Flipboard

JUNE 17, 2023

. • Quality: Across these several tasks, achieves accuracy competitive with task-specific approaches. Data-scalable: Learning efficiency increases as the number of task instances increases. They start by looking at the causes of the quality discrepancy.

LLM 145

LLM Large Language Models NLP Prompt Engineer 145

AWS Machine Learning Blog

NOVEMBER 15, 2024

This includes handling unexpected inputs, adversarial manipulations, and varying data quality without significant degradation in performance. To learn more about CoT and other prompt engineering techniques for Amazon Bedrock LLMs, see General guidelines for Amazon Bedrock LLM users.

Responsible AI 103

Responsible AI Prompt Engineer Prompt Engineering AI 103

Marktechpost

DECEMBER 8, 2024

Below are six ways discussed to prevent hallucinations in LLMs: Use High-Quality Data The use of high-quality data is one simple-to-do thing. The data that trains an LLM serves as its primary knowledge base, and any shortcomings in this dataset can directly lead to flawed outputs.

Prompt Engineer 111

Prompt Engineer Prompt Engineering Large Language Models LLM 111

The MLOps Blog

SEPTEMBER 26, 2024

TL;DR Hallucinations are an inherent feature of LLMs that becomes a bug in LLM-based applications. Causes of hallucinations include insufficient training data, misalignment, attention limitations, and tokenizer issues. What are LLM hallucinations? LLMs like GPT4o , Llama 3.1 , Claude 3.5 , or Gemini Pro 1.5

LLM 72

LLM Prompt Engineer Prompt Engineering Auto-complete 72

Snorkel AI

MARCH 4, 2025

Misaligned LLMs can generate harmful, unhelpful, or downright nonsensical responsesposing risks to both users and organizations. This is where LLM alignment techniques come in. LLM alignment techniques come in three major varieties: Prompt engineering that explicitly tells the model how to behave.

LLM 59

LLM Large Language Models Data Quality Prompt Engineer 59

Unite.AI

JANUARY 19, 2024

Taxonomy of Hallucination Mitigation Techniques Researchers have introduced diverse techniques to combat hallucinations in LLMs, which can be categorized into: 1. Prompt Engineering This involves carefully crafting prompts to provide context and guide the LLM towards factual, grounded responses.

Large Language Models 111

Large Language Models LLM Prompt Engineering Prompt Engineer 111

ODSC - Open Data Science

MARCH 5, 2025

Data Engineering: The infrastructure and pipeline work that supports AI and datascience. Data Management & Governance: Ensuring data quality, compliance, and security. Research & Project Management: Applying scientific methods and overseeing large-scale data initiatives.

Data Science 52

Data Science Software Engineer Data Scientist Machine Learning 52

AWS Machine Learning Blog

NOVEMBER 7, 2024

Prompt catalog – Crafting effective prompts is important for guiding large language models (LLMs) to generate the desired outputs. Prompt engineering is typically an iterative process, and teams experiment with different techniques and prompt structures until they reach their target outcomes.

Generative AI 104

Generative AI Machine Learning AI AI 104

The MLOps Blog

JUNE 27, 2023

W&B (Weights & Biases) W&B is a machine learning platform for your data science teams to track experiments, version and iterate on datasets, evaluate model performance, reproduce models, visualize results, spot regressions, and share findings with colleagues. Data monitoring tools help monitor the quality of the data.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

ODSC - Open Data Science

JULY 26, 2024

You’ll also be introduced to prompt engineering, a crucial skill for optimizing AI interactions. This two-hour session is crafted for AI practitioners who already possess a background in Python and familiarity with LangChain, aiming to elevate their skills in developing cutting-edge LLM agentic applications. Sign me up!

Data Scientist 52

Data Scientist Robotics Data Science Metadata 52

Heartbeat

JANUARY 9, 2024

We must create new tools and best practices to manage the LLM application lifecycle to address these issues. " The LLMOps Steps LLMs, sophisticated artificial intelligence (AI) systems trained on enormous text and code datasets, have changed the game in various fields, from natural language processing to content generation.

