Snorkel AI

AUGUST 9, 2023

and Llama 2) and techniques, ultimately showing that a simple DistilBERT model developed with Snorkel Flow outperforms GPT-4 by 34 points out-of-the-box and by 15 points even after advanced prompt engineering. This model and prompt ended up with a token-level score of 49.2 Prompt-Engineered GPT 4.0 zero-shot, 58.9

LLM 52

LLM Prompt Engineer Prompt Engineering Artificial Intelligence 52

O'Reilly Media

OCTOBER 12, 2021

That could be what the future holds: an understanding of “prompt engineering” that lets us tell an AI system precisely what we want a program to do, rather than how to do it. Testing would become much more important, as would understanding precisely the business problem that needs to be solved. Repeat as needed.

Algorithm 120

Algorithm Prompt Engineer Prompt Engineering Automation 120

Marktechpost

JULY 30, 2023

Utilizing AI and machine learning algorithms, the system will create initial tagging structures and recommend relevant questions and answers based on the team’s most frequent areas of inquiry. Not stopping at integrating AI into the platform, Stack Overflow is actively nurturing a community of knowledge-sharing centered around AI.

Natural Language Processing 94

Natural Language Processing Prompt Engineer Prompt Engineering AI 94

Unite.AI

OCTOBER 16, 2023

The roadmap to LLM integration have three predominant routes: Prompting General-Purpose LLMs : Models like ChatGPT and Bard offer a low threshold for adoption with minimal upfront costs, albeit with a potential price tag in the long haul.

Large Language Models 189

Large Language Models LLM Machine Learning DevOps 189

Artificial Corner

AUGUST 3, 2023

Prompt engineering in under 10 minutes — theory, examples and prompting on autopilot Master the science and art of communicating with AI. Prompt engineering is the process of coming up with the best possible sentence or piece of text to ask LLMs, such as ChatGPT, to get back the best possible response.

Prompt Engineer 98

Prompt Engineer Prompt Engineering Large Language Models LLM 98

Unite.AI

DECEMBER 18, 2023

A critical facet of this workflow is the generation of embeddings from the transcripts, a step fundamental to the efficacy of our RAG-based tagging, classification models, and intricate summarizations. What truly sets this venture apart is the novelty and uncharted nature of the field.

LLM 130

LLM Data Analysis Prompt Engineer Prompt Engineering 130

AWS Machine Learning Blog

APRIL 24, 2024

of overall responses) can be addressed by user education and prompt engineering. First think through your answer inside of tags, then assign a score between 0.0 Answer the score inside of tags. Also provide the reason to give this score inside of tags. Some of the errors (about 10% of negative feedback and 7.5%

LLM 112

LLM AI AI Generative AI 112

Heartbeat

DECEMBER 7, 2023

Under the Hood: Node Traversal : The method begins by initializing an empty list, tables, to store nodes tagged as tables. Tag-Based Identification : During traversal, the method checks the tag attribute of each node. If a node has its tag set to 'table', it is considered a table and is added to the tables list.

LLM 52

LLM OpenAI Deep Learning Large Language Models 52

Heartbeat

AUGUST 25, 2023

Introduction Prompt Engineering is arguably the most critical aspect in harnessing the power of Large Language Models (LLMs) like ChatGPT. However; current prompt engineering workflows are incredibly tedious and cumbersome. Logging prompts and their outputs to .csv First install the package via pip.

Prompt Engineer 52

Prompt Engineer Prompt Engineering Large Language Models Metadata 52

deepsense.ai

FEBRUARY 6, 2024

The entire process can be further automated incorporating automatic image tagging using modules like RAM or Tag2Text. Grounded SAM provides many other nice features, like inpainting or voice-based prompts, and supports various versions of SAM, such as EfficientSAM and EdgeSAM. The first concept is prompt engineering.

Prompt Engineer 82

Prompt Engineer Prompt Engineering NLP Computer Vision 82

AWS Machine Learning Blog

OCTOBER 6, 2023

Furthermore, we discuss the diverse applications of these models, focusing particularly on several real-world scenarios, such as zero-shot tag and attribution generation for ecommerce and automatic prompt generation from images. This is where the power of auto-tagging and attribute generation comes into its own.

Generative AI 99

Generative AI Prompt Engineer Prompt Engineering Computer Vision 99

Mlearning.ai

FEBRUARY 26, 2024

Post-Retrieval Next, the RAG model augments the user input (or prompts) by adding the relevant retrieved data in context (query + context). This step uses prompt engineering techniques to communicate effectively with the LLM. Adding Metadata Adding metadata, such as concept and level tags, to improve the quality of indexed data.

