Analytics Vidhya

AUGUST 28, 2024

AdalFlow provides a unified library with strong string processing, flexible tools, multiple output formats, and model monitoring like […] The post Optimizing LLM Tasks with AdalFlow: Achieving Efficiency with Minimal Abstraction appeared first on Analytics Vidhya.

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LLM Large Language Models NLP Generative AI 319

Analytics Vidhya

JUNE 25, 2024

Researchers and innovators are creating a wide range of tools and technology to support the creation of LLM-powered applications. With the aid of AI and NLP innovations like LangChain and […] The post Automating Web Search Using LangChain and Google Search APIs appeared first on Analytics Vidhya.

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Automation NLP Artificial Intelligence Artificial Intelligence 331

Analytics Vidhya

MAY 23, 2023

With advanced large […] The post 10 Exciting Projects on Large Language Models(LLM) appeared first on Analytics Vidhya. A portfolio of your projects, blog posts, and open-source contributions can set you apart from other candidates. You can demonstrate your skills by creating smaller projects from start to finish.

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Large Language Models LLM Software Development Data Science 344

Analytics Vidhya

SEPTEMBER 6, 2024

Despite being trained on vast datasets, LLMs can falter with nuanced or context-heavy queries, leading to […] The post How Can Prompt Engineering Transform LLM Reasoning Ability? This struggle often stems from the models’ limited reasoning capabilities or difficulty in processing complex prompts.

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Prompt Engineering Prompt Engineer LLM Large Language Models 291

Unite.AI

APRIL 17, 2024

In recent years, Natural Language Processing (NLP) has undergone a pivotal shift with the emergence of Large Language Models (LLMs) like OpenAI's GPT-3 and Google’s BERT. These models, characterized by their large number of parameters and training on extensive text corpora, signify an innovative advancement in NLP capabilities.

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Analytics Vidhya

NOVEMBER 28, 2024

Large Language Models (LLMs) have revolutionized characteristic dialect preparing (NLP), fueling applications extending from summarization and interpretation to conversational operators and retrieval-based frameworks.

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LLM BERT Large Language Models NLP 203

Analytics Vidhya

JULY 28, 2023

Learn to master prompt engineering for LLM applications with LangChain, an open-source Python framework that has revolutionized the creation of cutting-edge LLM-powered applications. Introduction In the digital age, language-based applications play a vital role in our lives, powering various tools like chatbots and virtual assistants.

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Prompt Engineering Prompt Engineer LLM Python 260

Analytics Vidhya

MAY 20, 2024

Introduction Artificial intelligence has made tremendous strides in Natural Language Processing (NLP) by developing Large Language Models (LLMs). However, a significant challenge with these models is the phenomenon known as “AI hallucinations.” appeared first on Analytics Vidhya.

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Large Language Models Natural Language Processing Artificial Intelligence Artificial Intelligence 318

Unite.AI

OCTOBER 25, 2023

In-context learning has emerged as an alternative, prioritizing the crafting of inputs and prompts to provide the LLM with the necessary context for generating accurate outputs. You have the flexibility to customize the underlying Large Language Model (LLM) as per your project needs.

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LLM OpenAI Prompt Engineering Prompt Engineer 304

Unite.AI

SEPTEMBER 7, 2023

In artificial intelligence (AI), the power and potential of Large Language Models (LLMs) are undeniable, especially after OpenAI’s groundbreaking releases such as ChatGPT and GPT-4. Despite rapid transformation, there are numerous LLM vulnerabilities and shortcomings that must be addressed.

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LLM Large Language Models Prompt Engineer Prompt Engineering 173

Unite.AI

FEBRUARY 7, 2024

This is why Machine Learning Operations (MLOps) has emerged as a paradigm to offer scalable and measurable values to Artificial Intelligence (AI) driven businesses. LLMs are deep neural networks that can generate natural language texts for various purposes, such as answering questions, summarizing documents, or writing code.

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Machine Learning Large Language Models LLM BERT 294

Marktechpost

DECEMBER 6, 2024

The rapid adoption of Large Language Models (LLMs) in various industries calls for a robust framework to ensure their secure, ethical, and reliable deployment. Lets look at 20 essential guardrails designed to uphold security, privacy, relevance, quality, and functionality in LLM applications.

