Marktechpost

OCTOBER 18, 2024

It links the reduction in local rank to the implicit regularization mechanisms of neural networks, offering a perspective that connects feature manifold compression to the Information Bottleneck framework. The reduction occurred across all layers, aligning with the compression phase as predicted by the Information Bottleneck theory.

Neural Network 99

Neural Network Inference Engine ML Artificial Intelligence 99

Analytics Vidhya

JUNE 13, 2021

The post Understand Weight of Evidence and Information Value! ArticleVideo Book This article was published as a part of the Data Science Blogathon Agenda We have all built a logistic regression at some point. appeared first on Analytics Vidhya.

Data Science 318

Data Science ML Python Machine Learning 318

AI News

JULY 28, 2023

According to a recent report by Harnham , a leading data and analytics recruitment agency in the UK, the demand for ML engineering roles has been steadily rising over the past few years. Advancements in AI and ML are transforming the landscape and creating exciting new job opportunities.

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ML ML Engineer Data Science Big Data 197

AI News

MAY 15, 2023

We must admit that human intelligence is limited in capacity and ability to process information. That’s essentially what the modern lifecycle of AI/ML products looks like. That requires experience in identifying the problems that can benefit from AI/ML the most, and agile, iterative processes of validating and scaling the ideas.

ML 267

ML Machine Learning Big Data AI 267

AWS Machine Learning Blog

MAY 9, 2024

The rapid advancements in artificial intelligence and machine learning (AI/ML) have made these technologies a transformative force across industries. An effective approach that addresses a wide range of observed issues is the establishment of an AI/ML center of excellence (CoE). What is an AI/ML CoE?

ML 125

ML Generative AI AI AI 125

Towards AI

APRIL 10, 2024

How much machine learning really is in ML Engineering? But what actually are the differences between a Data Engineer, Data Scientist, ML Engineer, Research Engineer, Research Scientist, or an Applied Scientist?! Data engineering is the foundation of all ML pipelines. It’s so confusing!

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ML Engineer ML Explainability Machine Learning 96

Aiiot Talk

AUGUST 10, 2023

Machine learning (ML) and artificial intelligence (AI) have many viable uses in business, including reducing overhead costs. What Are the Benefits of Using ML and AI? Leveraging ML and AI is beneficial because it’s a low-risk, high-reward approach to reducing overhead costs. How Can ML and AI Reduce Overhead Costs?

ML 130

ML Automation Artificial Intelligence Artificial Intelligence 130

Marktechpost

OCTOBER 29, 2024

Retrieval-augmented generation (RAG) systems, a key area of research in artificial intelligence, aim to enhance large language models (LLMs) by incorporating external sources of information for generating responses. However, this approach often results in the generation of responses that include irrelevant information, affecting accuracy.

LLM 119

LLM Large Language Models Artificial Intelligence Artificial Intelligence 119

AWS Machine Learning Blog

MAY 7, 2024

Large language models (LLMs) have unlocked new possibilities for extracting information from unstructured text data. SageMaker JumpStart is a machine learning (ML) hub with foundation models (FMs), built-in algorithms, and prebuilt ML solutions that you can deploy with just a few clicks.

Prompt Engineer 116

Prompt Engineer Prompt Engineering Large Language Models LLM 116

Marktechpost

AUGUST 26, 2024

Medical abstractive summarization faces challenges in balancing faithfulness and informativeness, often compromising one for the other. They introduce uMedSum, a modular hybrid framework designed to enhance faithfulness and informativeness by sequentially removing confabulations and adding missing information.

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BERT AI AI ML 94

Marktechpost

OCTOBER 23, 2024

Multi-modal entity alignment (MMEA) is a technique that leverages information from various data sources or modalities to identify corresponding entities across multiple knowledge graphs. These models may over-rely on specific modalities, insufficiently fuse information, lack modality-specific features, or neglect inter-modal relationships.

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Inference Engine ML Artificial Intelligence Artificial Intelligence 103

AWS Machine Learning Blog

NOVEMBER 7, 2024

The new information is used to enhance the training sets used in Step 1 for forecasting discounts. Operating such large-scale forecasting requires resilient, reusable, reproducible, and automated machine learning (ML) workflows with fast experimentation and continuous improvements. The following diagram illustrates this workflow.

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ML Machine Learning Automation Data Scientist 103

Unite.AI

JUNE 19, 2023

Adam Asquini is a Director of Information Management & Data Analytics at KPMG in Edmonton. That type of work's also really important and can save organizations a lot of effort and a lot of money in how they do their business, You’re currently the director of information management and data analytics at KPMG.

