Marktechpost

FEBRUARY 15, 2024

Generating mistakes in a zero-shot fashion and guiding the model to analyze these errors alongside the correct answers fosters a deeper understanding of the task at hand. AI aims for accurate and efficient learning. Traditional approaches have largely centered on models learning from correct examples.

Large Language Models 127

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Marktechpost

DECEMBER 9, 2023

In vision, the Segment Anything Model (SAM) has achieved remarkable success, attaining cutting-edge results in numerous image segmentation tasks, including zero-shot object proposal generation, zero-shot instance segmentation, and edge detection, among other practical uses.

Categorization 122

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Towards AI

AUGUST 9, 2023

An introduction to the core ideas and approaches to move from unimodality to multimodal LLMs LLMs have shown promising results on both zero-shot and few-shot learning on many natural language tasks. inside the prompt to feed to the LLM. Comparing instruction tuning with pre-train–finetune and prompting. [20]

Explainability 93

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AssemblyAI

SEPTEMBER 29, 2023

For information on what DALL-E 3 is, how it works, and the differences between DALL-E 3 and DALL-E 2, jump down to this section. At the highest level, DALL-E 2's works very simply: First, a text prompt is input into a text encoder that is trained to map the prompt to a representation space.

Deep Learning 290

Deep Learning ChatGPT OpenAI Large Language Models 290

ODSC - Open Data Science

DECEMBER 6, 2023

Prompt engineering has become the Wild West of tech skills. Though the field is still in its infancy, there’s a growing list of resources one can utilize if you’re interested in becoming a prompt engineer. You will learn what generative AI is, how it is used, and how it differs from traditional machine learning methods.

Prompt Engineer 98

Prompt Engineer Prompt Engineering Generative AI Software Development 98

Heartbeat

APRIL 10, 2023

A Lego design in the style of Refik Anadol, representing a colorful Istanbul like pixels moving in the flow of waves.” — — Created by Midjourney, prompted by Yavuz Kömeçoğlu ChatGPT has been tested in many different scenarios and has been able to show very high performance in important tests. What is Prompt Engineering?

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Prompt Engineer Prompt Engineering OpenAI ChatGPT 83

Viso.ai

MARCH 19, 2024

Grounded Segment Anything innovatively combines Grounding DINO’s zero-shot detection capabilities with Segment Anything’s versatile image segmentation. This integration enables detecting and segmenting objects within images using textual prompts. Vision Transformers (ViTs) form the backbone of this model.

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AWS Machine Learning Blog

NOVEMBER 15, 2023

Prompt engineering has become an essential skill for anyone working with large language models (LLMs) to generate high-quality and relevant texts. Although text prompt engineering has been widely discussed, visual prompt engineering is an emerging field that requires attention.

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Prompt Engineer Prompt Engineering Computer Vision Machine Learning 92

AWS Machine Learning Blog

AUGUST 14, 2023

The BloomZ 176B model, one of the largest publicly available models, is a state-of-the-art instruction-tuned model that can perform various in-context few-shot learning and zero-shot learning NLP tasks. Amazon SageMaker JumpStart is a machine learning (ML) hub offering algorithms, models, and ML solutions.

NLP 71

NLP Robotics Prompt Engineer Prompt Engineering 71

Towards AI

FEBRUARY 13, 2023

What is NLP? What is Transformers? What is NLP? Cool, we learned what NLP is in this section. Let’s go ahead and have a look at what the Transformers library is. What is the Transformers library? You may ask what pre-trained models are. Nice, we looked at what the Transformers library is.

Auto-classification 93

Auto-classification NLP Auto-complete Computer Vision 93

Marktechpost

JULY 14, 2023

For example, they can answer questions like “ Suppose you have a series of numbers: 2, 4, 6, 8, 10, … What is the next number in the sequence? Here, before sending your main request, you give LLM a set of example question-answers so that it can learn what you really want to ask. This is where Active Prompting comes into play.

Large Language Models 97

Large Language Models LLM Deep Learning AI 97

Snorkel AI

AUGUST 31, 2023

This piece will discuss advancements in how to use FMs to improve themselves (or other models like the multimodal zero-shot model CLIP) as well as how to distill typically large foundation models into smaller, more easily deployable versions. The prompting stage asks the model for output. Instead, Snorkel affiliate Prof.