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Unite.AI

NOVEMBER 29, 2023

Furthermore, developers have demonstrated that these smaller LLM frameworks can be trained further using a proprietary-models based dSFT or Distilled Supervised Fine-Tuning approach, that uses the output from an effective teacher model as supervised data for the student model in an attempt to boost the accuracy.

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LLM Large Language Models Natural Language Processing Artificial Intelligence 173

Marktechpost

SEPTEMBER 20, 2024

This limitation poses a significant hurdle for AI-driven applications requiring structured LLM outputs integrated into their data streams. Sketch enables out-of-the-box deployment of LLMs for unfamiliar tasks while maintaining output format correctness and conformity.

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LLM Large Language Models NLP Natural Language Processing 119

Marktechpost

APRIL 10, 2024

However, a groundbreaking new development is set to challenge this status quo and usher in a more inclusive era of language models – the Chinese Tiny LLM (CT-LLM). Imagine a world where language barriers are no longer an obstacle to accessing cutting-edge AI technologies. The pretraining corpus comprises an impressive 840.48

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IBM Journey to AI blog

APRIL 26, 2024

As large language models (LLMs) have entered the common vernacular, people have discovered how to use apps that access them. Modern AI tools can generate, create, summarize, translate, classify and even converse. Tools in the generative AI domain allow us to generate responses to prompts after learning from existing artifacts.

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Hybrid AI Large Language Models LLM AI 246

Unite.AI

JANUARY 2, 2024

Large Language Models (LLMs) have contributed to advancing the domain of natural language processing (NLP), yet an existing gap persists in contextual understanding. Retrieval Augmented Generation (RAG) is a powerful Artificial Intelligence (AI) framework designed to address the context gap by optimizing LLM’s output.

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LLM Large Language Models Chatbots Natural Language Processing 243

AssemblyAI

JANUARY 12, 2024

AI applications are set to contribute $15.7 trillion to the global economy by 2030, with 35% of businesses having already integrated AI technology.    AI Speech-to-Text, a component of Speech AI, uses cutting-edge Automatic Speech Recognition (ASR) models to transcribe and process speech into readable text.

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Large Language Models Python Natural Language Processing NLP 275

Unite.AI

JANUARY 29, 2024

Large language models (LLMs) like GPT-4, Claude, and LLaMA have exploded in popularity. Thanks to their ability to generate impressively human-like text, these AI systems are now being used for everything from content creation to customer service chatbots. So the process is: Pass input prompt to first LLM to generate output.

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Large Language Models LLM Automation NLP 289

Unite.AI

DECEMBER 1, 2023

Machine learning , a subset of AI, involves three components: algorithms, training data, and the resulting model. This obscurity makes it challenging to understand the AI's decision-making process. AI black boxes are systems whose internal workings remain opaque or invisible to users. Impact of the LLM Black Box Problem 1.

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LLM Machine Learning Explainability Algorithm 264

Unite.AI

SEPTEMBER 27, 2023

Generative AI refers to models that can generate new data samples that are similar to the input data. Having been there for over a year, I've recently observed a significant increase in LLM use cases across all divisions for task automation and the construction of robust, secure AI systems.

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Generative AI Large Language Models Prompt Engineer Prompt Engineering 304

Marktechpost

FEBRUARY 29, 2024

Existing methods, like direct finetuning of LLMs on user interaction data, show promise in powering various NLP tasks and enhancing user modeling. The researchers from Google research have proposed USER-LLM , a framework integrating user embeddings with LLMs to adapt dynamically to user context.

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Artificial Intelligence Artificial Intelligence LLM Large Language Models 130

Unite.AI

JULY 23, 2024

In this comprehensive guide, we'll explore the landscape of LLM serving, with a particular focus on vLLM (vector Language Model), a solution that's reshaping the way we deploy and interact with these powerful models. Example: Consider a relatively modest LLM with 13 billion parameters, such as LLaMA-13B.

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LLM Large Language Models Chatbots Artificial Intelligence 130

Towards AI

OCTOBER 18, 2024

Last Updated on October 19, 2024 by Editorial Team Author(s): Mdabdullahalhasib Originally published on Towards AI. Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. Published via Towards AI This member-only story is on us.

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NLP LLM Neural Network Generative AI 111

Unite.AI

DECEMBER 11, 2023

Gemini, Google's advanced multimodal AI, is birthed from the collaborative efforts of the unified DeepMind and Brain AI labs. The announcement of Google Gemini, nestled closely after the debut of Bard, Duet AI, and the PaLM 2 LLM, marks a clear intention from Google to not only compete but lead in the AI revolution.

