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AI Studio has released new updates that give developers even more control. ​ 

This post is co-written with Ross Ashworth at TP ICAP. The ability to quickly extract insights from customer relationship management systems (CRMs) and vast amounts of meeting notes can mean the difference between seizing opportunities and missing them entirely. TP ICAP faced this challenge, having thousands of vendor meeting records stored in their CRM. Using …

How TP ICAP transformed CRM data into real-time insights with Amazon Bedrock Read More »

This guest post was written by Mulay Ahmed and Caroline Lima-Lane of Principal Financial Group. The content and opinions in this post are those of the third-party authors and AWS is not responsible for the content or accuracy of this post. With US contact centers that handle millions of customer calls annually, Principal Financial Group® …

Principal Financial Group accelerates build, test, and deployment of Amazon Lex V2 bots through automation Read More »

Choosing the right large language model (LLM) for your use case is becoming both increasingly challenging and essential. Many teams rely on one-time (ad hoc) evaluations based on limited samples from trending models, essentially judging quality on “vibes” alone. This approach involves experimenting with a model’s responses and forming subjective opinions about its performance. However, …

Beyond vibes: How to properly select the right LLM for the right task Read More »

Generative AI is rapidly reshaping the music industry, empowering creators—regardless of skill—to create studio-quality tracks with foundation models (FMs) that personalize compositions in real time. As demand for unique, instantly generated content grows and creators seek smarter, faster tools, Splash Music collaborated with AWS to develop and scale music generation FMs, making professional music creation …

Splash Music transforms music generation using AWS Trainium and Amazon SageMaker HyperPod Read More »

Organizations often face challenges when implementing single-shot fine-tuning approaches for their generative AI models. The single-shot fine-tuning method involves selecting training data, configuring hyperparameters, and hoping the results meet expectations without the ability to make incremental adjustments. Single-shot fine-tuning frequently leads to suboptimal results and requires starting the entire process from scratch when improvements are …

Iterative fine-tuning on Amazon Bedrock for strategic model improvement Read More »

Artificial Intelligence (AI) is transforming the quick-service restaurant industry, particularly in drive-thru operations where efficiency and customer satisfaction intersect. Traditional systems create significant obstacles in service delivery, from staffing limitations and order accuracy issues to inconsistent customer experiences across locations. These challenges, combined with rising labor costs and demand fluctuations, have pushed the industry to …

Voice AI-powered drive-thru ordering with Amazon Nova Sonic and dynamic menu displays Read More »

Multimodal fine-tuning represents a powerful approach for customizing vision large language models (LLMs) to excel at specific tasks that involve both visual and textual information. Although base multimodal models offer impressive general capabilities, they often fall short when faced with specialized visual tasks, domain-specific content, or output formatting requirements. Fine-tuning addresses these limitations by adapting …

Optimizing document AI and structured outputs by fine-tuning Amazon Nova Models and on-demand inference Read More »

An overview of ten years of milestones and breakthroughs in Google’s work on genomics. ​ 

An overview of DeepSomatic, a new AI tool that helps identify complex genetic variants in cancer cells. ​