Data Scientist 59

Data Scientist Artificial Intelligence Artificial Intelligence Large Language Models 59

Snorkel AI

AUGUST 31, 2023

This piece will discuss advancements in how to use FMs to improve themselves (or other models like the multimodal zero-shot model CLIP) as well as how to distill typically large foundation models into smaller, more easily deployable versions. The prompting stage asks the model for output. Instead, Snorkel affiliate Prof.

Data Scientist 52

Data Scientist Artificial Intelligence Artificial Intelligence Large Language Models 52

Heartbeat

AUGUST 4, 2023

“Our intelligence is what makes us human, and AI is an extension of that quality.” — Yann LeCun A new milestone is recorded almost every week as we experience the renaissance of artificial intelligence (AI) research and development. Performing this process well is now defined as a profession: prompt engineering.

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Prompt Engineer Prompt Engineering Computer Vision Deep Learning 52

Mlearning.ai

MAY 28, 2023

It was not a very advanced workshop but we had the opportunity to work with film cameras and I would do anything to get my hands on those cameras just like any other student with zero budget. One of them is Inner Cosmos with David Eagleman. He is a famous neuroscientist and author from Standford University.

Artificial Intelligence 98

Artificial Intelligence Artificial Intelligence AI AI 98

Topbots

APRIL 11, 2023

As a testament to the remarkable progress in this area, several groundbreaking language models have emerged in recent years, pushing the boundaries of what machines can understand and generate. What is the goal? What are the results? They suggested that scaling up language models can improve task-agnostic few-shot performance.

NLP 98

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AssemblyAI

DECEMBER 23, 2022

Alignment, on the other hand, is concerned with what we actually want the model to do versus what it is being trained to do. ChatGPT is the latest language model from OpenAI and represents a significant improvement over its predecessor GPT-3. We will conclude by looking at some of the limitations of this methodology.

ChatGPT 246

ChatGPT Large Language Models OpenAI Algorithm 246

Marktechpost

DECEMBER 5, 2023

Their ability to utilize the strength of Natural Language Processing, Generation, and Understanding by generating content, answering questions, summarizing text, and so on have made LLMs the talk of the town in the last few months. What are Small Language Models?

BERT 134

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Snorkel AI

JANUARY 18, 2023

Today, I’ll focus on one paper that you and the team recently posted called “ Language Models in the Loop: Incorporating Prompting into Weak Supervision.” I think you can find it, but it’s basically just going over some prompting methods. Below follows a transcript of their conversation, lightly edited for readability.

Neural Network 52

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Marktechpost

JANUARY 14, 2024

The answer generation process of GRANOLA has two steps – first, a description of the answer entity along with any entity appearing in the question is obtained using an external knowledge graph (KG), and second, an LLM is zero-shot prompted to create an ordered list of answers of varying levels of granularity.

Large Language Models 101

Large Language Models Natural Language Processing AI AI 101

Towards AI

JUNE 21, 2023

Below are some key concepts and topics included in the course: From Zero to Hero with LangChain: A comprehensive introduction to the essential concepts, set up, and usage of Large Language Models (LLMs), LangChain, and Deep Lake. Learning How to Prompt: Gain proficiency in prompt engineering techniques and apply them in practice.

Large Language Models 88

Large Language Models Prompt Engineer Prompt Engineering Automation 88

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. The leap forward has been astonishing—even for those who have built AI systems for years. Extremely durable and very easy to clean.

LLM 52

LLM Prompt Engineer Prompt Engineering Artificial Intelligence 52

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. The leap forward has been astonishing—even for those who have built AI systems for years. Extremely durable and very easy to clean.

LLM 52

LLM Prompt Engineer Prompt Engineering Artificial Intelligence 52

Snorkel AI

SEPTEMBER 20, 2023

Data scientists feed the model a collection of prompts and expected responses. The model learns the gaps between what it currently produces and what the training pipeline expected and adjusts its “attention” to specific features and patterns. The answer is “both.” Lack of domain knowledge.

Data Science 59

Data Science Artificial Intelligence Artificial Intelligence NLP 59

Google Research AI blog

AUGUST 18, 2023

Posted by Ziniu Hu, Student Researcher, and Alireza Fathi, Research Scientist, Google Research, Perception Team There has been great progress towards adapting large language models (LLMs) to accommodate multimodal inputs for tasks including image captioning , visual question answering (VQA) , and open vocabulary recognition. WebGPT and ReAct ).