Metadata 52

Metadata Large Language Models LLM Neural Network 52

AssemblyAI

JANUARY 19, 2023

Prepending data:image/png;base64, to the string lets the browser know that the <img> tag in the HTML file contains a raw image rather than a URL at which it can find and fetch an image. What is prompt engineering? How does DALL-E 2 work? How does Imagen work? What is classifier-free guidance?

Python 130

Python Prompt Engineer Prompt Engineering Chatbots 130

AWS Machine Learning Blog

MAY 15, 2024

This post demonstrates how to use advanced prompt engineering to control an LLM’s behavior and responses. Ref ExamGenTG Chain-of-Thought (CoT) Prompting Before we embark on constructing the app, let’s delve into prompt engineering. The 200,000 tokens supported by Anthropic Claude v2.1

Prompt Engineer 85

Prompt Engineer Prompt Engineering Generative AI Python 85

AWS Machine Learning Blog

MARCH 13, 2024

Use LLM prompt engineering to accommodate customized policies The pre-trained Toxicity Detection models from Amazon Transcribe and Amazon Comprehend provide a broad toxicity taxonomy, commonly used by social platforms for moderating user-generated content in audio and text formats. Respond in the tag with either 'Y' or 'N'.

LLM 110

LLM Natural Language Processing Prompt Engineer Prompt Engineering 110

Heartbeat

NOVEMBER 22, 2023

tags : (Optional) List of tags to associate with the evaluation. Parameters: prediction : The output string from the first model. prediction_b : The output string from the second model. input : (Optional) The input or task string that led to the predictions. reference : (Optional) A reference string for comparison.

LLM 52

LLM Explainability Metadata Deep Learning 52

AWS Machine Learning Blog

MAY 13, 2024

In this part of the blog series, we review techniques of prompt engineering and Retrieval Augmented Generation (RAG) that can be employed to accomplish the task of clinical report summarization by using Amazon Bedrock. It can be achieved through the use of proper guided prompts. There are many prompt engineering techniques.

Generative AI 104

Generative AI Prompt Engineer Prompt Engineering LLM 104

Snorkel AI

FEBRUARY 13, 2024

link] With a little prompt engineering (encouraging the LLM to behave as an expert in banking and giving one example per label), the team boosted the PaLM 2’s F1 score to 69. That’s much closer to production-grade performance, but not close enough.

LLM 52

LLM Data Scientist Neural Network Data Science 52

Snorkel AI

FEBRUARY 13, 2024

link] With a little prompt engineering (encouraging the LLM to behave as an expert in banking and giving one example per label), the team boosted the PaLM 2’s F1 score to 69. That’s much closer to production-grade performance, but not close enough.

LLM 52

LLM Data Scientist Neural Network Data Science 52

AWS Machine Learning Blog

MARCH 15, 2024

client(service_name='bedrock-runtime') Let’s start by working on the intent validator prompt template. This is an iterative process, but thanks to Anthropic’s prompt engineering guide, you can quickly create a prompt that can accomplish the task. Always put your response to the Human within the Response tags.

Generative AI 122

Generative AI Prompt Engineer Prompt Engineering LLM 122

Flipboard

DECEMBER 6, 2023

We discuss model selection and prompt engineering and optimization later in this post, but it’s worth noting that for the query generation stage, we noticed that Claude Instant was able to produce comparable results, especially when the user question is well phrased and not as sophisticated.

Chatbots 130

Chatbots LLM Prompt Engineer Prompt Engineering 130

Marktechpost

OCTOBER 23, 2023

However, a significant limitation has persisted in effectively communicating with these advanced T2I models using natural language descriptions, making it challenging for users to obtain engaging images without expertise in prompt engineering.

Large Language Models 116

Large Language Models Prompt Engineer Prompt Engineering LLM 116

AWS Machine Learning Blog

NOVEMBER 22, 2023

Use the “Generative AI” tag as you are browsing the session catalog to find them. Hear best practices for using unstructured (video, image, PDF), semi-structured (Parquet), and table-formatted (Iceberg) data for training, fine-tuning, checkpointing, and prompt engineering. Reserve your seat now!

ML 113

ML Generative AI Prompt Engineer Prompt Engineering 113

AWS Machine Learning Blog

SEPTEMBER 14, 2023

It can be difficult to find insights from this data, particularly if efforts are needed to classify, tag, or label it. As human tagging or categorization is no longer necessary, this can save businesses a lot of time, money, and labor. Amazon Comprehend custom classification can be useful in this situation. Choose Submit.

Categorization 97

Categorization Machine Learning Data Scientist Natural Language Processing 97

Unite.AI

JULY 27, 2023

Effectual prompt engineering goes beyond mere creation; it encompasses best practices. Prompts should offer clarity, and be succinct, yet provide the AI with enough guidance without excessive prescription. The post Mastering AI Art: A Concise Guide to Midjourney and Prompt Engineering appeared first on Unite.AI.

