Remove 2022 Remove Healthcare Remove Presentation Remove Scripts
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The Case For the Anti-Script: A Multifactor Analysis of Script Adherence

Balto

“The anti-script doesn’t mean that you should wing it on every call… what anti-script means is, think about a physical paper script and an agent who is reading it off word for word… you’re taking the most powerful part of the human out of the human.” Share on Twitter. Share on Facebook.

Scripts 52
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Guest Blog: Customer Support Chatbots ? Striking The Right Balance

ShepHyken

Another study by UK-based Juniper Research estimates that chatbots will help businesses save more than $8 billion per year by 2022. In fact, the success rate of bot interactions in the healthcare sector was only 12% according to the same Juniper study. These numbers are staggering. Things aren’t as bad as they sound though.

Chatbots 191
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Federated Learning on AWS with FedML: Health analytics without sharing sensitive data – Part 2

AWS Machine Learning

Analyzing real-world healthcare and life sciences (HCLS) data poses several practical challenges, such as distributed data silos, lack of sufficient data at a single site for rare events, regulatory guidelines that prohibit data sharing, infrastructure requirement, and cost incurred in creating a centralized data repository. and data_loader.py

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Simplify access to internal information using Retrieval Augmented Generation and LangChain Agents

AWS Machine Learning

The service analyzes the text and identifies any PII entities present within the query. The Amazon Kendra crawler is then able to use both the corporate training video scripts and documentation stored in these other sources to assist the conversational bot in answering questions specific to company corporate training guidelines.

APIs 88
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Extract non-PHI data from Amazon HealthLake, reduce complexity, and increase cost efficiency with Amazon Athena and Amazon SageMaker Canvas

AWS Machine Learning

For example, in the healthcare industry, ML-driven analytics can be used for diagnostic assistance and personalized medicine, while in health insurance, it can be used for predictive care management. This team has the knowledge and intuition in healthcare but not the ML skills to build models and generate predictions.

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Inpaint images with Stable Diffusion using Amazon SageMaker JumpStart

AWS Machine Learning

In November 2022, we announced that AWS customers can generate images from text with Stable Diffusion models using Amazon SageMaker JumpStart. You have to run end-to-end tests to make sure that the script, the model, and the desired instance work together efficiently.

APIs 76
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Upscale images with Stable Diffusion in Amazon SageMaker JumpStart

AWS Machine Learning

In November 2022, we announced that AWS customers can generate images from text with Stable Diffusion models in Amazon SageMaker JumpStart. Running large models like Stable Diffusion requires custom inference scripts. JumpStart simplifies this process by providing ready-to-use scripts that have been robustly tested.

APIs 70