Large Language Models 92

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Towards AI

APRIL 27, 2023

What is the problem statement? They are not aware of what is in the data and do not have strategies in place for what to do with it. Data can reveal insights into what your customers want! Once a list of potential use cases is identified, it takes months to just finalize what use case to pursue. blah blah…….

Automation 88

Automation Auto-complete Computer Vision ML Engineer 88

AWS Machine Learning Blog

APRIL 8, 2024

Unlocking accurate and insightful answers from vast amounts of text is an exciting capability enabled by large language models (LLMs). When building LLM applications, it is often necessary to connect and query external data sources to provide relevant context to the model.

LLM 101

LLM Large Language Models Machine Learning Data Ingestion 101

Towards AI

DECEMBER 10, 2023

What this post doesn’t do. In addition, LLMs in zero-shot fashion are known to be misaligned (language models may understand the task differently) and produce hallucinations. Tanuki is an open-source library for easy and seamless building of LLM-powered apps with little to no required LLM or prompting knowledge.

LLM 89

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ODSC - Open Data Science

DECEMBER 8, 2023

So let’s take a look at these advancements, who pushed them forward, and what the year entails. It achieves superior zero-, one-, and few-shot learning accuracies on several NLP benchmarks. In the early months of the year, Google AI took center stage with the release of PaLM 2 , a massive LLM with 540B parameters.

Large Language Models 52

Large Language Models LLM NLP Data Science 52

AWS Machine Learning Blog

OCTOBER 31, 2023

This post was co-written with Anthony Medeiros, Manager of Solutions Engineering and Architecture for North America Artificial Intelligence, and Blake Santschi, Business Intelligence Manager, from Schneider Electric. In particular, they are routinely used to store information related to customer accounts.

LLM 103

LLM Large Language Models ML Machine Learning 103

Unite.AI

AUGUST 1, 2023

GPT-4: Prompt Engineering ChatGPT has transformed the chatbot landscape, offering human-like responses to user inputs and expanding its applications across domains – from software development and testing to business communication, and even the creation of poetry. Prompt 1 : “Tell me about Convolutional Neural Networks.”

Prompt Engineer 246

Prompt Engineer Prompt Engineering ChatGPT Convolutional Neural Networks 246

Sebastian Ruder

JUNE 6, 2022

With 1032 accepted papers (604 long, 97 short, 331 in Findings), this post can only offer a glimpse of the diverse research presented at the conference—biased towards my research interests. Language diversity and multimodality Panelists and their spoken languages at the ACL 2022 keynote panel on supporting linguistic diversity.

NLP 52

NLP Natural Language Processing Computational Linguistics Neural Network 52

Snorkel AI

OCTOBER 6, 2023

What other tooling do you need to bring it into production? Preparing a corpus of prompts and responses for instruction tuning. Customizing LLMs is imperative for enterprises Large language models make for exciting demos, but solve few—if any—business problems off the shelf. How do you host this enormous model?

Large Language Models 69

Large Language Models LLM Data Mining Data Science 69

Snorkel AI

JANUARY 4, 2023

An exciting chat between Alex Ratner, co-founder and CEO, Snorkel AI, and Simran Arora, ML researcher, Stanford University, about new research from Hazy Research on how prompting methods enable a 6B parameter model to outperform the 175B parameter GPT-3. But writing these natural language prompts can be quite a brittle process.

Prompt Engineer 52

Prompt Engineer Prompt Engineering Large Language Models OpenAI 52

Unite.AI

MARCH 25, 2024

Over the past few years, T2V or Text to Video models have demonstrated remarkable success in generating vivid and diverse videos using textual prompts, and this demonstration of T2V models is what forms the foundation for the DynamiCrafter framework. So let’s get started.

Computer Vision 130

Computer Vision Artificial Intelligence Artificial Intelligence AI 130

Mlearning.ai

AUGUST 8, 2023

The objective of Grounding DINO (published in this paper in March 2023) was to develop a strong system to detect arbitrary objects specified by human language inputs without the need to retrain the model, also known as zero-shot detection. The model can identify and detect any object simply by providing a text prompt.

Algorithm 52

Algorithm AI AI Computer Vision 52

Heartbeat

JANUARY 29, 2024

What is Meta-Learning? The model learns from this meta-dataset and generalizes its knowledge to novel functions with only a few examples, sometimes referred to as few-shot learning. Among the myriad breakthroughs in this field, Meta-Learning is pushing the boundaries of machine learning.

Machine Learning 52

Machine Learning Neural Network Natural Language Processing Algorithm 52