Hacker News

OCTOBER 21, 2024

It outlines the historical evolution of LLMs from traditional Natural Language Processing (NLP) models to their pivotal role in AI. The report introduces a structured seven-stage pipeline for fine-tuning LLMs, spanning data preparation, model initialization, hyperparameter tuning, and model deployment.

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Data Science Dojo

AUGUST 28, 2023

Large Language Model Ops also known as LLMOps isn’t just a buzzword; it’s the cornerstone of unleashing LLM potential. From data management to model fine-tuning, LLMOps ensures efficiency, scalability, and risk mitigation. As LLMs redefine AI capabilities, mastering LLMOps becomes your compass in this dynamic landscape.

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Data Science Dojo

JULY 17, 2023

In recent years, there has been a growing interest in the use of artificial intelligence (AI) for data analysis. AI tools can automate many of the tasks involved in data analysis, and they can also help businesses to discover new insights from their data.

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AWS Machine Learning Blog

NOVEMBER 1, 2024

Fine-tuning is a powerful approach in natural language processing (NLP) and generative AI , allowing businesses to tailor pre-trained large language models (LLMs) for specific tasks. This process involves updating the model’s weights to improve its performance on targeted applications.

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DagsHub

FEBRUARY 29, 2024

Data, is therefore, essential to the quality and performance of machine learning models. This makes data preparation for machine learning all the more critical, so that the models generate reliable and accurate predictions and drive business value for the organization. Why do you need Data Preparation for Machine Learning?

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Dataconomy

APRIL 16, 2025

Cross-lingual language models (XLMs) have emerged as a pivotal technology in the landscape of natural language processing (NLP), empowering machines to engage with diverse languages seamlessly. What are cross-lingual language models?

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Dataconomy

MARCH 26, 2025

Fine-tuning plays a crucial role in enhancing the utility of pretrained models in machine learning and AI. This process not only accelerates development but also democratizes access to advanced AI capabilities. What is fine-tuning in machine learning and AI?

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AWS Machine Learning Blog

DECEMBER 4, 2024

When using generative AI, achieving high performance with low latency models that are cost-efficient is often a challenge, because these goals can clash with each other. With Amazon Bedrock Model Distillation, you can now customize models for your use case using synthetic data generated by highly capable models.

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AWS Machine Learning Blog

NOVEMBER 27, 2023

Generative artificial intelligence ( generative AI ) models have demonstrated impressive capabilities in generating high-quality text, images, and other content. However, these models require massive amounts of clean, structured training data to reach their full potential. Clean data is important for good model performance.

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AWS Machine Learning Blog

DECEMBER 18, 2024

AIs transformative impact extends throughout the modern business landscape, with telecommunications emerging as a key area of innovation. Fastweb , one of Italys leading telecommunications operators, recognized the immense potential of AI technologies early on and began investing in this area in 2019.

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AWS Machine Learning Blog

NOVEMBER 15, 2024

This trend toward multimodality enhances the capabilities of AI systems in tasks like cross-modal retrieval, where a query in one modality (such as text) retrieves data in another modality (such as images or design files). All businesses, across industry and size, can benefit from multimodal AI search.

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Towards AI

AUGUST 16, 2023

Last Updated on August 17, 2023 by Editorial Team Author(s): Jeff Holmes MS MSCS Originally published on Towards AI. Jason Leung on Unsplash AI is still considered a relatively new field, so there are really no guides or standards such as SWEBOK. 85% or more of AI projects fail [1][2]. 85% or more of AI projects fail [1][2].

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AWS Machine Learning Blog

OCTOBER 5, 2023

Artificial intelligence (AI) and machine learning (ML) have seen widespread adoption across enterprise and government organizations. Processing unstructured data has become easier with the advancements in natural language processing (NLP) and user-friendly AI/ML services like Amazon Textract , Amazon Transcribe , and Amazon Comprehend.

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PyImageSearch

FEBRUARY 17, 2025

Home Table of Contents Chat with Graphic PDFs: Understand How AI PDF Summarizers Work The Challenge of Processing Complex PDFs Layout Complexity Table and Figure Recognition Mathematical and Special Characters Enter the World of Multimodal Models The Power of RAG Key Components of a RAG Pipeline Why Choose ColPali as the Retriever?

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Dataconomy

MARCH 27, 2023

RPA is often considered a form of artificial intelligence, but it is not a complete AI solution. AI, on the other hand, can learn from data and adapt to new situations without human intervention. RPA can be easily integrated with legacy systems, and the implementation process is relatively straightforward.

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AWS Machine Learning Blog

SEPTEMBER 1, 2023

Nowadays, the majority of our customers is excited about large language models (LLMs) and thinking how generative AI could transform their business. In this post, we discuss how to operationalize generative AI applications using MLOps principles leading to foundation model operations (FMOps).

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Towards AI

JUNE 27, 2023

In the rapidly expanding field of artificial intelligence (AI), machine learning tools play an instrumental role. Already a multi-billion-dollar industry, AI is having a profound impact on every aspect of life, business, and society. These tools are becoming increasingly sophisticated, enabling the development of advanced applications.

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AWS Machine Learning Blog

FEBRUARY 6, 2024

We address this skew with generative AI models (Falcon-7B and Falcon-40B), which were prompted to generate event samples based on five examples from the training set to increase the semantic diversity and increase the sample size of labeled adverse events. Outside of work, when not discussing AI in radiology, she likes to run and hike.

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AWS Machine Learning Blog

NOVEMBER 15, 2024

In the rapidly evolving landscape of AI, generative models have emerged as a transformative technology, empowering users to explore new frontiers of creativity and problem-solving. 11B and 90B are the first Llama models to support vision tasks, with a new model architecture that integrates image encoder representations into the language model.

