Remove Auto-complete Remove LLM Remove Software Engineer
article thumbnail

Taming the Oracle: Key Principals That Bring Our LLM Agents to Production

Towards AI

Generated with Microsoft Designer With the second anniversary of the ChatGPT earthquake right around the corner, the rush to build useful applications based on large language models (LLMs) of its like seems to be in full force. I believe they are highly relevant to other LLM based applications just as much.

LLM 80
article thumbnail

MetaGPT: Complete Guide to the Best AI Agent Available Right Now

Unite.AI

Last time we delved into AutoGPT and GPT-Engineering , the early mainstream open-source LLM-based AI agents designed to automate complex tasks. Enter MetaGPT — a Multi-agent system that utilizes Large Language models by Sirui Hong fuses Standardized Operating Procedures (SOPs) with LLM-based multi-agent systems.

Python 328
professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

AI and coding: How Seattle tech companies are using generative AI for programming

Flipboard

Prompt: “A robot helping a software engineer develop code.” ” Generative AI is already changing the way software engineers do their jobs. Redfin Photo) “We’ve already found a number of places where AI tools are making our engineers more efficient. Made with Microsoft Bing Image Creator.

article thumbnail

How Amazon Search M5 saved 30% for LLM training cost by using AWS Trainium

AWS Machine Learning Blog

To summarize, we used the following flags for compilation: NEURON_CC_FLAGS="--target trn1 --auto-cast all --auto-cast-type bf16 --model-type transformer --optlevel O1" Checkpoint compatibility When compilation is successfully complete, we can proceed to train our models on Trainium. You can find him on LinkedIn.

LLM 118
article thumbnail

Introducing SageMaker Core: A new object-oriented Python SDK for Amazon SageMaker

AWS Machine Learning Blog

Auto code completion – It enhances the developer experience by offering real-time suggestions and completions in popular integrated development environments (IDEs), reducing chances of syntax errors and speeding up the coding process. Data preparation In this phase, prepare the training and test data for the LLM.

Python 87
article thumbnail

Automate Q&A email responses with Amazon Bedrock Knowledge Bases

AWS Machine Learning Blog

We then send the prompt alongside the additional context to a large language model (LLM) for response generation. on Amazon Bedrock as our LLM to generate user responses using additional context. The prompt is then augmented with the chunks that are retrieved from the vector store. Anthropic’s Claude Sonnet 3.5

article thumbnail

Boosting Salesforce Einstein’s code generating model performance with Amazon SageMaker

AWS Machine Learning Blog

In this post, we share how the Salesforce Einstein AI Platform team boosted latency and throughput of their code generation LLM using Amazon SageMaker. LMI containers are a set of high-performance Docker Containers purpose built for LLM inference. Looking to host your own LLMs on SageMaker?

LLM 128