Flipboard

NOVEMBER 6, 2024

We developed and validated a deep learning model designed to identify pneumoperitoneum in computed tomography images. Delays or misdiagnoses in detecting pneumoperitoneum can significantly increase mortality and morbidity. External validation included 480 scans from Cedars-Sinai Medical Center. and a specificity of 0.97–0.99

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Smart Data Collective

DECEMBER 1, 2022

As we look ahead to 2022, there are four key trends that organizations should be aware of when it comes to big data: cloud computing, artificial intelligence, automated streaming analytics, and edge computing. This post outlines five current trends in big data for 2022 and beyond. The Rise of Streaming Analytics.

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Google Research AI blog

FEBRUARY 14, 2023

As we do this, we’re transforming robot learning into a scalable data problem so that we can scale learning of generalized low-level skills, like manipulation. In this blog post, we’ll review key learnings and themes from our explorations in 2022.

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Applied Data Science

DECEMBER 23, 2022

Just wait until you hear what happened in 2022. In our review of 2019 we talked a lot about reinforcement learning and Generative Adversarial Networks (GANs), in 2020 we focused on Natural Language Processing (NLP) and algorithmic bias, in 202 1 Transformers stole the spotlight. In 2022 we got diffusion models ( NeurIPS paper ).

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Towards AI

NOVEMBER 16, 2024

Keswani’s Algorithm introduces a novel approach to solving two-player non-convex min-max optimization problems, particularly in differentiable sequential games where the sequence of player actions is crucial. Keswani’s Algorithm: The algorithm essentially makes response function : maxy∈{R^m} f (.,

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PyImageSearch

JANUARY 30, 2023

This last blog of the series will cover the benefits, applications, challenges, and tradeoffs of using deep learning in the education sector. To learn about Computer Vision and Deep Learning for Education, just keep reading. As soon as the system adapts to human wants, it automates the learning process accordingly.

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Google Research AI blog

FEBRUARY 21, 2023

In 2022, we leveraged recent advances in deep learning to accurately predict protein function from raw amino acid sequences. Feeding data from quantum sensors directly to quantum algorithms without going through classical measurements may provide a large advantage.

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Google Research AI blog

FEBRUARY 23, 2023

Commensurate with our mission to demonstrate these societal benefits , Google Research’s programs in applied machine learning (ML) have helped place Alphabet among the top five most impactful corporate research institutions in the health and life sciences publications on the Nature Impact Index in every year from 2019 through 2022.

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Data Science Dojo

JUNE 26, 2023

In order to learn the nuances of language and to respond coherently and pertinently, deep learning algorithms are used along with a large amount of data. The BERT algorithm has been trained on 3.3 A prompt is given to GPT-3 and it produces very accurate human-like text output based on deep learning.

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Dataconomy

MAY 23, 2023

AI-generated images are the result of intricate algorithms, deep learning models, and neural networks. AI art can be seen as a form of computational creativity where algorithms and software are used to generate novel and expressive images, sounds, texts, or other forms of media. What is AI art?

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Heartbeat

NOVEMBER 27, 2023

Deep learning automates and improves medical picture analysis. Convolutional neural networks (CNNs) can learn complicated patterns and features from enormous datasets, emulating the human visual system. Convolutional Neural Networks (CNNs) Deep learning in medical image analysis relies on CNNs.

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Heartbeat

NOVEMBER 21, 2023

Computer vision, the field dedicated to enabling machines to perceive and understand visual data, has witnessed a monumental shift in recent years with the advent of deep learning. Photo by charlesdeluvio on Unsplash Welcome to a journey through the advancements and applications of deep learning in computer vision.

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Dataconomy

FEBRUARY 26, 2024

This attribute is particularly beneficial for algorithms that thrive on parallelization, effectively accelerating tasks that range from complex simulations to deep learning model training. Their architecture is a beacon of parallel processing capability, enabling the execution of thousands of tasks simultaneously.

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Towards AI

MAY 13, 2024

Since the emergence of ChatGPT in 2022, AI has dominated discussions. This synergy enables AI supercomputers to leverage HPC capabilities, optimizing performance for demanding AI tasks like training deep learning models or image recognition algorithms.

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PyImageSearch

JANUARY 2, 2023

This blog will cover the benefits, applications, challenges, and tradeoffs of using deep learning in healthcare. Computer Vision and Deep Learning for Healthcare Benefits Unlocking Data for Health Research The volume of healthcare-related data is increasing at an exponential rate.

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Google Research AI blog

FEBRUARY 28, 2023

In 2022, we expanded our research interactions and programs to faculty and students across Latin America , which included grants to women in computer science in Ecuador. We also help make global conferences accessible to more researchers around the world, for example, by funding 24 students this year to attend Deep Learning Indaba in Tunisia.

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ML @ CMU

JANUARY 2, 2025

We hypothesize that this architecture enables higher efficiency in learning the structure of natural tasks and better generalization in tasks with a similar structure than those with less specialized modules. 2022 ; Mittal et al., Previous works ( Goyal et al., 2018 ) to enhance training (see Materials and Methods in Zhang et al.,

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ODSC - Open Data Science

FEBRUARY 17, 2023

Natural language processing (NLP) has been growing in awareness over the last few years, and with the popularity of ChatGPT and GPT-3 in 2022, NLP is now on the top of peoples’ minds when it comes to AI. Developing NLP tools isn’t so straightforward, and requires a lot of background knowledge in machine & deep learning, among others.

