Agents

In: Artificial Intelligence

Large language models (LLMs) excel at generating human-like text but face a critical challenge: hallucination—producing responses that sound convincing but are factually incorrect. While these models are trained on vast amounts of generic data, they often lack the organization-specific context and up-to-date information needed for accurate responses in business settings.Continue Reading

In: Artificial Intelligence

AI agents continue to gain momentum, as businesses use the power of generative AI to reinvent customer experiences and automate complex workflows. We are seeing Amazon Bedrock Agents applied in investment research, insurance claims processing, root cause analysis, advertising campaigns, and much more. Agents use the reasoning capability of foundationContinue Reading

In: Artificial Intelligence

The integration of generative AI capabilities is driving transformative changes across many industries. Although weather information is accessible through multiple channels, businesses that heavily rely on meteorological data require robust and scalable solutions to effectively manage and use these critical insights and reduce manual processes. This solution demonstrates how toContinue Reading

In: Artificial Intelligence

Generative AI has revolutionized technology through generating content and solving complex problems. To fully take advantage of this potential, seamless integration with existing business systems and efficient access to data are crucial. Amazon Bedrock Agents provides the integration capabilities to connect generative AI models with the wealth of information andContinue Reading

In: Artificial Intelligence

This post was written with Zach Marston and Serg Masis from Syngenta. Syngenta and AWS collaborated to develop Cropwise AI, an innovative solution powered by Amazon Bedrock Agents, to accelerate their sales reps’ ability to place Syngenta seed products with growers across North America. Cropwise AI harnesses the power ofContinue Reading

In: Artificial Intelligence

Generative AI agents are designed to interact with their environment to achieve specific objectives, such as automating repetitive tasks and augmenting human capabilities. By orchestrating multistep workflows that adapt to evolving goals in real time, these agents increase productivity, reduce errors, and deliver more personalized experiences. To manage these complexContinue Reading

In: Artificial Intelligence

Hallucinations in large language models (LLMs) refer to the phenomenon where the LLM generates an output that is plausible but factually incorrect or made-up. This can occur when the model’s training data lacks the necessary information or when the model attempts to generate coherent responses by making logical inferences beyondContinue Reading

In: Artificial Intelligence

Stock technical analysis questions can be as unique as the individual stock analyst themselves. Queries often have multiple technical indicators like Simple Moving Average (SMA), Exponential Moving Average (EMA), Relative Strength Index (RSI), and others. Answering these varied questions would mean writing complex business logic to unpack the query intoContinue Reading