Marktechpost

MAY 30, 2024

Google plays a crucial role in advancing AI by developing cutting-edge technologies and tools like TensorFlow, Vertex AI, and BERT. Transformer Models and BERT Model This course introduces the Transformer architecture and the BERT model, covering components like the self-attention mechanism.

Artificial Intelligence 131

Artificial Intelligence Artificial Intelligence BERT Computer Vision 131

ODSC - Open Data Science

JANUARY 29, 2024

The role of prompt engineer has attracted massive interest ever since Business Insider released an article last spring titled “ AI ‘Prompt Engineer Jobs: $375k Salary, No Tech Backgrund Required.” It turns out that the role of a Prompt Engineer is not simply typing questions into a prompt window.

Prompt Engineering 52

Prompt Engineering Prompt Engineer Data Science LLM 52

Marktechpost

APRIL 16, 2024

LangChain is an open-source framework that allows developers to build LLM-based applications easily. It provides for easily connecting LLMs with external data sources to augment the capabilities of these models and achieve better results. It teaches how to build LLM-powered applications using LangChain using hands-on exercises.

Large Language Models 103

Large Language Models Auto-complete Prompt Engineering Prompt Engineer 103

Unite.AI

JANUARY 23, 2024

Large language models (LLMs) have exploded in popularity over the last few years, revolutionizing natural language processing and AI. From chatbots to search engines to creative writing aids, LLMs are powering cutting-edge applications across industries. Prompt engineering is crucial to steering LLMs effectively.

Large Language Models 100

Large Language Models Prompt Engineering Prompt Engineer LLM 100

Marktechpost

APRIL 1, 2024

Although large language models (LLMs) had been developed prior to the launch of ChatGPT, the latter’s ease of accessibility and user-friendly interface took the adoption of LLM to a new level. It provides codes for working with various models, such as GPT-4, BERT, T5, etc., and explains how they work.

ChatGPT 115

ChatGPT Large Language Models Prompt Engineer Prompt Engineering 115

Towards AI

DECEMBER 28, 2023

Here are 11 pillars for building expertise in GenAI: Basics of Python- Python serves as a prominent programming language for working with large language models (LLMs) due to its versatility, extensive libraries, and community support. Learning the basics of transformers which is the core of LLM is imperative for a professional.

Large Language Models 122

Large Language Models Natural Language Processing Deep Learning Prompt Engineering 122

AWS Machine Learning Blog

JUNE 25, 2024

Whether you’re a developer seeking to incorporate LLMs into your existing systems or a business owner looking to take advantage of the power of NLP, this post can serve as a quick jumpstart. Operational efficiency Uses prompt engineering, reducing the need for extensive fine-tuning when new categories are introduced.

Automation 126

Automation Prompt Engineer Prompt Engineering Categorization 126

Towards AI

JANUARY 30, 2024

The 12 groups are as follows — Types of Models Common LLM Terms LLM Lifecycle Stages LLM Evaluations LLM Architecture Retrieval Augmented Generation (RAG) LLM Agents LMM Architecture Cost & Efficiency LLM Security Deployment & Inference A list of providers supporting LLMOps Like the generative AI space, this taxonomy is also evolving.

Generative AI 112

Generative AI LLM Prompt Engineer Prompt Engineering 112

Ehud Reiter

AUGUST 25, 2024

” BERT/BART/etc can be used in data-to-text, but may not be best approach Around 2020 LSTMs got replaced by fine-tuned transformer language models such as BERT and BART. This is a much better way to build data-to-text and other NLG systems, and I know of several production-quality NLG systems built using BART (etc).

BERT 133

BERT NLP Natural Language Processing Prompt Engineer 133

The MLOps Blog

SEPTEMBER 26, 2024

TL;DR Hallucinations are an inherent feature of LLMs that becomes a bug in LLM-based applications. Effective mitigation strategies involve enhancing data quality, alignment, information retrieval methods, and prompt engineering. What are LLM hallucinations? In 2022, when GPT-3.5

LLM 72

LLM Prompt Engineer Prompt Engineering Auto-complete 72

Unite.AI

AUGUST 28, 2023

Systems like ChatGPT by OpenAI, BERT, and T5 have enabled breakthroughs in human-AI communication. Deep learning techniques further enhanced this, enabling sophisticated image and speech recognition. Transformers and Advanced NLP Models : The introduction of transformer architectures revolutionized the NLP landscape.

Auto-complete 240

Auto-complete ChatGPT Large Language Models Neural Network 240

AWS Machine Learning Blog

DECEMBER 22, 2023

We start off with a baseline foundation model from SageMaker JumpStart and evaluate it with TruLens , an open source library for evaluating and tracking large language model (LLM) apps. These functions can be implemented in several ways, including BERT-style models, appropriately prompted LLMs, and more.

