Towards AI

JANUARY 22, 2025

Drawbacks: Latency: Fetching and processing external data can slow down response times. Dependency on Retrievers: Performance hinges on the quality and relevance of retrieved data. Integration Complexity: Requires seamless integration between the retriever and generator components. Citations: Lewis, P.,

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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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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. The post Is There a Library for Cleaning Data before Tokenization?

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Unite.AI

SEPTEMBER 18, 2023

NLP in particular has been a subfield that has been focussed heavily in the past few years that has resulted in the development of some top-notch LLMs like GPT and BERT. Artificial Intelligence is a very vast branch in itself with numerous subfields including deep learning, computer vision , natural language processing , and more.

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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. Measuring LLMSuccess Evaluating large language models in healthcare often startswith: Benchmark performance on standardized NLP datasets. Peer-reviewed research to validate theoretical accuracy.

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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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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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AWS Machine Learning Blog

MARCH 17, 2025

Healthcare agents can integrate LLM models and call external functions or APIs through a series of steps: natural language input processing , self-correction, chain of thought, function or API calling through an integration layer, data integration and processing, and persona adoption.

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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

OCTOBER 8, 2024

Each of these specialized sources went through tailored pipelines to preserve data integrity and quality, ensuring that the resulting language models can handle a wide range of topics. TxT360: A New Era for Open-Source AI The release of TxT360 marks a significant leap forward in AI and NLP research.

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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). This deficiency underscores the need for newer, more innovative approaches to enhance LLMs’ structured knowledge grounding (SKG) capabilities, enabling them to comprehend and utilize structured data more effectively.

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AWS Machine Learning Blog

APRIL 29, 2024

Close collaboration with AWS Trainium has also played a major role in making the Arcee platform extremely performant, not only accelerating model training but also reducing overall costs and enforcing compliance and data integrity in the secure AWS environment. is the Head of Applied NLP Research at Arcee. Shamane Siri Ph.D.

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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. Prior to Amazon, Evangelia completed her Ph.D. at Language Technologies Institute, Carnegie Mellon University.

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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

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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AWS Machine Learning Blog

MARCH 10, 2025

With seven years of experience in AI/ML, his expertise spans GenAI and NLP, specializing in designing and deploying agentic AI systems. With expertise in GenAI and NLP, he focuses on designing and deploying intelligent systems that enhance automation and decision-making.

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AWS Machine Learning Blog

OCTOBER 23, 2024

By processing data closer to where it resides, SnapLogic promotes faster, more efficient operations that meet stringent regulatory requirements, ultimately delivering a superior experience for businesses relying on their data integration and management solutions. He currently is working on Generative AI for data integration.

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Marktechpost

FEBRUARY 23, 2025

Important Milestones Integration of Machine Learning: The adoption of machine learning enabled AI agents to identify patterns in large datasets, making them more responsive and effective in various applications. Data Quality and Bias: The effectiveness of AI agents depends on the quality of the data they are trained on.

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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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AWS Machine Learning Blog

NOVEMBER 15, 2023

In this post, we demonstrate how data aggregated within the AWS CCI Post Call Analytics solution allowed Principal to gain visibility into their contact center interactions, better understand the customer journey, and improve the overall experience between contact channels while also maintaining data integrity and security.

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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., spam vs. not spam), while generative NLP models can create new text based on a given prompt (e.g., a social media post or product description).

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Marktechpost

AUGUST 21, 2024

The model’s architecture also allows it to outperform larger models in reasoning tasks while maintaining competitive performance across various NLP benchmarks. Vision Instruct sets a new standard in multimodal AI, enabling advanced visual and textual data integration for complex tasks. Finally, Phi 3.5 MoE-instruct.

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AWS Machine Learning Blog

SEPTEMBER 28, 2023

Each request/response interaction is facilitated by the AWS SDK and sends network traffic to Amazon Lex (the NLP component of the bot). As an Information Technology Leader, Jay specializes in artificial intelligence, data integration, business intelligence, and user interface domains.

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Marktechpost

JUNE 14, 2024

LLMs have excelled in NLP tasks, and this success has inspired attempts to adapt them to understanding proteins. The literature review highlights key limitations in existing datasets and NLP and protein sequence benchmarks.

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ODSC - Open Data Science

APRIL 6, 2023

Each of these creates visualizations and reports based on data stored in a database. They often provide drag-and-drop interfaces that allow non-technical users to create reports and dashboards using SQL queries as the underlying data source. Data integration tools allow for the combining of data from multiple sources.

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Heartbeat

OCTOBER 23, 2023

Natural Language Processing (NLP) and Text Mining: Healthcare data includes vast amounts of unstructured information in clinical notes, research articles, and patient narratives. Data scientists and machine learning engineers employ NLP techniques and text-mining algorithms to process and analyze this textual data.

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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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Marktechpost

JANUARY 27, 2025

SSL is a powerful technique for extracting meaningful patterns from large, unlabelled datasets, proving transformative in fields like computer vision and NLP. In single-cell genomics (SCG), SSL offers significant potential for analyzing complex biological data, especially with the advent of foundation models.

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Heartbeat

SEPTEMBER 20, 2023

This technology has broad applications, including aiding individuals with visual impairments, improving image search algorithms, and integrating optical recognition with advanced language generation to enhance human-machine interactions. NLP enables computers to comprehend and generate coherent sentences.

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Pickl AI

OCTOBER 18, 2023

Automatic Data Capture: Streamlining Data Entry with AI AI has the remarkable ability to extract data without manual intervention, allowing employees to focus on more critical tasks, such as customer interactions. Predictive Data Quality Machine learning models can predict data quality issues before they become critical.

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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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Pickl AI

OCTOBER 2, 2024

Summary: Artificial Intelligence (AI) is revolutionising Genomic Analysis by enhancing accuracy, efficiency, and data integration. Despite challenges like data quality and ethical concerns, AI’s potential in genomics continues to grow, shaping the future of healthcare.

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Heartbeat

MAY 29, 2023

LLMs are one of the most exciting advancements in natural language processing (NLP). LLMs are trained on massive amounts of text data, allowing them to generate highly accurate predictions and responses. Tokenization: Tokenization is a crucial step in data preparation for natural language processing (NLP) tasks.

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The Stanford AI Lab Blog

NOVEMBER 5, 2021

Manning Contact : jennyhong@cs.stanford.edu Keywords : legal nlp, information extraction, weak supervision Capturing Logical Structure of Visually Structured Documents with Multimodal Transition Parser Authors : Yuta Koreeda, Christopher D.

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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. Use AWS KMS encryption in Amazon Comprehend – Amazon Comprehend works with AWS KMS to provide enhanced encryption for your data.

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AWS Machine Learning Blog

SEPTEMBER 5, 2023

This dramatically reduces the size of data while capturing features that characterize the equipment’s behavior. Figure 1: Sample of HVAC sensor data AWS Glue is a serverless data integration service for processing large quantities of data at scale.

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John Snow Labs

SEPTEMBER 26, 2024

Data integration has been an enormous challenge in healthcare for decades.

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