Category: Artificial Intelligence

With the rise of large language models, natural language processing, and generative AI models, embeddings are becoming a critical piece of data in more machine learning use cases. In this post, explore different ways embeddings are used in machine learning and where problems can show up that impact your ML models, and how you can use WhyLabs to identify those problems and create monitors to avoid them showing up again in the future.

Prior authorization is an insurance review process used by healthcare providers to confirm medical coverage with health insurance companies. Learn how Neurons Lab collaborated with Treatline on its platform to streamline the highly manual prior authorization process using intelligent document processing (IDP) and generative AI. Neurons Lab is an innovative technology company specializing in AI/ML and software development.

Migrating to a new hosting provider to save costs presents an opportunity to fine-tune application performance and the DevOps processes supporting a company’s applications. This was the case for MasterWorks, which is based near Seattle and helps move the hearts and minds of people to act for Christian ministries across America. Learn how Avahi Technologies and AWS collaborated to help MasterWorks migrate an application that uses machine learning models from a SaaS provider to AWS.

As the digitization of businesses accelerates, the value of effective knowledge management continues to rise. The complexity of large language models (LLMs) and semantic search demands a modern data strategy and specific technical skill sets. Together, generative AI and semantic search form an integrated ecosystem for intelligent knowledge management. Learn how both can be harnessed to improve productivity and operational efficiency by democratizing enhanced search capabilities and generating actionable insights.

Many organizations still are managing expensive single use case data environments, however, and IBM’s Modern Data Accelerators on AWS can help build modern implementation of a data fabric architecture, enabling customers to realize faster time to value. Learn how IBM’s Modern Data Accelerators can help build modern implementation of a data fabric architecture, which standardizes data integration across the enterprise.

Adversarial machine learning (AML) attacks, also known as “artificial intelligence attacks” (AI attacks), involve deliberate attempts to manipulate or compromise machine learning models or even make it reveal sensitive information. Explore how AIShield‘s seamless integration within the Amazon SageMaker environment alleviates AI security concerns by mitigating risks before and after deployment, enabling customers to develop and deploy AI applications with confidence.

Generative AI and large language models (LLMs) such as AI21 Labs’ Jurassic models are reshaping how we engage with information. This post walks through using the Jurassic-2 (J2) large language model and how to consume the model via an AWS Lambda API endpoint. We’ll also discuss how to make calls to the J2 model via the publicly available Jurassic-2 Python SDK. AI21 Labs is an AWS Partner and leader in generative AI and LLMs, revolutionizing the way people read and write.

As the world grows, concerns over pollution and climate change are forcing businesses to redesign how they produce and use energy. A notable approach for achieving this objective is through informing end users of their power usage patterns. Learn how IBM’s anomaly detection solution for energy and utilities helps companies increase energy efficiency leveraging a personalized AI paradigm and to calculate ESG metrics related to energy consumption.

IBM’s watsonx is an artificial intelligence and data platform designed to scale and accelerate the impact of AI with trusted data. As a part of watsonx, IBM has launched watsonx.data, which enables customers to scale analytics and AI with a fit-for-purpose data store, built on an open lakehouse architecture. It provides querying, governance, and open data formats for easy data access and sharing. Customers can connect to their data within minutes, gain trusted insights quickly, and reduce data warehouse costs.

Contact center agents operate under vast pressure to find quick customer service solutions—yet they often lack the tools to do so. The IBM Consulting Contact Center Modernization (CCM) solution with Amazon Connect is an intuitive, omnichannel cloud platform that addresses complex and costly issues faced by businesses. By leveraging speed and operational efficiency, and by delivering exceptional customer experiences, IBM Consulting CCM enables brands to jump-start their journey towards success.