LLM 119

LLM Large Language Models BERT Prompt Engineer 119

AssemblyAI

MAY 23, 2023

Large Language Models In recent years, LLM development has seen a significant increase in size, as measured by the number of parameters. This trend started with models like the original GPT and ELMo, which had millions of parameters, and progressed to models like BERT and GPT-2, with hundreds of millions of parameters.

Large Language Models 130

Large Language Models Neural Network LLM Chatbots 130

Snorkel AI

FEBRUARY 13, 2024

Large language model distillation isolates LLM performance on a specific task and mirrors its functionality in a smaller format. LLM distillation basics Multi-billion parameter language models pre-trained on millions of documents have changed the world. What is LLM distillation? How does LLM distillation work?

LLM 52

LLM Data Scientist Neural Network Data Science 52

Snorkel AI

FEBRUARY 13, 2024

Large language model distillation isolates LLM performance on a specific task and mirrors its functionality in a smaller format. LLM distillation basics Multi-billion parameter language models pre-trained on millions of documents have changed the world. What is LLM distillation? How does LLM distillation work?

LLM 52

LLM Data Scientist Neural Network Data Science 52

Mlearning.ai

JULY 24, 2023

In Generative AI projects, there are five distinct stages in the lifecycle, centred around a Large Language Model 1️⃣ Pre-training : This involves building an LLM from scratch. The likes of BERT, GPT4, Llama 2, have undergone pre-training on a large corpus of data. The model generates a completion on the prompt.

Generative AI 52

Generative AI Prompt Engineering Prompt Engineer Large Language Models 52

deepsense.ai

NOVEMBER 9, 2024

On the other hand, the more demanding the task – the higher the risk of LLM hallucinations. In this article, you’ll find: what the problem with hallucination is, which techniques we use to reduce them, how to measure hallucinations using methods such as LLM-as-a-judge tips and tricks from my experience as an experienced data scientist.

Prompt Engineering 59

Prompt Engineering Prompt Engineer LLM ChatGPT 59

Bugra Akyildiz

FEBRUARY 9, 2025

It does a deep dive into two reinforcement learning algorithms used in training large language models (LLMs): Proximal Policy Optimization (PPO) Group Relative Policy Optimization (GRPO) LLM Training Overview The training of LLMs is divided into two phases: Pre-training: The model learns next token prediction using large-scale web data.

LLM 52

LLM Deep Learning Algorithm BERT 52

Snorkel AI

AUGUST 17, 2023

Users can easily constrain an LLM’s output with clever prompt engineering. However, this approach comes with one big downside: the prompt must include at least one example for each potential output. Sends the prompt to the LLM. In-context learning. Over thousands of executions, those extra tokens can add up.

Generative AI 52

Generative AI BERT LLM Prompt Engineer 52

Snorkel AI

AUGUST 17, 2023

Users can easily constrain an LLM’s output with clever prompt engineering. However, this approach comes with one big downside: the prompt must include at least one example for each potential output. Sends the prompt to the LLM. In-context learning. Over thousands of executions, those extra tokens can add up.

Generative AI 52

Generative AI BERT LLM Prompt Engineer 52

Snorkel AI

AUGUST 17, 2023

Users can easily constrain an LLM’s output with clever prompt engineering. However, this approach comes with one big downside: the prompt must include at least one example for each potential output. Sends the prompt to the LLM. In-context learning. Over thousands of executions, those extra tokens can add up.

Generative AI 52

Generative AI BERT LLM Prompt Engineer 52

ODSC - Open Data Science

NOVEMBER 8, 2023

LLM Basics First and foremost, you need to understand the basics of generative AI and LLMs, such as key terminology, uses, potential issues, and primary frameworks. Prompt Engineering Another buzzword you’ve likely heard of lately, prompt engineering means designing inputs for LLMs once they’re developed.

Generative AI 52

Generative AI Prompt Engineering Prompt Engineer LLM 52

Heartbeat

MARCH 19, 2024

Introduction Large language models (LLMs) have emerged as a driving catalyst in natural language processing and comprehension evolution. LLM use cases range from chatbots and virtual assistants to content generation and translation services. Similarly, Google utilizes LLMOps for its next-generation LLM, PaLM 2.

Large Language Models 52

Large Language Models Prompt Engineering Prompt Engineer Natural Language Processing 52

AWS Machine Learning Blog

MAY 31, 2023

In 2018, BERT-large made its debut with its 340 million parameters and innovative transformer architecture, setting the benchmark for performance on NLP tasks. AI21 Jurassic-2 Jumbo Instruct Jurassic-2 Jumbo Instruct is an LLM by AI21 Labs that can be applied to any language comprehension or generation task.

