AWS Machine Learning Blog

MARCH 17, 2025

Large language models (LLMs) have revolutionized the field of natural language processing, enabling machines to understand and generate human-like text with remarkable accuracy. However, despite their impressive language capabilities, LLMs are inherently limited by the data they were trained on.

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Unite.AI

NOVEMBER 11, 2024

Alix Melchy is the VP of AI at Jumio, where he leads teams of machine learning engineers across the globe with a focus on computer vision, natural language processing and statistical modeling. This focus ensures that AI models are developed with a strong foundation of inclusivity and fairness.

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Machine Learning AI AI Natural Language Processing 162

AI Weekly

JUNE 27, 2024

co-founder says data centers will be less energy-intensive in the future as artificial intelligence makes computations more efficient. bloomberg.com CData scores $350M as data integration needs surge in the age of AI In the race to adopt AI and gain a competitive edge, enterprises are making substantial investments.

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Flipboard

DECEMBER 3, 2024

The agent uses natural language processing (NLP) to understand the query and uses underlying agronomy models to recommend optimal seed choices tailored to specific field conditions and agronomic needs. What corn hybrids do you suggest for my field?”.

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Unite.AI

SEPTEMBER 27, 2024

Meta's recent launch of Llama 3.2 , the latest iteration in its Llama series of large language models, is a significant development in the evolution of open-source generative AI ecosystem. allows for the processing of multimodal data—integrating images, text, and more—making advanced AI capabilities more accessible to a wider audience.

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Flipboard

DECEMBER 26, 2024

Self-supervised learning (SSL) has emerged as a powerful method for extracting meaningful representations from vast, unlabelled datasets, transforming computer vision and natural language processing. However, identifying scenarios in SCG where SSL outperforms traditional learning methods remains a nuanced challenge.

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Computer Vision Natural Language Processing Data Integration Machine Learning 129

Heartbeat

SEPTEMBER 20, 2023

Pixabay: by Activedia Image captioning combines natural language processing and computer vision to generate image textual descriptions automatically. This integration combines visual features extracted from images with language models to generate descriptive and contextually relevant captions.

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Unite.AI

AUGUST 9, 2024

Some of the leading generative AI playgrounds are: Hugging Face: Hugging Face is a leading generative AI playground, especially renowned for its natural language processing (NLP) capabilities. It offers a comprehensive library of pre-trained AI models, datasets, and tools, making it easier to create and deploy AI applications.

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AWS Machine Learning Blog

MARCH 18, 2025

Intelligent insights and recommendations Using its large knowledge base and advanced natural language processing (NLP) capabilities, the LLM provides intelligent insights and recommendations based on the analyzed patient-physician interaction. These insights can include: Potential adverse event detection and reporting.

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Unite.AI

SEPTEMBER 21, 2023

AI systems can process large amounts of data to learn patterns and relationships and make accurate and realistic predictions that improve over time. Organizations and practitioners build AI models that are specialized algorithms to perform real-world tasks such as image classification, object detection, and natural language processing.

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IBM Journey to AI blog

NOVEMBER 10, 2023

Ring 3 uses the capabilities of Ring 1 and Ring 2, including the data integration capabilities of the platform for terminology standardization and person matching. This also supports the capabilities to insert actionable insights and care plan updates directly into the provider care flow within the Electronic Medical Record (EMR).

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Unite.AI

OCTOBER 11, 2023

Traditional Databases : Structured Data Storage : Traditional databases, like relational databases, are designed to store structured data. This means data is organized into predefined tables, rows, and columns, ensuring data integrity and consistency.

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IBM Journey to AI blog

JANUARY 12, 2024

The advantages of AI are numerous and impactful, from predictive analytics that refine strategies, to natural language processing that fuels customer interactions and assists users in their daily tasks, to assistive tools that enhance accessibility, communication and independence for people with disabilities.

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Unite.AI

SEPTEMBER 24, 2024

This multi-faceted approach to data analysis allows for more accurate demand forecasting and inventory optimization, helping businesses reduce costs associated with overstocking or stockouts. IBM Supply Chain is designed to be scalable and adaptable, making it suitable for businesses of various sizes across different industries.

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Marktechpost

MAY 9, 2024

In Natural Language Processing (NLP) tasks, data cleaning is an essential step before tokenization, particularly when working with text data that contains unusual word separations such as underscores, slashes, or other symbols in place of spaces.

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Marktechpost

FEBRUARY 23, 2025

Defining AI Agents At its simplest, an AI agent is an autonomous software entity capable of perceiving its surroundings, processing data, and taking action to achieve specified goals. Data Quality and Bias: The effectiveness of AI agents depends on the quality of the data they are trained on.

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Flipboard

FEBRUARY 11, 2025

In this post, we propose an end-to-end solution using Amazon Q Business to address similar enterprise data challenges, showcasing how it can streamline operations and enhance customer service across various industries. The Process Data Lambda function redacts sensitive data through Amazon Comprehend.

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Marktechpost

DECEMBER 25, 2023

Transformer models are crucial in machine learning for language and vision processing tasks. Transformers, renowned for their effectiveness in sequential data handling, play a pivotal role in natural language processing and computer vision.