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Generative AI Responsible AI Artificial Intelligence Artificial Intelligence 244

AWS Machine Learning Blog

NOVEMBER 19, 2024

This year, generative AI and machine learning (ML) will again be in focus, with exciting keynote announcements and a variety of sessions showcasing insights from AWS experts, customer stories, and hands-on experiences with AWS services. Visit the session catalog to learn about all our generative AI and ML sessions.

ML 83

ML Generative AI AI AI 83

Marktechpost

JULY 20, 2024

Traditional methods, relying solely on formal proof data, overlook valuable informal reasoning processes crucial to human mathematicians. The paper addresses the need to bridge informal human reasoning with formal proof generation, aiming to improve the efficiency and accuracy of automated theorem proving.

Automation 100

Automation AI AI Artificial Intelligence 100

Marktechpost

APRIL 28, 2024

However, recent studies highlight a challenge: these LLMs struggle to utilize middle information effectively, termed the lost-in-the-middle challenge. While the LLM can comprehend the information at the beginning and end of the long context, it often overlooks the information in the middle.

Large Language Models 118

Large Language Models LLM ML Artificial Intelligence 118

AWS Machine Learning Blog

MAY 30, 2024

To serve their customers, Vitech maintains a repository of information that includes product documentation (user guides, standard operating procedures, runbooks), which is currently scattered across multiple internal platforms (for example, Confluence sites and SharePoint folders). langsmith==0.0.43 pgvector==0.2.3 streamlit==1.28.0

Chatbots 122

Chatbots Prompt Engineer Prompt Engineering Large Language Models 122

Marktechpost

JULY 9, 2024

Let’s delve into the methods and applications of CL, particularly focusing on its implementation within Information Retrieval (IR) systems presented by researchers from Renmin University of China. Also, don’t forget to follow us on Twitter and join our 46k+ ML SubReddit , 26k+ AI Newsletter, Telegram Channel , and LinkedIn Gr oup.

Machine Learning 100

Machine Learning Categorization Algorithm ML 100

Marktechpost

NOVEMBER 10, 2024

The conventional method of converting HTML documents into plain text before feeding them to LLMs results in a substantial loss of structural and semantic information. Moreover, research in structured data understanding has demonstrated the superior information richness of HTML and Excel tables compared to plain text.

Artificial Intelligence 60

Artificial Intelligence Artificial Intelligence ChatGPT ML 60

Marktechpost

NOVEMBER 18, 2024

While these systems use interaction histories between users and items through Graph Neural Networks (GNNs) to mine latent information and capture high-order interactions, the quality of collected data poses a major obstacle. Don’t Forget to join our 55k+ ML SubReddit. If you like our work, you will love our newsletter.

Neural Network 75

Neural Network AI AI Algorithm 75

Marktechpost

SEPTEMBER 10, 2024

While some models attempt to integrate past interactions to inform future recommendations, they often need to provide a robust solution for sequential music recommendations, especially in recognizing when users are likely to repeat their listening patterns. If you like our work, you will love our newsletter.

Neural Network 97

Neural Network Deep Learning Algorithm AI Researcher 97

Towards AI

FEBRUARY 21, 2024

Image generated with DALL-E 3 In the fast-paced world of Machine Learning (ML) research, keeping up with the latest findings is crucial and exciting, but let’s be honest — it’s also a challenge. Enter ML Conference Paper Explorer: your sidekick in navigating the ML paper maze with ease. What’s the next big thing in ML?

ML 99

ML Machine Learning AI AI 99

Marktechpost

OCTOBER 24, 2024

Despite advances, handling the vast amount of visual information in videos remains a core challenge in developing scalable and efficient VLMs. Models like Video-ChatGPT and Video-LLaVA focus on spatial and temporal pooling mechanisms to condense frame-level information into smaller tokens. Don’t Forget to join our 55k+ ML SubReddit.

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AI Researcher AI Research Inference Engine Artificial Intelligence 118

Marktechpost

JUNE 30, 2024

Existing methods often need help with errors and hallucinations, leading to incorrect or misleading information in generated responses. Currently, LLMs are used for tasks requiring information retrieval and generation, emphasizing grounding responses in verifiable sources. Join our Telegram Channel and LinkedIn Gr oup.

Large Language Models 84

Large Language Models LLM ML Artificial Intelligence 84

AWS Machine Learning Blog

OCTOBER 29, 2024

This post is part of an ongoing series on governing the machine learning (ML) lifecycle at scale. To start from the beginning, refer to Governing the ML lifecycle at scale, Part 1: A framework for architecting ML workloads using Amazon SageMaker. We use SageMaker Model Monitor to assess these models’ performance.

