AI Weekly

JUNE 22, 2023

marketscreener.com The Pace Of AI Innovation For Cybersecurity Is Fast And Furious Within the broad scope of AI, the real applications of machine learning (ML) and deep learning (DL) algorithm models are offering significant benefits to bolster enterprise cybersecurity.

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AssemblyAI

NOVEMBER 9, 2023

The models are powered by advanced Deep Learning and Machine Learning research. In Natural Language Processing, or NLP, Text Summarization refers to the process of using Deep Learning and Machine Learning models to synthesize large bodies of texts into their most important parts. 67:34: He said the U.S.

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Towards AI

AUGUST 25, 2023

Machine learning (ML) is a subset of AI that provides computer systems the ability to automatically learn and improve from experience without being explicitly programmed. In ML, there are a variety of algorithms that can help solve problems. Any competent software engineer can implement any algorithm. 12, 2021. [6]

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Flipboard

JULY 10, 2023

RF Diffusion, a deep learning tool. Senior scientist Bobby Langan shows a video of one of his favorite deep-learning tools, used to create experimental cancer therapeutics. Senior scientist Bobby Langan shows a video of one of his favorite deep-learning tools, used to create experimental cancer therapeutics.

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Heartbeat

NOVEMBER 14, 2023

For many years, gradient-boosting models and deep-learning solutions have won the lion's share of Kaggle competitions. XGBoost is not limited to machine learning tasks, as its incredible power can be harnessed when harmonized with deep learning algorithms. 2 (2021): 522–531. . "ConvXGB:

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Viso.ai

DECEMBER 3, 2023

This article will provide an introduction to object detection and provide an overview of the state-of-the-art computer vision object detection algorithms. The recent deep learning algorithms provide robust person detection results. Most modern person detector techniques are trained on frontal and asymmetric views.

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Marktechpost

JULY 23, 2023

The number of AI and, in particular, machine learning (ML) publications related to medical imaging has increased dramatically in recent years. A current PubMed search using the Mesh keywords “artificial intelligence” and “radiology” yielded 5,369 papers in 2021, more than five times the results found in 2011.

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Flipboard

JUNE 20, 2023

Rather than humans programming computers with specific step-by-step instructions on how to complete a task, in machine learning a human provides the AI with data and asks it to achieve a certain outcome via an algorithm. Deep learning Deep learning is a specific type of machine learning used in the most powerful AI systems.

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Heartbeat

OCTOBER 18, 2023

In this article, we embark on a journey to explore the transformative potential of deep learning in revolutionizing recommender systems. However, deep learning has opened new horizons, allowing recommendation engines to unravel intricate patterns, uncover latent preferences, and provide accurate suggestions at scale.

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Becoming Human

MARCH 16, 2023

Overhyped or not, investments in AI drug discovery jumped from $450 million in 2014 to a whopping $58 billion in 2021. AI began back in the 1950s as a simple series of “if, then rules” and made its way into healthcare two decades later after more complex algorithms were developed. AI drug discovery is exploding.

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Dlabs.ai

AUGUST 31, 2021

And you can expect them to cover topics as far-flung as business intelligence, machine learning, deep learning, AI algorithms, virtual assistants, and chatbots. Big Data Conference Europe 2021 Date: September 28-30th Place: Online Ticket: 238 – 544 EUR The Big Data Conference covers more than its name suggests.

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Applied Data Science

JANUARY 4, 2022

Hiding your 2021 resolution list under a glass of champagne? To write this post we shook the internet upside down for industry news and research breakthroughs and settled on the following 5 themes, to wrap up 2021 in a neat bow: ? In 2021, the following were added to the ever growing list of Transformer applications.

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Viso.ai

DECEMBER 19, 2023

Image Classification Using Machine Learning CNN Image Classification (Deep Learning) Example applications of Image Classification Let’s dive deep into it! It uses AI-based deep learning models to analyze images with results that for specific tasks already surpass human-level accuracy (for example, in face recognition ).

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Viso.ai

OCTOBER 9, 2024

Human-machine interaction is an important area of research where machine learning algorithms with visual perception aim to gain an understanding of human interaction. State-of-the-art emotion AI Algorithms Outlook, current research, and applications What Is AI Emotion Recognition? About us: Viso.ai What is Emotion AI?

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PyImageSearch

OCTOBER 28, 2024

One day, I was looking for an email idea while writing my daily self-driving car newsletter , when I was suddenly caught by the news: Tesla had released a new FSD12 model based on End-to-End Learning. And it was because not only was the new model fully based on Deep Learning, but it also effectively removed 300,000 lines of code.

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IBM Journey to AI blog

AUGUST 1, 2023

It’s the underlying engine that gives generative models the enhanced reasoning and deep learning capabilities that traditional machine learning models lack. Foundation models: The driving force behind generative AI Also known as a transformer, a foundation model is an AI algorithm trained on vast amounts of broad data.

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Applied Data Science

AUGUST 2, 2021

This post is a bitesize walk-through of the 2021 Executive Guide to Data Science and AI  — a white paper packed with up-to-date advice for any CIO or CDO looking to deliver real value through data. Machine learning The 6 key trends you need to know in 2021 ? Download the free, unabridged version here.

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NVIDIA Developer

MAY 21, 2021

Thursday, June 10, 2021 - 09:00 Indian/Maldives Speakers Pallab Maji Senior Solutions Architect - Deep Learning at NVIDIA NVIDIA Pallab is fascinated with artificial intelligence and works on machine learning for computer vision and natural language processing. Capacity: 999 Status: Open

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Sebastian Ruder

JANUARY 24, 2022

2021) 2021 saw many exciting advances in machine learning (ML) and natural language processing (NLP).   2021 saw the continuation of the development of ever larger pre-trained models. 2021 saw the development of alternative model architectures that are viable alternatives to the transformer. style loss.