Automation 97

Automation Python Machine Learning BERT 97

Snorkel AI

MAY 25, 2023

At inference time, users provide “prompts” to the LLM—snippets of text that the model uses as a jumping-off point. First, the model converts each token in the prompt into its embedding. By making BERT bidirectional, it allowed the inputs and outputs to take each others’ context into account. The new tool caused a stir.

Large Language Models 52

Large Language Models BERT Neural Network LLM 52

Snorkel AI

MAY 25, 2023

At inference time, users provide “prompts” to the LLM—snippets of text that the model uses as a jumping-off point. First, the model converts each token in the prompt into its embedding. By making BERT bidirectional, it allowed the inputs and outputs to take each others’ context into account. The new tool caused a stir.

Large Language Models 52

Large Language Models BERT Neural Network LLM 52

Unite.AI

AUGUST 4, 2023

This, coupled with the challenges of understanding AI concepts and complex algorithms, contributes to the learning curve associated with developing applications using LLMs. Nevertheless, the integration of LLMs with other tools to form LLM-powered applications could redefine our digital landscape.

Prompt Engineering 245

Prompt Engineering Prompt Engineer Python NLP 245

Heartbeat

AUGUST 2, 2023

Introduction to LLMs LLM in the sphere of AI Large language models (often abbreviated as LLMs) refer to a type of artificial intelligence (AI) model typically based on deep learning architectures known as transformers. It has become the backbone of many successful language models, like GPT-3, BERT, and their variants.

Large Language Models 52

Large Language Models Prompt Engineering Prompt Engineer ChatGPT 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

Heartbeat

OCTOBER 5, 2023

The emergence of Large Language Models (LLMs) like OpenAI's GPT , Meta's Llama , and Google's BERT has ushered in a new era in this field. These LLMs can generate human-like text, understand context, and perform various Natural Language Processing (NLP) tasks.

Large Language Models 52

Large Language Models DevOps Machine Learning Prompt Engineer 52

ODSC - Open Data Science

NOVEMBER 19, 2024

While LLMs excel in generating text, they face challenges in producing natural, conversational voice interactions. The workshop covered strategies to enhance LLM-powered voice agents, enabling them to handle interruptions, improvise, and maintain conversation flow.

Deep Learning 52

Deep Learning Data Science Neural Network BERT 52

The MLOps Blog

FEBRUARY 15, 2024

Due to the rise of LLMs and the shift towards pre-trained models and prompt engineering, specialists in traditional NLP approaches are particularly at risk. Even small and relatively weaker LLMs like DistilGPT2 and t5-small have surpassed classical NLP models in understanding context and generating coherent text.

NLP 59

NLP Natural Language Processing Data Scientist Software Engineer 59

Snorkel AI

MARCH 2, 2023

Ali Arsanjani, director of cloud partner engineering at Google Cloud , presented a talk entitled “Challenges and Ethics of DLM and LLM Adoption in the Enterprise” at Snorkel AI’s recent Foundation Model Virtual Summit. Really quickly, LLMs can do many things. Then comes prompt engineering.

Large Language Models 52

Large Language Models Prompt Engineer Prompt Engineering Neural Network 52

Snorkel AI

MARCH 2, 2023

Ali Arsanjani, director of cloud partner engineering at Google Cloud , presented a talk entitled “Challenges and Ethics of DLM and LLM Adoption in the Enterprise” at Snorkel AI’s recent Foundation Model Virtual Summit. Really quickly, LLMs can do many things. Then comes prompt engineering.

Large Language Models 52

Large Language Models Prompt Engineer Prompt Engineering Neural Network 52

Heartbeat

NOVEMBER 17, 2023

Exact Match Probably the simplest ways to evaluate an LLM or runnable’s string output against a reference label is by a simple string equivalence. Considerations for Choosing a Distance Metric for Text Embeddings: Scale or Magnitude : Embeddings from models like Word2Vec, FastText, BERT, and GPT are often normalized to unit length.

Data Scientist 52

Data Scientist Deep Learning Algorithm BERT 52

Snorkel AI

OCTOBER 17, 2023

Then, we had a lot of machine-learning and deep-learning engineers. The work involved in training something like a BERT model and a large language model is very similar. That knowledge transfers, but the skillset that you’re operating in, there are unique engineering challenges. But that part was challenging.

Large Language Models 64

Large Language Models NLP Prompt Engineer Prompt Engineering 64

Snorkel AI

OCTOBER 17, 2023

Then, we had a lot of machine-learning and deep-learning engineers. The work involved in training something like a BERT model and a large language model is very similar. That knowledge transfers, but the skillset that you’re operating in, there are unique engineering challenges. But that part was challenging.

Large Language Models 59

Large Language Models NLP Prompt Engineer Prompt Engineering 59