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AI Weekly

APRIL 11, 2024

We explore how AI can transform roles and boost performance across business functions, customer operations and software development. The Microsoft AI London outpost will focus on advancing state-of-the-art language models, supporting infrastructure, and tooling for foundation models. No legacy process is safe.

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Robotics Artificial Intelligence Artificial Intelligence Data Drift 217

Marktechpost

NOVEMBER 1, 2024

Natural Language Processing (NLP) focuses on building computational models to interpret and generate human language. However, NLP for Hindi still needs to be improved, mainly due to a need for high-quality Hindi data and language-specific models.

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Large Language Models NLP Natural Language Processing Artificial Intelligence 128

Marktechpost

AUGUST 6, 2024

Advancements in NLP have led to the development of large language models (LLMs) capable of performing complex language-related tasks with high accuracy. A significant problem in NLP is the reliance on human annotations for model evaluation. Addressing this problem is crucial for advancing NLP technologies and their applications.

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LLM NLP Large Language Models AI 124

Analytics Vidhya

SEPTEMBER 18, 2024

Introduction Large Language Models (LLMs) contributed to the progress of Natural Language Processing (NLP), but they also raised some important questions about computational efficiency. These models have become too large, so the training and inference cost is no longer within reasonable limits.

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AWS Machine Learning Blog

NOVEMBER 22, 2024

In this post, we demonstrate the potential of large language model (LLM) debates using a supervised dataset with ground truth. In this LLM debate, we have two debater LLMs, each one taking one side of an argument and defending it based on the previous arguments for N(=3) rounds. The arguments are saved for a judge LLM to review.

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LLM Explainability Natural Language Processing Large Language Models 108

Unite.AI

SEPTEMBER 13, 2024

As the demand for large language models (LLMs) continues to rise, ensuring fast, efficient, and scalable inference has become more crucial than ever. NVIDIA's TensorRT-LLM steps in to address this challenge by providing a set of powerful tools and optimizations specifically designed for LLM inference.

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Large Language Models LLM Natural Language Processing Auto-complete 130

Unite.AI

AUGUST 1, 2023

The spotlight is also on DALL-E, an AI model that crafts images from textual inputs. Such sophisticated and accessible AI models are poised to redefine the future of work, learning, and creativity. The Impact of Prompt Quality Using well-defined prompts is the key to engaging in useful and meaningful conversations with AI systems.

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Prompt Engineering Prompt Engineer ChatGPT Convolutional Neural Networks 246

Marktechpost

JULY 3, 2024

GitLab: Validating and Testing AI Models GitLab has developed GitLab Duo, a platform that validates and tests AI-generated outputs. This initiative uses LLMs to assess the quality, accuracy, and reliability of AI models at scale. This rigorous testing process is crucial for maintaining trust in AI-driven features.

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LLM Natural Language Processing Large Language Models Big Data 131

Unite.AI

AUGUST 28, 2023

With advancements in deep learning, natural language processing (NLP), and AI, we are in a time period where AI agents could form a significant portion of the global workforce. These AI agents, transcending chatbots and voice assistants, are shaping a new paradigm for both industries and our daily lives.

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Marktechpost

FEBRUARY 27, 2024

Its development responds to the pressing need for a unified interface that simplifies complex LLM workflows, making them more accessible and manageable for researchers. DataDreamer offers a suite of functionalities that significantly lower the barriers to effective LLM use.

LLM 138

LLM Large Language Models Python NLP 138

Towards AI

OCTOBER 10, 2024

Last Updated on October 12, 2024 by Editorial Team Author(s): Vladyslav Fliahin Originally published on Towards AI. Introduction Source: Image generated by the author using AI (Flux AI) Did you know that businesses receive thousands of customer reviews daily, each containing valuable insights?

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Metadata LLM Algorithm Large Language Models 119

Marktechpost

FEBRUARY 3, 2024

In the dynamic field of Artificial Intelligence (AI), the trajectory from one foundational model to another has represented an amazing paradigm shift. Using a technique known as LLM-as-a-Judge prompting, the language model assesses and rewards its own outputs for doing this. While requiring 2.2

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Artificial Intelligence Artificial Intelligence LLM Large Language Models 139