AWS Machine Learning Blog

JUNE 13, 2023

Organizations can maximize the value of their modern data architecture with generative AI solutions while innovating continuously. The latest offering for generative AI from AWS is Amazon Bedrock , which is a fully managed service and the easiest way to build and scale generative AI applications with foundation models.

Generative AI 69

Generative AI Metadata LLM Large Language Models 69

AWS Machine Learning Blog

SEPTEMBER 15, 2023

Large language model (LLM) agents are programs that extend the capabilities of standalone LLMs with 1) access to external tools (APIs, functions, webhooks, plugins, and so on), and 2) the ability to plan and execute tasks in a self-directed fashion. We conclude the post with items to consider before deploying LLM agents to production.

LLM 95

LLM Prompt Engineer Prompt Engineering Large Language Models 95

AWS Machine Learning Blog

NOVEMBER 29, 2023

However, harnessing this potential while ensuring the responsible and effective use of these models hinges on the critical process of LLM evaluation. An evaluation is a task used to measure the quality and responsibility of output of an LLM or generative AI service. Who needs to perform LLM evaluation?

LLM 78

LLM Data Scientist Algorithm Generative AI 78

AWS Machine Learning Blog

MAY 30, 2024

Because Amazon Bedrock is serverless, you don’t have to manage infrastructure, and you can securely integrate and deploy generative AI capabilities into your applications using the AWS services you are already familiar with. The wrapper function reads the table metadata from the S3 bucket. If it finds any, it skips to Step 6.

Metadata 93

Metadata Generative AI LLM Prompt Engineer 93

AWS Machine Learning Blog

MAY 30, 2024

Instead, Vitech opted for Retrieval Augmented Generation (RAG), in which the LLM can use vector embeddings to perform a semantic search and provide a more relevant answer to users when interacting with the chatbot. Prompt engineering Prompt engineering is crucial for the knowledge retrieval system.

Chatbots 91

Chatbots Prompt Engineer Prompt Engineering Large Language Models 91

AWS Machine Learning Blog

MAY 7, 2024

Large language models (LLMs) have unlocked new possibilities for extracting information from unstructured text data. Although much of the current excitement is around LLMs for generative AI tasks, many of the key use cases that you might want to solve have not fundamentally changed.

Prompt Engineer 89

Prompt Engineer Prompt Engineering Large Language Models LLM 89

Flipboard

DECEMBER 6, 2023

The following are some of the experiments that were conducted by the team, along with the challenges identified and lessons learned: Pre-training – Q4 understood the complexity and challenges that come with pre-training an LLM using its own dataset. The generated query is then run against the database to fetch the relevant context.

Chatbots 130

Chatbots LLM Prompt Engineer Prompt Engineering 130

John Snow Labs

OCTOBER 16, 2023

The recent NLP Summit served as a vibrant platform for experts to delve into the many opportunities and also challenges presented by large language models (LLMs). As the market for generative AI solutions is poised to hit $51.8 billion by 2028, LLMs play a pivotal role in this growth trajectory. Unstructured.IO

Large Language Models 52

Large Language Models NLP Metadata LLM 52

deepsense.ai

JULY 30, 2023

Model training is only a small part of a typical machine learning project (source: own study) Of course, in the context of Large Language Models, we often talk about just fine tuning, few-shot learning or just prompt engineering instead of a full training procedure. Why are these elements so important? monitoring and automation).

Large Language Models 92

Large Language Models LLM Machine Learning Automation 92

AWS Machine Learning Blog

OCTOBER 24, 2023

By integrating generative artificial intelligence (AI) into the process, we can further enhance IDP capabilities. Generative AI not only introduces enhanced capabilities in document processing, it also introduces a dynamic adaptability to changing data patterns.

IDP 107

IDP LLM Prompt Engineer Prompt Engineering 107

Heartbeat

FEBRUARY 8, 2024

The recent rise of Large Language Models (LLMs) has been a game changer for the ChatBot industry. These LLM-based bots have found various applications in various industries and have become the go-to information source for many people. Each chat message is associated with content and role, e.g., Human, AI, or a system role.

Conversational AI 52

Conversational AI Chatbots LLM Prompt Engineer 52

Flipboard

NOVEMBER 24, 2023

Many customers are building generative AI apps on Amazon Bedrock and Amazon CodeWhisperer to create code artifacts based on natural language. Amazon Bedrock is the easiest way to build and scale generative AI applications with foundation models (FMs).

ETL 112

ETL Prompt Engineer Prompt Engineering Generative AI 112

ODSC - Open Data Science

OCTOBER 6, 2023

Be sure to check out his talk, “ Prompt Optimization with GPT-4 and Langchain ,” there! The difference between the average person using AI and a Prompt Engineer is testing. Most people run a prompt 2–3 times and find something that works well enough.

Prompt Engineer 52

Prompt Engineer Prompt Engineering Python Data Science 52

Heartbeat

DECEMBER 13, 2023

You would change it to the following: tools = load_tools(tool_names, llm=llm) Defining Custom Tools Custom tools in LangChain are defined by the user to perform specific tasks or operations not provided by the native tools in the LangChain toolkit. You pass in a query (text string), and you get a result (text string).

LLM 52

LLM Metadata Deep Learning Automation 52

Heartbeat

NOVEMBER 8, 2023

For example, you can create a chain that takes user input, formats it with a PromptTemplate, and then passes the formatted response to an LLM. The main differences between using an LLMChain versus directly passing a prompt to an LLM are: LLMChain allows chaining multiple prompts together, while directly passing a prompt only allows one.

LLM 52

LLM OpenAI Data Scientist Prompt Engineer 52

AWS Machine Learning Blog

APRIL 16, 2024

To learn more about SageMaker Studio JupyterLab Spaces, refer to Boost productivity on Amazon SageMaker Studio: Introducing JupyterLab Spaces and generative AI tools. Text to SQL: Using natural language to enhance query authoring SQL is a complex language that requires an understanding of databases, tables, syntaxes, and metadata.

Data Scientist 84

Data Scientist Generative AI ML Machine Learning 84

Snorkel AI

MARCH 2, 2023

Ali Arsanjani, director of cloud partner engineering at Google Cloud , presented a talk entitled “Challenges and Ethics of DLM and LLM Adoption in the Enterprise” at Snorkel AI’s recent Foundation Model Virtual Summit. But: these are not going to be adequate for supporting generative AI.

Large Language Models 52

Large Language Models Prompt Engineer Prompt Engineering Neural Network 52

Snorkel AI

MARCH 2, 2023

Ali Arsanjani, director of cloud partner engineering at Google Cloud , presented a talk entitled “Challenges and Ethics of DLM and LLM Adoption in the Enterprise” at Snorkel AI’s recent Foundation Model Virtual Summit. But: these are not going to be adequate for supporting generative AI.

Large Language Models 52

Large Language Models Prompt Engineer Prompt Engineering Neural Network 52