Towards AI

JUNE 18, 2024

About Building LLMs for Production Generative AI and LLMs are transforming industries with their ability to understand and generate human-like text and images. However, building reliable and scalable LLM applications requires a lot of extra work and a deep understanding of various techniques and frameworks.

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Large Language Models Prompt Engineer Prompt Engineering LLM 60

AWS Machine Learning Blog

MARCH 13, 2024

The LLM analysis provides a violation result (Y or N) and explains the rationale behind the model’s decision regarding policy violation. The audio moderation workflow activates the LLM’s policy evaluation only when the toxicity analysis exceeds a set threshold. LLMs, in contrast, offer a high degree of flexibility.

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LLM Natural Language Processing Prompt Engineer Prompt Engineering 125

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.

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Chatbots Prompt Engineer Prompt Engineering Large Language Models 122

AWS Machine Learning Blog

SEPTEMBER 1, 2023

Furthermore, we deep dive on the most common generative AI use case of text-to-text applications and LLM operations (LLMOps), a subset of FMOps. MLOps engineers are responsible for providing a secure environment for data scientists and ML engineers to productionize the ML use cases.

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Generative AI Prompt Engineer Prompt Engineering AI 123

AWS Machine Learning Blog

OCTOBER 4, 2023

In this post, we walk you through deploying a Falcon large language model (LLM) using Amazon SageMaker JumpStart and using the model to summarize long documents with LangChain and Python. SageMaker is a HIPAA-eligible managed service that provides tools that enable data scientists, ML engineers, and business analysts to innovate with ML.

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LLM Large Language Models Generative AI ML 109

Heartbeat

OCTOBER 5, 2023

Feature Engineering and Model Experimentation MLOps: Involves improving ML performance through experiments and feature engineering. LLMOps: LLMs excel at learning from raw data, making feature engineering less relevant. The focus shifts towards prompt engineering and fine-tuning.

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Large Language Models DevOps Prompt Engineer Prompt Engineering 52

ODSC - Open Data Science

JANUARY 10, 2024

You will also become familiar with the concept of LLM as a reasoning engine that can power your applications, paving the way to a new landscape of software development in the era of Generative AI.

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Large Language Models LLM Deep Learning Data Science 52

TheSequence

NOVEMBER 12, 2023

📌 ML Engineering Event: Join Meta, PepsiCo, RiotGames, Uber & more at apply(ops) apply(ops) is in two days! SAVE MY SPOT 🔎 ML Research LLM Pruning Microsoft Research published a research paper proposing LoRAShear, a technique for pruning and recovering knowledge in LLMs.

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OpenAI Generative AI ML Prompt Engineer 64

Snorkel AI

JUNE 9, 2023

That means curating an optimized set of prompts and responses for instruction tuning as well as cultivating the right mix of pre-training data for self-supervision. Snorkel Foundry will allow customers to programmatically curate unstructured data to pre-train an LLM for a specific domain.

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Large Language Models Data Scientist Machine Learning Computer Vision 52

Snorkel AI

JUNE 9, 2023

That means curating an optimized set of prompts and responses for instruction tuning as well as cultivating the right mix of pre-training data for self-supervision. Snorkel Foundry will allow customers to programmatically curate unstructured data to pre-train an LLM for a specific domain.

Large Language Models 52

Large Language Models Data Scientist Machine Learning Computer Vision 52

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?

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LLM Data Scientist Algorithm Generative AI 102

AWS Machine Learning Blog

MAY 9, 2024

This includes implementation of industry best practice measures and industry frameworks, such as NIST , OWASP-LLM , OWASP-ML , MITRE Atlas. AI/ML Specialist Solutions Architect at AWS, based in Virginia, US. Vikram Elango is a Sr.

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ML Generative AI AI AI 125

The MLOps Blog

JUNE 27, 2023

The platform also offers features for hyperparameter optimization, automating model training workflows, model management, prompt engineering, and no-code ML app development. LLM training configurations. Guardrails: – Does pydantic-style validation of LLM outputs. recovery from node failures).

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Metadata Machine Learning Data Scientist Data Quality 134

AWS Machine Learning Blog

JANUARY 26, 2024

Understanding and addressing LLM vulnerabilities, threats, and risks during the design and architecture phases helps teams focus on maximizing the economic and productivity benefits generative AI can bring. This post provides three guided steps to architect risk management strategies while developing generative AI applications using LLMs.

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