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Data and AI
 

February 2023
 
 
 
 
 

Hello, Data and AI enthusiasts!

With AI providing benefits across many industries, companies are constantly innovating on how to make applications smarter and better. However, advancements in AI can create new challenges and raise legal and ethical questions. Building trusted AI pipelines has become increasingly important within AI applications, and there are three main pillars to building trustworthy AI pipelines: fairness, explainability, and robustness. In this month's newsletter, find out more about these pillars and explore tools to help instill trust in your apps.
 
 
 
 

Spotlights
 
 

IBM Data and AI on AWS: Unlock the power of your data

Use AI, machine learning, and data science technology to get the most out of the hybrid cloud.
 
 

Instilling trust in AI
 

What level of trust can - and should - we place in these AI systems?
 
 

Easily deploy Watson Libraries' NLP models on AWS
 

Learn how to use Watson NLP on an AWS Fargate environment to easily deploy NLP capabilities anywhere.
 
 
 
 

Leverage external data to enhance your chatbot's conversational skills

Augment a conversation with live data from API calls that can be set up to fetch near real-time data from databases or to fetch public information on the internet.
 
 

Code on the Road: Can you build ML pipelines in JupyterLab with Elyra without writing code?
 
 
 
Watch the video
 

Other items of interest
 
 

News