Prompt Engineer 246

Prompt Engineer Prompt Engineering AI AI 246

Heartbeat

FEBRUARY 8, 2024

Tracking and Monitoring with Comet When creating applications with LLMs, most of the time is spent on prompt engineering rather than training the models. Comet has a rich set of features for LLMOps: LLM Projects: It is designed for analyzing prompts, responses, and chaining. This has introduced a new area of expertise: LLMOps.

Conversational AI 52

Conversational AI Chatbots LLM Prompt Engineer 52

Heartbeat

SEPTEMBER 19, 2023

Comet’s LLMOps tool provides an intuitive and responsive view of our prompt history. Prompt Playground: With the LLMOps tool comes the new Prompt Playground, which allows Prompt Engineers to iterate quickly with different Prompt Templates and understand the impact on different contexts.

Large Language Models 52

Large Language Models Metadata LLM Data Scientist 52

John Snow Labs

OCTOBER 12, 2023

Zero-Shot NER Prompts are now available for FREE Prompt engineering is gaining traction as a fast-evolving discipline that aims to guide advanced language models like GPT-3 to generate precise and intended results, such as answering queries or constructing meaningful narratives. We have now resolved this issue.

NLP 52

NLP Auto-complete Auto-classification Prompt Engineer 52

Unite.AI

JUNE 15, 2023

Well, we also Triage, which is the name of our second product, route issues, tag them, make sure they get to the right agent in the right channel, the right time, so you can deploy that. And then you can leverage all of that correctness through prompt engineering, through fine-tuning, which actually brings the hallucination problem down.

Large Language Models 246

Large Language Models Generative AI Chatbots Auto-complete 246

deepsense.ai

MAY 26, 2023

The resulting canonical form is then passed to an intelligence processing block – AI reads chunks of text, creating a summary and tags to make efficient searches possible – which calculates so-called embedding vectors. Each uploaded document has 3 tags useful for searching, clustering and prompt tuning.

OpenAI 52

OpenAI Neural Network Prompt Engineer Prompt Engineering 52

Heartbeat

OCTOBER 19, 2023

Users can gain deep insights into the evolution of their prompts and responses. Prompt Playground Adventure: Within the LLMOps toolkit lies the innovative Prompt Playground, a dynamic space where Prompt Engineers can embark on expedited explorations. Step 1: Login to the Comet website.

Large Language Models 52

Large Language Models LLM Metadata Deep Learning 52

Snorkel AI

DECEMBER 14, 2023

Errors on rare slices of data can have significant business consequences—NSFW tags on social platforms, for example. Many organizations pursue model-centric iteration, such as hyper-parameter tuning and prompt engineering. Additionally, these data slices change with world events and business needs over time.

Categorization 64

Categorization Prompt Engineer Prompt Engineering Large Language Models 64

Snorkel AI

DECEMBER 14, 2023

Errors on rare slices of data can have significant business consequences—NSFW tags on social platforms, for example. Many organizations pursue model-centric iteration, such as hyper-parameter tuning and prompt engineering. Additionally, these data slices change with world events and business needs over time.

Categorization 59

Categorization Prompt Engineer Prompt Engineering Large Language Models 59

AWS Machine Learning Blog

APRIL 25, 2023

Infrastructure settings cover the network configuration, IAM roles, Amazon Simple Storage Service (Amazon S3) folder for input, output data, and tags. He is currently focused on generative AI, LLMs, prompt engineering, large model inference optimization, and scaling ML across enterprises. You only need to set it up one time.

Machine Learning 79

Machine Learning Data Scientist Python ML 79

Heartbeat

DECEMBER 13, 2023

', args_schema=None, return_direct=False, verbose=False, callbacks=None, callback_manager=None, tags=None, metadata=None, handle_tool_error=False, api_wrapper=WikipediaAPIWrapper(wiki_client=<module 'wikipedia' from '/usr/local/lib/python3.10/dist-packages/wikipedia/__init__.py'>, Input should be a search query.',

LLM 52

LLM Metadata Deep Learning Automation 52

Snorkel AI

MAY 25, 2023

In the fine-tuning approach, you would use a dataset with labeled examples of the kind of information you want to extract, for example, a dataset that has person names annotated with a [PER] tag. Then you could use the fine-tuned model to predict the tags for new texts.

Large Language Models 52

Large Language Models BERT Neural Network LLM 52

Snorkel AI

MAY 25, 2023

In the fine-tuning approach, you would use a dataset with labeled examples of the kind of information you want to extract, for example, a dataset that has person names annotated with a [PER] tag. Then you could use the fine-tuned model to predict the tags for new texts.

Large Language Models 52

Large Language Models BERT Neural Network LLM 52