We performed a comparison between Azure OpenAI and IBM Watson Machine Learning based on real PeerSpot user reviews.
Find out in this report how the two AI Development Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The product saves a lot of time."
"It's very powerful. It allows users to query our documents using natural language and receive answers in the same way. This makes our product information much more accessible than traditional keyword-based search."
"The product's initial setup phase was pretty easy."
"Azure OpenAI is very easy to use instead of AWS services."
"The most crucial aspect is the conversational capability, where you can simply ask questions, and it provides answers based on your content and documents, particularly tailored to your specific environment."
"Our clients are interested in building knowledge bases, particularly in child welfare. In this domain, we focus on supporting caseworkers by compiling and organizing relevant information. This information is then stored in a database using a query. The database generates summaries and reminders for specific actions and even facilitates sending emails to parents or other relevant parties. The system's complexity is tailored to the specific needs of child welfare cases. Additionally, we're exploring opportunities to assist a healthcare organization. Specifically, we're working on streamlining the process of filling out forms required for insurance claims. This effort aims to ensure that hospitals can receive funding or payment for the care they provide."
"The high precision of information extraction is the most valuable feature."
"The solution has a very drag-and-drop environment. Instead of coding something from scratch or understanding any concept in extensive depth before deployment, this is good. Plus, they have an auto dataset, which means you can choose any dataset they have instead of providing your own. So that's also pretty nice."
"The solution is very valuable to our organization due to the fact that we can work on it as a workflow."
"Scalability-wise, I rate the solution ten out of ten."
"It has improved self-service and customer satisfaction."
"It is has a lot of good features and we find the image classification very useful."
"I was particularly interested in trying the AutoML feature to see how it handles data and proposes new models. The variety of models it provides is impressive."
"The most valuable aspect of the solution's the cost and human labor savings."
"We encountered challenges related to question understanding."
"Since we don't train the model on our data, it's a struggle to ensure OpenAI answers questions exclusively from our data. During user testing, we found ways to make the system provide answers from outside sources."
"Sometimes, the responses are repetitive."
"The product features themselves are fine. However, with Microsoft scaling the service so much, the support structure needs to keep pace. When solving complex issues, the process of interacting with Microsoft can be quite time-consuming."
"There are certain shortcomings with the product's scalability and support team where improvements are required."
"Deployment was slightly complex for me to understand."
"Azure OpenAI is not an optimized tool yet, making it one of its shortcomings where improvements are required."
"The fine-tuning of models with the use of Azure OpenAI is an area with certain shortcomings currently, and it can be considered for improvement in the future."
"Scaling is limited in some use cases. They need to make it easier to expand in all aspects."
"The supporting language is limited."
"Honestly, I haven't seen any comparative report that has run the same data through two different artificial intelligence or machine learning capabilities to get something out of it. I would love to see that."
"In future releases, I would like to see a more flexible environment."
"They should add more GPU processing power to improve performance, especially when dealing with large amounts of data."
"If I consider how we want to use it in our organization, certain areas of improvement can be addressed. For instance, we want to use it with Generative AI, not like ChatGPT, but in a way intended for industrial use."
Azure OpenAI is ranked 2nd in AI Development Platforms with 17 reviews while IBM Watson Machine Learning is ranked 9th in AI Development Platforms with 6 reviews. Azure OpenAI is rated 8.0, while IBM Watson Machine Learning is rated 8.0. The top reviewer of Azure OpenAI writes "Created a chatbot powered by OpenAI to answer HR, travel, and expense-related questions". On the other hand, the top reviewer of IBM Watson Machine Learning writes "A highly efficient solution that delivers the desired results to its users". Azure OpenAI is most compared with Google Vertex AI, Amazon SageMaker, Microsoft Azure Machine Learning Studio, Hugging Face and TensorFlow, whereas IBM Watson Machine Learning is most compared with Google Cloud AI Platform and TensorFlow. See our Azure OpenAI vs. IBM Watson Machine Learning report.
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