ML 93

ML Machine Learning Large Language Models Categorization 93

AWS Machine Learning Blog

SEPTEMBER 23, 2024

Machine learning (ML) projects are inherently complex, involving multiple intricate steps—from data collection and preprocessing to model building, deployment, and maintenance. To start our ML project predicting the probability of readmission for diabetes patients, you need to download the Diabetes 130-US hospitals dataset.

ML 81

ML Computer Vision Data Scientist Software Development 81

Flipboard

OCTOBER 25, 2023

Unstructured data is information that doesn’t conform to a predefined schema or isn’t organized according to a preset data model. Unstructured information may have a little or a lot of structure but in ways that are unexpected or inconsistent. Additionally, we show how to use AWS AI/ML services for analyzing unstructured data.

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ML Metadata AI AI 165

AWS Machine Learning Blog

FEBRUARY 12, 2024

Sharing in-house resources with other internal teams, the Ranking team machine learning (ML) scientists often encountered long wait times to access resources for model training and experimentation – challenging their ability to rapidly experiment and innovate. If it shows online improvement, it can be deployed to all the users.

ML 128

ML Explainability Machine Learning Deep Learning 128

Flipboard

NOVEMBER 24, 2023

With that, the need for data scientists and machine learning (ML) engineers has grown significantly. These skilled professionals are tasked with building and deploying models that improve the quality and efficiency of BMW’s business processes and enable informed leadership decisions.

ML 149

ML DevOps Data Scientist ML Engineer 149

Marktechpost

SEPTEMBER 20, 2024

One alternative to fully-resolved simulations (FRS) is to use coarse grids, with closure models correcting for errors by approximating the missing fine-scale information. To address this, they developed a physics-informed neural operator (PINO) that eliminates the need for closure models and coarse-grid solvers.

Machine Learning 97

Machine Learning ML AI AI 97

Marktechpost

AUGUST 1, 2024

Information seeking and integration are critical processes that underpin analysis and decision-making across various fields. These processes demand significant time and effort, especially when dealing with complex queries that require thorough and precise information retrieval.

Large Language Models 116

Large Language Models AI AI ChatGPT 116

AWS Machine Learning Blog

OCTOBER 20, 2023

Customers of every size and industry are innovating on AWS by infusing machine learning (ML) into their products and services. Recent developments in generative AI models have further sped up the need of ML adoption across industries.

ML 119

ML Data Scientist ML Engineer Data Science 119

AWS Machine Learning Blog

NOVEMBER 29, 2023

Data preparation is a crucial step in any machine learning (ML) workflow, yet it often involves tedious and time-consuming tasks. With this integration, SageMaker Canvas provides customers with an end-to-end no-code workspace to prepare data, build and use ML and foundations models to accelerate time from data to business insights.

ML 122

ML Data Quality Automation Machine Learning 122

Marktechpost

AUGUST 25, 2024

However, a significant hurdle remains-LLMs can struggle with irrelevant information in problem descriptions, leading to a decline in their reasoning accuracy. Among the critical issues this research addresses is the influence of irrelevant information on LLM reasoning performance.

LLM 95

LLM Large Language Models Artificial Intelligence Artificial Intelligence 95

Marktechpost

JULY 27, 2024

These methods have the potential to greatly exaggerate published results, deceiving the scientific community and the general public about the actual effectiveness of ML models. Due to the intricacy of ML research, which includes pre-training, post-training, and evaluation stages, there is much potential for QRPs. Check out the Paper.

Machine Learning 110

Machine Learning ML Metadata Large Language Models 110

Marktechpost

SEPTEMBER 21, 2024

Researchers from Microsoft have introduced an innovative solution to these challenges with GRIN (GRadient-INformed Mixture of Experts). Furthermore, the model’s ability to avoid token dropping means it maintains a high level of accuracy and robustness across various tasks, unlike models that lose information during training.

Deep Learning 119

Deep Learning Natural Language Processing Computer Vision AI Researcher 119

Marktechpost

NOVEMBER 21, 2023

It ingeniously applies techniques from natural-language models, akin to ChatGPT, to reconstruct comprehensive information, like oceanic temperatures, from sparse data collected by a limited number of sensors. This ability holds immense value for global climate models, shedding light on crucial information for understanding climate dynamics.

Convolutional Neural Networks 101

Convolutional Neural Networks Neural Network Artificial Intelligence Artificial Intelligence 101