The MLOps Blog

NOVEMBER 14, 2023

Deep learning models are typically highly complex. While many traditional machine learning models make do with just a couple of hundreds of parameters, deep learning models have millions or billions of parameters. The reasons for this range from wrongly connected model components to misconfigured optimizers.

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AI Weekly

OCTOBER 26, 2023

cryptopolitan.com Applied use cases Alluxio rolls out new filesystem built for deep learning Alluxio Enterprise AI is aimed at data-intensive deep learning applications such as generative AI, computer vision, natural language processing, large language models and high-performance data analytics.

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Marktechpost

JULY 2, 2023

Recently, neural fields have gained a lot of traction in computer vision as a means of representing signals like pictures, 3D shapes/scenes, movies, music, medical images, and weather data. Prior functa work demonstrated that deep learning on neural fields is possible for many different modalities, even with relatively small datasets.

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Marktechpost

JULY 12, 2023

ResNet expands on this achievement by including identity mappings through shortcut connections, enabling the training of deep neural networks with good performance across various computer vision applications, including image classification, object identification, and semantic segmentation.

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Marktechpost

SEPTEMBER 21, 2024

Artificial intelligence (AI) research has increasingly focused on enhancing the efficiency & scalability of deep learning models. These models have revolutionized natural language processing, computer vision, and data analytics but have significant computational challenges.

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Marktechpost

OCTOBER 18, 2023

The idea of compilation is a potentially effective remedy that can balance the needs for computing efficiency and model size. In recent research, a team of researchers has introduced a deep learning compiler specifically made for neural network training.

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Marktechpost

SEPTEMBER 4, 2023

The researchers improved the program’s ability to measure how bad the problem was. Researchers also categorized the type of spine curve just by looking at one picture. This problem statement fell under the class of Computer Vision and was a classification approach. If you like our work, you will love our newsletter.

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AI Weekly

APRIL 11, 2024

Generative AI is igniting a new era of innovation within the back office. And this is particularly true for accounts payable (AP) programs, where AI, coupled with advancements in deep learning, computer vision and natural language processing (NLP), is helping drive increased efficiency, accuracy and cost savings for businesses.

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Marktechpost

SEPTEMBER 6, 2023

With the advancements in machine learning and deep learning techniques, there has also been an increase in automation of various dimensions. To overcome this problem, researchers from Skoltech and other institutions have devised a new way to distinguish weighted goods at a supermarket.

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Marktechpost

JULY 12, 2023

Advances in Deep Learning Methodologies are greatly impacting the Artificial Intelligence community. Deep Learning techniques are being widely used in almost every industry, be it healthcare, social media, engineering, finance, or education.

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Unite.AI

NOVEMBER 20, 2024

Driven by a passion for the convergence of technology and medicine, he enthusiastically balances his roles as a practicing radiologist, Assistant Professor of Radiology at Baylor College of Medicine, and AI researcher. AI will further enhance navigation capabilities with locally embedded computer vision and path planning models.

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Marktechpost

DECEMBER 5, 2023

University Teknikal Malaysia Melaka (UTeM) researchers have formulated an approach to Human Activity Recognition (HAR) to tackle traditional limitations. They have introduced a system that leverages Channel State Information (CSI) and advanced deep learning techniques. If you like our work, you will love our newsletter.

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IBM Journey to AI blog

OCTOBER 12, 2023

Unlike basic machine learning models, deep learning models allow AI applications to learn how to perform new tasks that need human intelligence, engage in new behaviors and make decisions without human intervention. Emotion AI is a theory of mind AI currently in development.

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Marktechpost

NOVEMBER 16, 2023

To efficiently handle hyperparameter optimization (HPO) for deep chemical models, the paper introduces a technique called Training Performance Estimation (TPE), adapting it from a method used in computer vision architectures. All credit for this research goes to the researchers of this project.

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AI Weekly

JULY 13, 2023

theguardian.com Sarah Silverman sues OpenAI and Meta claiming AI training infringed copyright The US comedian and author Sarah Silverman is suing the ChatGPT developer OpenAI and Mark Zuckerberg’s Meta for copyright infringement over claims that their artificial intelligence models were trained on her work without permission.

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AI Weekly

SEPTEMBER 28, 2023

Rule-based chatbots rely on pre-defined conditions and keywords to provide responses, lacking the ability to adapt to context or learn from previous interactions. makeuseof.com Computer vision's next breakthrough Computer vision can do more than reduce costs and improve quality.

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Marktechpost

NOVEMBER 16, 2023

Thanks to developments in deep learning approaches, the capability of image analysis algorithms has been greatly enhanced. As a result of improvements in data storage, processing speed, and algorithm quality, larger samples have been used in radiological research. If you like our work, you will love our newsletter.

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Marktechpost

AUGUST 19, 2023

This falls under a broad category of Computer Vision. A team of researchers from Chongqing University designed a new system that could enhance these nanohole arrays into structural colors. They also used various Machine Learning models in designing this system.

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Marktechpost

JANUARY 4, 2024

Also, don’t forget to join our 35k+ ML SubReddit , 41k+ Facebook Community, Discord Channel , LinkedIn Gr oup , Twitter , and Email Newsletter , where we share the latest AI research news, cool AI projects, and more. If you like our work, you will love our newsletter.

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Marktechpost

OCTOBER 5, 2023

In computer vision and human-computer interaction, the critical task of face orientation estimation has emerged as a pivotal component with multifaceted applications. In response to these challenges, researchers from the Shibaura Institute of Technology in Japan have pioneered a novel AI solution.

