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Information extraction with LLMs using Amazon SageMaker JumpStart

AWS Machine Learning

Rather than requiring extensive feature engineering and dataset labeling, LLMs can be fine-tuned on small amounts of domain-specific data to quickly adapt to new use cases. This post walks through examples of building information extraction use cases by combining LLMs with prompt engineering and frameworks such as LangChain.

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2024 Expectations: The forefront of the next generation of customer success

Totango

Most expect to see CS emerging as a growth engine. Human expertise, along with AI technology, transforms CS into a significant growth engine for their companies. For many companies, the CSM role has become a catch-all for various tasks – from renewals and billing to technical support.

SaaS 97
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Assured Fire and Security Boosts Growth with BigChange Mobile Tech

CSM Magazine

Using live linked mobile devices running the BigChange app, Assured has increased engineer productivity, reduced operational costs and improved management visibility of the field service operation. “From the first demo to a call to the Roadcrew support team at 3 in the morning, I just love everything about it. .”

Finance 52
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WHY OTPs CEASED CATCHING THOSE OTP (ON THE PROWL)

pindrop

OTPs are often used for the purpose of account login, identity verification, device verification, or password recovery. Through deception, a fraudster can steal your personal data to gain access to your bank accounts and other valuable data. Diminished Impact on Security: Over time, fraudsters adapted and found ways to beat OTPs.

Banking 127
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Ten Examples of Client-Facing Roles

CSM Magazine

Account Manager Account managers act as liaisons between their organization and existing clients, ensuring that all activities associated with the account run smoothly and successfully meet the goals set forth by both parties involved in the agreement.

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Build an automated insight extraction framework for customer feedback analysis with Amazon Bedrock and Amazon QuickSight

AWS Machine Learning

Operational efficiency Uses prompt engineering, reducing the need for extensive fine-tuning when new categories are introduced. Generative AI models offer advantages with pre-trained language understanding, prompt engineering, and reduced need for retraining on label changes, saving time and resources compared to traditional ML approaches.

Feedback 126
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Churn prediction using multimodality of text and tabular features with Amazon SageMaker Jumpstart

AWS Machine Learning

To try out the solution in your own account, make sure that you have the following in place: An AWS account. If you don’t have an account, you can sign up for one. We now carry out feature engineering steps and then fit the model. The solution outlined in the post is part of SageMaker JumpStart.