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Marktechpost

JULY 24, 2023

Many studies have been motivated to explore hidden hierarchical patterns in the large volume of weather datasets for weather forecasting due to the recent development of deep learning techniques, the widespread availability of massive weather observation data, and the advent of information and computer technology.

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Heartbeat

MAY 23, 2023

As technology continues to improve exponentially, deep learning has emerged as a critical tool for enabling machines to make decisions and predictions based on large volumes of data. Edge computing may change how we think about deep learning. Standardizing model management can be tricky but there is a solution.

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AWS Machine Learning Blog

OCTOBER 5, 2023

Xin Huang is a Senior Applied Scientist for Amazon SageMaker JumpStart and Amazon SageMaker built-in algorithms. He focuses on developing scalable machine learning algorithms. an AI start-up, and worked as the CEO and Chief Scientist in 2019–2021. Yida Wang is a principal scientist in the AWS AI team of Amazon.

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Viso.ai

NOVEMBER 28, 2024

The majority of contemporary computer vision algorithms are also excellent at capturing high-level aspects of a picture, but as they process data, they lose fine-grained details. What is a FeatUp Algorithm? introduced FeatUp, a task- and model-agnostic framework to restore lost spatial information in deep features. Hamilton, S.

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NVIDIA Developer

MAY 21, 2021

Deep learning is a powerful AI approach that uses multi-layered artificial neural networks to deliver state-of-the-art accuracy in tasks such as object detection, speech recognition, and language translation. You’ll train deep learning models from scratch, learning tools and tricks to achieve highly accurate results.

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Viso.ai

DECEMBER 10, 2023

Image recognition with deep learning is a key application of AI vision and is used to power a wide range of real-world use cases today. I n past years, machine learning, in particular deep learning technology , has achieved big successes in many computer vision and image understanding tasks.

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Mlearning.ai

APRIL 8, 2023

Charting the evolution of SOTA (State-of-the-art) techniques in NLP (Natural Language Processing) over the years, highlighting the key algorithms, influential figures, and groundbreaking papers that have shaped the field. NLP algorithms help computers understand, interpret, and generate natural language.

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Viso.ai

MAY 20, 2023

The YOLOv7 algorithm is making big waves in the computer vision and machine learning communities. In this article, we will provide the basics of how YOLOv7 works and what makes it the best object detector algorithm available today. The original YOLO object detector was first released in 2016.

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Flipboard

JULY 10, 2023

Figure 4: Architecture of fully connected autoencoders (source: Amor, “Comprehensive introduction to Autoencoders,” ML Cheat Sheet , 2021 ). Figure 5: Architecture of Convolutional Autoencoder for Image Segmentation (source: Bandyopadhyay, “Autoencoders in Deep Learning: Tutorial & Use Cases [2023],” V7Labs , 2023 ).

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Unite.AI

MAY 10, 2024

Realizing that many of the tedious development processes in Mellanox could be automated by machine-learning algorithms, I changed my majors to optimization and machine learning and completed an MSc in the space. At Visualead, we’d been running algorithms on mobile devices since 2012, including models.

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AWS Machine Learning Blog

DECEMBER 2, 2024

Over the past decade, advancements in deep learning have spurred a shift toward so-called global models such as DeepAR [3] and PatchTST [4]. AutoGluon predictors can be seamlessly deployed to SageMaker using AutoGluon-Cloud and the official Deep Learning Containers. Journal of Machine Learning Research 21, no.

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Shreyansh Singh

DECEMBER 17, 2021

In my last post, I covered a high-level overview of Federated Learning, its applications, advantages & challenges. We also went through a high-level overview of how Federated Optimization algorithms work. But from a mathematical sense, how is Federated Learning training actually performed? But why make this change?

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ODSC - Open Data Science

FEBRUARY 28, 2023

Tangent Works Recognized by Gartner as a Cool Vendor in 2021, Tangent Works’ goal is to help organizations effectively utilize their time-series data for predictive models. Cloudera For Cloudera, it’s all about machine learning optimization.

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AWS Machine Learning Blog

MAY 30, 2023

In 2021, we launched AWS Support Proactive Services as part of the AWS Enterprise Support plan. Since its introduction, we’ve helped hundreds of customers optimize their workloads, set guardrails, and improve the visibility of their machine learning (ML) workloads’ cost and usage.

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The Stanford AI Lab Blog

DECEMBER 6, 2021

The thirty-fifth Conference on Neural Information Processing Systems (NeurIPS) 2021 is being hosted virtually from Dec 6th - 14th. Some of the members in our SAIL community also serve as co-organizers of several exciting workshops that will take place on Dec 13-14, so we hope you will check them out!

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Towards AI

JULY 20, 2023

As the capabilities of high-powered computers and ML algorithms have grown, so have opportunities to improve the SLR process. New research has also begun looking at deep learning algorithms for automatic systematic reviews, According to van Dinter et al.

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ODSC - Open Data Science

MARCH 22, 2023

Many companies are now utilizing data science and machine learning , but there’s still a lot of room for improvement in terms of ROI. Nevertheless, we are still left with the question: How can we do machine learning better? billion in 2022, an increase of 21.3% billion in 2022, an increase of 21.3%

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AWS Machine Learning Blog

DECEMBER 20, 2023

SageMaker JumpStart is the machine learning (ML) hub of Amazon SageMaker that provides access to foundation models in addition to built-in algorithms and end-to-end solution templates to help you quickly get started with ML. About the authors Dr. Kyle Ulrich is an Applied Scientist with the Amazon SageMaker built-in algorithms team.

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