Large Language Models 52

Large Language Models Natural Language Processing LLM Machine Learning 52

AWS Machine Learning Blog

SEPTEMBER 14, 2023

The complexity of developing a bespoke classification machine learning model varies depending on a variety of aspects such as data quality, algorithm, scalability, and domain knowledge, to mention a few. He is currently focused on Generative AI, LLMs, prompt engineering, and scaling Machine Learning across enterprises.

Categorization 112

Categorization Machine Learning Data Scientist Natural Language Processing 112

Bugra Akyildiz

AUGUST 3, 2024

model size and data volume are significantly different as well as various strategies for data sampling. Articles Meta has announced the release of Llama 3.1 , latest and most capable open-source large language model (LLM) collection to date. Today, we had a special issue with Llama3.1

Neural Network 52

Neural Network Prompt Engineer Prompt Engineering Large Language Models 52

Bugra Akyildiz

SEPTEMBER 8, 2024

Some of the other key dimensions and themes that they have improved upon with regards to model development: Data Quality and Diversity: The quality and diversity of training data is crucial for model performance. 👷 The LLM Engineer focuses on creating LLM-based applications and deploying them.

LLM 52

LLM Large Language Models Neural Network Machine Learning 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

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

Topbots

SEPTEMBER 11, 2023

For example, if you are working on a virtual assistant, your UX designers will have to understand prompt engineering to create a natural user flow. All of this might require new skills on your team such as prompt engineering and conversational design. Prompting is great to get a head-start into pre-trained models.

UX Design 59

UX Design AI AI Automation 59

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.

Generative AI 135

Generative AI ML LLM AI 135

Unite.AI

JANUARY 22, 2025

It emerged to address challenges unique to ML, such as ensuring data quality and avoiding bias, and has become a standard approach for managing ML models across business functions. With the rise of large language models (LLMs), however, new challenges have surfaced.

Prompt Engineer 200

Prompt Engineer Prompt Engineering Large Language Models LLM 200

Unite.AI

SEPTEMBER 4, 2023

However, the world of LLMs isn't simply a plug-and-play paradise; there are challenges in usability, safety, and computational demands. In this article, we will dive deep into the capabilities of Llama 2 , while providing a detailed walkthrough for setting up this high-performing LLM via Hugging Face and T4 GPUs on Google Colab.

ChatGPT 284

ChatGPT Auto-complete Large Language Models LLM 284

Unite.AI

MARCH 13, 2024

Regardless of the approach, the training process for DSLMs involves exposing the model to large volumes of domain-specific textual data, such as academic papers, legal documents, financial reports, or medical records. Here are some notable examples: Legal Domain Law LLM Assistant SaulLM-7B Equall.ai

Natural Language Processing 201

Natural Language Processing Large Language Models Data Scarcity LLM 201

Unite.AI

FEBRUARY 4, 2025

As we enter the second wave of generative AI productization, companies are realizing that successfully implementing these technologies requires more than simply connecting an LLM to their data. While touted as a promising career path, prompt engineering is essentially recreating the same barriers we've struggled with in data analytics.

Prompt Engineering 189

Prompt Engineering Prompt Engineer AI AI 189

AWS Machine Learning Blog

SEPTEMBER 9, 2024

Generative artificial intelligence (AI) has revolutionized this by allowing users to interact with data through natural language queries, providing instant insights and visualizations without needing technical expertise. This can democratize data access and speed up analysis.

Software Architect 108

Software Architect Generative AI AI AI 108

ODSC - Open Data Science

SEPTEMBER 20, 2023

ODSC West Confirmed Sessions Pre-Bootcamp Warmup and Self-Paced Sessions Data Literacy Primer* Data Wrangling with SQL* Programming with Python* Data Wrangling with Python* Introduction to AI* Introduction to NLP Introduction to R Programming Introduction to Generative AI Large Language Models (LLMs) Prompt Engineering Introduction to Fine-Tuning LLMs (..)

Data Science 52

Data Science Large Language Models Machine Learning Python 52

Topbots

JUNE 6, 2023

In October 2022, I published an article on LLM selection for specific NLP use cases , such as conversation, translation and summarisation. Open-source competes with for-profits, spurring innovation in LLM efficiency and scaling. Generative AI pushes autoregressive models, while autoencoding models are waiting for their moment.

LLM 105

LLM ChatGPT Prompt Engineer Prompt Engineering 105