API also offers seamless integration with other platforms, including Google Sheets, Zapier, and Microsoft Excel, making it easier for businesses to integrate AI capabilities into their existing workflows.

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What is an AI API?

So, AI APIs, as you may know, are pre-built software components that allow developers to easily integrate artificial intelligence capabilities into their applications. They work by providing access to pre-trained models and algorithms for tasks such as natural language processing, image recognition, and sentiment analysis.

Developers can now send data to these APIs and receive processed results, allowing them to build intelligent applications without extensive machine learning expertise. Many current AI APIs are also available on a pay-as-you-go basis, making it quite cost-effective for businesses to leverage the power of AI.

While still cost-effective, there's a recent emphasis on optimizing AI APIs for specific use cases to reduce cost and latency, particularly for large models like GPT-4. Businesses are exploring diverse models to achieve better parity across AI applications​​.

Lately, the trend has also shifted towards more customized generative AI models, precisely adapted to specific market needs and user requirements. This customization allows for greater efficiency and accuracy in specialized fields like healthcare, finance, and legal sectors​​.

In addition to making it easier and more profitable to incorporate AI into applications, AI APIs also enable companies to quickly prototype and test new AI-powered features and functionalities. If you’re a business owner, this will help you promptly respond to changing market needs and customer demands.

The evolution of AI technologies has accelerated significantly, with particular advancements in generative AI and AI-driven data analytics. Vendors are now infusing AI into a broader range of products, enhancing data management efficiency and offering more intuitive, interactive experiences through natural language interfaces​​.

However, despite the many benefits of AI APIs, there are also some challenges and considerations you need to keep in mind when using them.

Remember to also carefully evaluate and test the APIs you use to make sure they are accurate, reliable, and suitable for your specific use cases. The final touch would be ensuring the necessary technical expertise and resources to properly integrate and manage the AI APIs you are using.

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Conclusion

Overall, it’s no secret the extent to which AI APIs have revolutionized how businesses incorporate artificial intelligence capabilities into their applications. With pre-trained models and algorithms readily available, companies can now quickly and easily build intelligent applications without hardly any machine-learning expertise.

IBM Watson, Microsoft Cognitive Services, Google Cloud AI, Amazon AI Services, and OpenAI are some of the leading providers of AI APIs, each with its own unique features and capabilities, and our list can help you evaluate which one you’d like to choose for your project.

AI technology will definitely advance even more, and even now, the possibilities for AI APIs are endless. As a business owner, you can leverage this technology to gain a competitive advantage and drive innovation.

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author

CEO and Founder of Merge

My mission is to help startups build software, experiment with new features, and bring their product vision to life.

My mission is to help startups build software, experiment with new features, and bring their product vision to life.

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