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Dataconomy

APRIL 27, 2023

Rapid progress in AI has been made in recent years due to an abundance of data, high-powered processing hardware, and complex algorithms. AI computing is the use of computer systems and algorithms to perform tasks that would typically require human intelligence What is an AI computer?

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Heartbeat

FEBRUARY 28, 2023

The past few years have witnessed exponential growth in medical image analysis using deep learning. In this article we will look into medical image segmentation and see how deep learning can be helpful in these cases. Finally, we will look at some of the recent semi-supervised medical image segmentation algorithms.

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AssemblyAI

MARCH 21, 2023

Top 50 keywords in submitted research papers at ICLR 2022 ( source ) A recent bibliometric study systematically analysed this research trend, revealing an exponential growth of published research involving GNNs, with a striking +447% average annual increase in the period 2017-2019.

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Flipboard

JUNE 20, 2023

We present the results of recent performance and power draw experiments conducted by AWS that quantify the energy efficiency benefits you can expect when migrating your deep learning workloads from other inference- and training-optimized accelerated Amazon Elastic Compute Cloud (Amazon EC2) instances to AWS Inferentia and AWS Trainium.

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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, 2014. [3]

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Google Research AI blog

FEBRUARY 2, 2023

Great machine learning (ML) research requires great systems. With the increasing sophistication of the algorithms and hardware in use today and with the scale at which they run, the complexity of the software necessary to carry out day-to-day tasks only increases. You can find other posts in the series here.)

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Dataconomy

MAY 8, 2023

AI drawing generators use machine learning algorithms to produce artwork What is AI drawing? You might think of AI drawing as a generative art where the artist combines data and algorithms to create something completely new. They use deep learning models to learn from large sets of images and make new ones that meet the prompts.

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Smart Data Collective

JUNE 22, 2023

Taking the world by storm, artificial intelligence and machine learning software are changing the landscape in many fields. Earlier today, one analysis found that the market size for deep learning was worth $51 billion in 2022 and it will grow to be worth $1.7 Amazon has a very good overview if you want to learn more.

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Becoming Human

MARCH 16, 2023

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. Since the advent of deep learning in the 2000s, AI applications in healthcare have expanded. A few AI technologies are empowering drug design.

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Dataconomy

FEBRUARY 6, 2024

This popularity is primarily due to the spread of big data and advancements in algorithms. Going back from the times when AI was merely associated with futuristic visions to today’s reality, where ML algorithms seamlessly navigate our daily lives. These technologies have undergone a profound evolution. billion by 2032.

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Dataversity

DECEMBER 15, 2021

The new year will bring us many exciting developments in data-enabling technologies including the merging of artificial intelligence with quantum computing and graph neural networks, which will power extremely complex, next-generation algorithms. Knowledge graphs will become lego-like with the ability to be plugged into diverse applications.

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Google Research AI blog

APRIL 18, 2023

Posted by Badih Ghazi, Staff Research Scientist, and Nachiappan Valliappan, Staff Software Engineer, Google Research Recently, differential privacy (DP) has emerged as a mathematically robust notion of user privacy for data aggregation and machine learning (ML), with practical deployments including the 2022 US Census and in industry.

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NYU Center for Data Science

JULY 5, 2024

The S4MI pipeline addresses a critical bottleneck in the advancement of clinical treatments: the heavy reliance on supervised learning techniques that require large amounts of annotated data. This process is not only costly but also incredibly time-consuming, demanding extensive involvement from clinical specialists. “A

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Flipboard

JULY 10, 2023

Figure 5: Architecture of Convolutional Autoencoder for Image Segmentation (source: Bandyopadhyay, “Autoencoders in Deep Learning: Tutorial & Use Cases [2023],” V7Labs , 2023 ). VAEs can generate new samples from the learned latent distribution, making them ideal for image generation and style transfer tasks.

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Google Research AI blog

FEBRUARY 2, 2023

For research, it has not only reduced language model latency for users , designed computer architectures , accelerated hardware , assisted protein discovery , and enhanced robotics , but also provided a reliable backend interface for users to search for neural architectures and evolve reinforcement learning algorithms.

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DrivenData Labs

JUNE 14, 2023

In December 2022, DrivenData and Meta AI launched the Video Similarity Challenge. Between December 2022 and April 2023, 404 participants from 59 countries signed up to solve the problems posed by the two tracks, and 82 went on to submit solutions. His research interest is deep metric learning and computer vision.

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IBM Journey to AI blog

DECEMBER 20, 2023

Each type and sub-type of ML algorithm has unique benefits and capabilities that teams can leverage for different tasks. What is machine learning? Instead of using explicit instructions for performance optimization, ML models rely on algorithms and statistical models that deploy tasks based on data patterns and inferences.

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BAIR

APRIL 6, 2023

These robots use recent advances in deep learning to operate autonomously in unstructured environments. By pooling data from all robots in the fleet, the entire fleet can efficiently learn from the experience of each individual robot. Using this formalism, we can now instantiate and compare IFL algorithms (i.e.,

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NYU Center for Data Science

MAY 31, 2023

CDS Assistant Professor/Faculty Fellow Jacopo Cirrone works at the intersection of machine learning and healthcare, recently publishing two papers that expand deep learning research within these fields. In this study, we developed effective deep learning approaches for segmentation and classification.

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