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AWS Machine Learning Blog

NOVEMBER 22, 2023

Now all you need is some guidance on generative AI and machine learning (ML) sessions to attend at this twelfth edition of re:Invent. And although generative AI has appeared in previous events, this year we’re taking it to the next level. And although our track focuses on generative AI, many other tracks have related sessions.

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ODSC - Open Data Science

FEBRUARY 5, 2025

This problem often stems from inadequate user value, underwhelming performance, and an absence of robust best practices for building and deploying LLM tools as part of the AI development lifecycle. LLMs, while accelerating some processes, introduce complexities that require new tools and methodologies. Evaluation: Tools likeNotion.

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Data Science Dojo

AUGUST 1, 2023

The next generation of Language Model Systems (LLMs) and LLM chatbots are expected to offer improved accuracy, expanded language support, enhanced computational efficiency, and seamless integration with emerging technologies. The answer will be in natural language and will be relevant to the question.

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Towards AI

JANUARY 14, 2025

Last Updated on January 15, 2025 by Editorial Team Author(s): Yash Thube Originally published on Towards AI. Transformers have revolutionized natural language processing (NLP), powering models like GPT and BERT. Understanding Vision Transformers (ViTs) And what I learned while implementing them!

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IBM Journey to AI blog

OCTOBER 20, 2023

AI platform tools enable knowledge workers to analyze data, formulate predictions and execute tasks with greater speed and precision than they can manually. AI plays a pivotal role as a catalyst in the new era of technological advancement. PwC calculates that “AI could contribute up to USD 15.7 trillion in value.

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IBM Journey to AI blog

JULY 17, 2023

is our enterprise-ready next-generation studio for AI builders, bringing together traditional machine learning (ML) and new generative AI capabilities powered by foundation models. With watsonx.ai, businesses can effectively train, validate, tune and deploy AI models with confidence and at scale across their enterprise.

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AWS Machine Learning Blog

APRIL 17, 2023

“Instead of focusing on the code, companies should focus on developing systematic engineering practices for improving data in ways that are reliable, efficient, and systematic. This can be a tedious task involving data collection, discovery, profiling, cleansing, structuring, transforming, enriching, validating, and securely storing the data.

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IBM Journey to AI blog

AUGUST 12, 2024

AIOPs refers to the application of artificial intelligence (AI) and machine learning (ML) techniques to enhance and automate various aspects of IT operations (ITOps). However, they differ fundamentally in their purpose and level of specialization in AI and ML environments.

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Pickl AI

OCTOBER 3, 2024

Summary: Artificial Intelligence Models as a Service (AIMaaS) provides cloud-based access to scalable, customizable AI models. AIMaaS democratises AI, making advanced technologies accessible to organisations of all sizes across various industries. Predictive Analytics : Models that forecast future events based on historical data.

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AWS Machine Learning Blog

OCTOBER 23, 2023

Given this mission, Talent.com and AWS joined forces to create a job recommendation engine using state-of-the-art natural language processing (NLP) and deep learning model training techniques with Amazon SageMaker to provide an unrivaled experience for job seekers.

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Pickl AI

JULY 12, 2024

Introduction Artificial Intelligence (AI) transforms industries by enabling machines to mimic human intelligence. Python’s simplicity, versatility, and extensive library support make it the go-to language for AI development. It includes Python and a vast collection of pre-installed libraries and tools for AI development.

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AWS Machine Learning Blog

JULY 11, 2024

Fine tuning embedding models using SageMaker SageMaker is a fully managed machine learning service that simplifies the entire machine learning workflow, from data preparation and model training to deployment and monitoring. For more information about fine tuning Sentence Transformer, see Sentence Transformer training overview.

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AWS Machine Learning Blog

NOVEMBER 22, 2023

An intelligent document processing (IDP) project usually combines optical character recognition (OCR) and natural language processing (NLP) to read and understand a document and extract specific entities or phrases. Pay attention to protection of data at rest and data produced in IDP outputs.

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IBM Journey to AI blog

MARCH 27, 2024

This article explores an innovative way to streamline the estimation of Scope 3 GHG emissions leveraging AI and Large Language Models (LLMs) to help categorize financial transaction data to align with spend-based emissions factors. Why are Scope 3 emissions difficult to calculate? This is where LLMs come into play.

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AWS Machine Learning Blog

JULY 29, 2024

With the addition of forecasting, you can now access end-to-end ML capabilities for a broad set of model types—including regression, multi-class classification, computer vision (CV), natural language processing (NLP), and generative artificial intelligence (AI)—within the unified user-friendly platform of SageMaker Canvas.

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Dataconomy

JULY 28, 2023

Data preprocessing is a fundamental and essential step in the field of sentiment analysis, a prominent branch of natural language processing (NLP). These tools offer a wide range of functionalities to handle complex data preparation tasks efficiently.

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AWS Machine Learning Blog

AUGUST 14, 2023

In this post, we showcase how to build an end-to-end generative AI application for enterprise search with Retrieval Augmented Generation (RAG) by using Haystack pipelines and the Falcon-40b-instruct model from Amazon SageMaker JumpStart and Amazon OpenSearch Service. It also hosts foundation models solely developed by Amazon, such as AlexaTM.

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AWS Machine Learning Blog

JULY 24, 2024

Large language models (LLMs) have achieved remarkable success in various natural language processing (NLP) tasks, but they may not always generalize well to specific domains or tasks. This is where MLflow can help streamline the ML lifecycle, from data preparation to model deployment.

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