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Marktechpost

MARCH 3, 2024

We cannot deny the significant strides made in natural language processing (NLP) through large language models (LLMs). Still, these models often need to catch up when dealing with the complexities of structured information, highlighting a notable gap in their capabilities.

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Unite.AI

DECEMBER 14, 2023

The consequences of data contamination can be far-reaching, resulting in incorrect predictions, unreliable outcomes, and skewed data. What Are Large Language Models? LLMs have gained significant popularity and are widely used in various applications, including natural language processing and machine translation.

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ODSC - Open Data Science

MARCH 3, 2025

Their work has set a gold standard for integrating advanced natural language processing (NLP ) into clinical settings. This approach allows for natural language queries like, Has this patient shown signs of depression since starting Montelukast?transforming transforming how clinicians interact withdata.

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Marktechpost

JUNE 30, 2024

These platforms enhance data processing capabilities, allowing users to automate data entry, perform complex calculations, and generate insights from large datasets. AI workbooks can also suggest data visualizations and provide predictive analytics, making it easier for users to interpret and act on their data.

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Unite.AI

JANUARY 22, 2024

Synthetic data , artificially generated to mimic real data, plays a crucial role in various applications, including machine learning , data analysis , testing, and privacy protection. Google researchers highlighted advancements in named entity recognition, relation extraction, and question answering.

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Marktechpost

MAY 8, 2024

These technologies have revolutionized computer vision, robotics, and natural language processing and played a pivotal role in the autonomous driving revolution. Over the past decade, advancements in deep learning and artificial intelligence have driven significant strides in self-driving vehicle technology.

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Marktechpost

AUGUST 21, 2024

These models represent significant advancements in natural language processing, multimodal AI, and high-performance computing, each designed to address specific challenges and optimize various AI-driven tasks. Mini Instruct, Phi 3.5 MoE (Mixture of Experts), and Phi 3.5 Vision Instruct. Image Source Phi 3.5 Finally, Phi 3.5

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Unite.AI

SEPTEMBER 24, 2024

Exploring LangChain LangChain is a helpful framework designed to simplify AI models' development, integration, and deployment, particularly those focused on Natural Language Processing (NLP) and conversational AI.

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Unite.AI

SEPTEMBER 18, 2023

Artificial Intelligence is a very vast branch in itself with numerous subfields including deep learning, computer vision , natural language processing , and more. There exists an intelligent privacy parking management system that makes use of a Role-Based Access Control or RBAC model to manage permissions.

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AWS Machine Learning Blog

APRIL 7, 2025

This granularity supports better version control and data lineage tracking, which are crucial for data integrity and compliance. Focusing on relevant chunks can improve the performance of LLMs, ultimately leading to more accurate insights and better decision-making processes within organizations.

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AWS Machine Learning Blog

MARCH 14, 2025

Her overall work focuses on Natural Language Processing (NLP) research and developing NLP applications for AWS customers, including LLM Evaluations, RAG, and improving reasoning for LLMs. at Language Technologies Institute, Carnegie Mellon University. Prior to Amazon, Evangelia completed her Ph.D.

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IBM Journey to AI blog

OCTOBER 20, 2023

These development platforms support collaboration between data science and engineering teams, which decreases costs by reducing redundant efforts and automating routine tasks, such as data duplication or extraction. Store operating platform : Scalable and secure foundation supports AI at the edge and data integration.

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Topbots

OCTOBER 4, 2023

Here are a few examples across various domains: Natural Language Processing (NLP) : Predictive NLP models can categorize text into predefined classes (e.g., However, to improve results for specific use cases, developers often fine-tune generative models on small amounts of labeled data.

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AWS Machine Learning Blog

JUNE 21, 2024

They needed no additional infrastructure for data integration. This was very useful in combination with SageMaker integration with Amazon Elastic Container Registry (Amazon ECR), SageMaker endpoint configuration, and SageMaker models to provide the entire configuration required to spin up their LLMs as needed.

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IBM Journey to AI blog

DECEMBER 16, 2022

The solution also helps with data quality management by assigning data quality scores to assets and simplifies curation with AI-driven data quality rules. AI recommendations and robust search methods with the power of natural language processing and semantic search help locate the right data for projects.

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Unite.AI

AUGUST 27, 2024

Using Natural Language Processing (NLP) and the latest AI models, Perplexity AI moves beyond keyword matching to understand the meaning behind questions. Interact with data: Analyze uploaded files and answer questions about the data, integrating seamlessly with web searches for a complete view.

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O'Reilly Media

OCTOBER 11, 2022

It’s possible to augment this basic process with OCR so the application can find data on paper forms, or to use natural language processing to gather information through a chat server. But the core of the process is simple, and hasn’t changed much since the early days of web testing.

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AWS Machine Learning Blog

MARCH 10, 2025

The solutions efficient document processing and embedding capabilities addressed the previous systems limitations, enabling faster and more efficient knowledge base updates. Amazon Bedrock Guardrails implements content filtering and safety checks as part of the query processing pipeline.

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Unite.AI

JUNE 14, 2024

How have your experiences at companies like Comcast, Elsevier, and Microsoft influenced your approach to integrating AI and search technologies? Throughout my career, I have been deeply focused on natural language processing (NLP) techniques and machine learning.

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