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Towards AI

DECEMBER 16, 2024

The Top 10 AI Research Papers of 2024: Key Takeaways and How You Can Apply Them Photo by Maxim Tolchinskiy on Unsplash As the curtains draw on 2024, its time to reflect on the innovations that have defined the year in AI. So, grab a coffee (or a milkshake, if youre like me) and lets explore the top AI research papers of 2024.

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Marktechpost

OCTOBER 10, 2023

Deep learning, a machine learning subset, automatically learns complex representations from the input. Convolutional neural networks (CNNs) and vision transformers (ViT), two examples of deep learning models for computer vision, analyze signals by assuming planar (flat) regions.

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AI Weekly

DECEMBER 14, 2023

businessinsider.com Research 10 GitHub Repositories to Master Machine Learning It covers a wide range of topics such as Quora, blogs, interviews, Kaggle competitions, cheat sheets, deep learning frameworks, natural language processing, computer vision, various machine learning algorithms, and ensembling techniques.

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Towards AI

DECEMBER 16, 2024

The Top 10 AI Research Papers of 2024: Key Takeaways and How You Can Apply Them Photo by Maxim Tolchinskiy on Unsplash As the curtains draw on 2024, its time to reflect on the innovations that have defined the year in AI. So, grab a coffee (or a milkshake, if youre like me) and lets explore the top AI research papers of 2024.

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AI Researcher AI Research Computer Vision Neural Network 98

Towards AI

DECEMBER 16, 2024

The Top 10 AI Research Papers of 2024: Key Takeaways and How You Can Apply Them Photo by Maxim Tolchinskiy on Unsplash As the curtains draw on 2024, its time to reflect on the innovations that have defined the year in AI. So, grab a coffee (or a milkshake, if youre like me) and lets explore the top AI research papers of 2024.

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AI Researcher AI Research Computer Vision Neural Network 98

Towards AI

DECEMBER 16, 2024

The Top 10 AI Research Papers of 2024: Key Takeaways and How You Can Apply Them Photo by Maxim Tolchinskiy on Unsplash As the curtains draw on 2024, its time to reflect on the innovations that have defined the year in AI. So, grab a coffee (or a milkshake, if youre like me) and lets explore the top AI research papers of 2024.

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Marktechpost

DECEMBER 8, 2023

A team of researchers from Meta AI and the University of Maryland tackled the problem of object recognition by developing a new method that utilizes a language decoder to predict text tokens from image embeddings and form labels. Object recognition, predating the deep learning era, has aided in image annotation.

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Pickl AI

DECEMBER 26, 2024

Summary: Amazon’s Ultracluster is a transformative AI supercomputer, driving advancements in Machine Learning, NLP, and robotics. Its high-performance architecture accelerates AI research, benefiting healthcare, finance, and entertainment industries.

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Allen AI

JUNE 20, 2023

AI Researcher, Executive, and Forbes Top 5 AI Entrepreneur Ali Farhadi to Lead Institute’s Next Chapter The Allen Institute for Artificial Intelligence (AI2) today announced Ali Farhadi will become its new Chief Executive Officer, effective July 31. As an AI professor in the Paul G. Brainchild of the late Paul G.

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Marktechpost

OCTOBER 27, 2023

Because they have orders of magnitude cheaper processing costs than cutting-edge NWP models, data-driven Deep Learning (DL) models are becoming more and more popular for weather forecasting. Building data-driven models for predicting the large-scale circulation of the atmosphere has been the subject of several research.

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Marktechpost

SEPTEMBER 30, 2023

In the realm of computer vision, a persistent challenge has perplexed researchers: altering an object’s camera viewpoint with just a single RGB image. However, researchers at Columbia University have introduced the revolutionary Zero-1-to-3 framework. If you like our work, you will love our newsletter.

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Topbots

DECEMBER 5, 2023

Top 10 AI Research Papers 2023 1. Sparks of AGI by Microsoft Summary In this research paper, a team from Microsoft Research analyzes an early version of OpenAI’s GPT-4, which was still under active development at the time. Sign up for more AI research updates. Enjoy this article?

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Marktechpost

NOVEMBER 25, 2023

Data augmentation is a critical technique in deep learning that involves creating new training data by modifying existing samples. Creating variations of existing samples prevents overfitting and helps the model learn more robust and adaptable features, which is crucial for accurate predictions in real-world scenarios.

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Unite.AI

OCTOBER 22, 2024

Understanding Computational Complexity in AI The performance of AI models depends heavily on computational complexity. In AI, particularly in deep learning , this often means dealing with a rapidly increasing number of computations as models grow in size and handle larger datasets.

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Marktechpost

SEPTEMBER 12, 2023

Image-to-image translation (I2I) is an interesting field within computer vision and machine learning that holds the power to transform visual content from one domain into another seamlessly. All Credit For This Research Goes To the Researchers on This Project. If you like our work, you will love our newsletter.

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Viso.ai

DECEMBER 20, 2023

Huawei’s Mindspore is an open-source deep learning framework for training and inference written in C++. license, MindSpore AI allows users to use, modify, and distribute the software. Our no-code solution enables teams to rapidly build real-world computer vision using the latest deep learning models out of the box.

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Viso.ai

FEBRUARY 11, 2024

The developers of Detectron2 are Meta’s Facebook AI Research (FAIR) team, who have stated that “Our goal with Detectron2 is to support the wide range of cutting-edge object detection and segmentation models available today, but also to serve the ever-shifting landscape of cutting-edge research.”

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