Today, the Accounts Payable (AP) and Accounts Receivable (AR) analysts in Amazon Finance operations receive queries from customers through email, cases, internal tools, or phone. When a query arises, analysts must engage in a time-consuming process of reaching out to subject matter experts (SMEs) and go through multiple policy documents containing standard operating procedures (SOPs) …
Google and Kaggle recently launched a five-day intensive course about generative AI.
We are excited to announce the availability of Cohere’s advanced reranking model Rerank 3.5 through our new Rerank API in Amazon Bedrock. This powerful reranking model enables AWS customers to significantly improve their search relevance and content ranking capabilities. This model is also available for Amazon Bedrock Knowledge Base users. By incorporating Cohere’s Rerank 3.5 …
Cohere Rerank 3.5 is now available in Amazon Bedrock through Rerank API Read More »
As developers gear up for re:Invent 2024, they again face the unique challenges of physical racing. What are the obstacles? Let’s have a look. In this blog post, I will look at what makes physical AWS DeepRacer racing—a real car on a real track—different to racing in the virtual world—a model in a simulated 3D …
The new efficient multi-adapter inference feature of Amazon SageMaker unlocks exciting possibilities for customers using fine-tuned models. This capability integrates with SageMaker inference components to allow you to deploy and manage hundreds of fine-tuned Low-Rank Adaptation (LoRA) adapters through SageMaker APIs. Multi-adapter inference handles the registration of fine-tuned adapters with a base model and dynamically …
Prompt engineering refers to the practice of writing instructions to get the desired responses from foundation models (FMs). You might have to spend months experimenting and iterating on your prompts, following the best practices for each model, to achieve your desired output. Furthermore, these prompts are specific to a model and task, and performance isn’t …
Enterprises are facing challenges in accessing their data assets scattered across various sources because of increasing complexities in managing vast amount of data. Traditional search methods often fail to provide comprehensive and contextual results, particularly for unstructured data or complex queries. Search solutions in modern big data management must facilitate efficient and accurate search of …
Search enterprise data assets using LLMs backed by knowledge graphs Read More »
Generative AI continues to transform numerous industries and activities, with one such application being the enhancement of chess, a traditional human game, with sophisticated AI and large language models (LLMs). Using the Custom Model Import feature in Amazon Bedrock, you can now create engaging matches between foundation models (FMs) fine-tuned for chess gameplay, combining classical …
Large language models (LLMs) have witnessed an unprecedented surge in popularity, with customers increasingly using publicly available models such as Llama, Stable Diffusion, and Mistral. Across diverse industries—including healthcare, finance, and marketing—organizations are now engaged in pre-training and fine-tuning these increasingly larger LLMs, which often boast billions of parameters and larger input sequence length. Although …
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 complex workflows effectively, agents rely on …
Getting started with Amazon Bedrock Agents custom orchestrator Read More »
