AWS Machine Learning Blog

FEBRUARY 12, 2025

This concept is similar to knowledge distillation used in deep learning, except that were using the teacher model to generate a new dataset from its knowledge rather than directly modifying the architecture of the student model. The following diagram illustrates the overall flow of the solution. Yiyue holds a Ph.D.

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Towards AI

MARCH 11, 2025

Ilya Sutskever, previously at Google and OpenAI, has been intimately involved in many of the major Deep Learning and LLMs breakthroughs in the past 1015 years. Ilya has consistently been central to major breakthroughs in deep learning scaling laws and training objectives for LLMs, making it plausible hes discovered yet another one.

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Analytics Vidhya

FEBRUARY 16, 2022

Since 2012 after convolutional neural networks(CNN) were introduced, we moved away from handcrafted features to an end-to-end approach using deep neural networks. This article was published as a part of the Data Science Blogathon. Introduction Computer vision is a field of A.I. These are easy to develop […].

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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. CT scans are routinely used to diagnose pneumoperitoneum.

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NYU Center for Data Science

DECEMBER 11, 2024

While scientists typically use experiments to understand natural phenomena, a growing number of researchers are applying the scientific method to study something humans created but dont fully comprehend: deep learning systems. The organizers saw a gap between deep learnings two traditional camps.

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Data Science Dojo

MARCH 4, 2024

Emerging as a key player in deep learning (2010s) The decade was marked by focusing on deep learning and navigating the potential of AI. Launch of Kepler Architecture: NVIDIA launched the Kepler architecture in 2012. It provided optimized codes for deep learning models.

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Hacker News

SEPTEMBER 24, 2021

Deep learning is now being used to translate between languages, predict how proteins fold , analyze medical scans , and play games as complex as Go , to name just a few applications of a technique that is now becoming pervasive. Although deep learning's rise to fame is relatively recent, its origins are not.

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Hacker News

OCTOBER 11, 2024

Deep learning — a software model that relies on billions of neurons and trillions of connections — requires immense computational power. In 2012, a breakthrough came when Alex Krizhevsky from the University of Toronto used NVIDIA GPUs to win the ImageNet image recognition competition.

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Hacker News

DECEMBER 12, 2024

She played a major role in the deep learning revolution by laboring for years to create the ImageNet dataset and competition, which challenged AI systems to recognize objects and animals across 1,000 categories. Stanford University professor Fei-Fei Li has already earned her place in the history of AI.

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AWS Machine Learning Blog

JUNE 6, 2023

This post further walks through a step-by-step implementation of fine-tuning a RoBERTa (Robustly Optimized BERT Pretraining Approach) model for sentiment analysis using AWS Deep Learning AMIs (AWS DLAMI) and AWS Deep Learning Containers (DLCs) on Amazon Elastic Compute Cloud (Amazon EC2 p4d.24xlarge)

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AWS Machine Learning Blog

JUNE 15, 2023

Dive into Deep Learning ( D2L.ai ) is an open-source textbook that makes deep learning accessible to everyone. If you are interested in learning more about these benchmark analyses, refer to Auto Machine Translation and Synchronization for “Dive into Deep Learning”.

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Towards AI

FEBRUARY 10, 2023

In 2018, OpenAI released an analysis showing that since 2012, the amount of computing used in the largest AI training runs has been increasing exponentially, with a doubling time of 3–4 months [8]. By comparison, Moore’s Law had a 2-year doubling period.

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AWS Machine Learning Blog

APRIL 16, 2024

It employs advanced deep learning technologies to understand user input, enabling developers to create chatbots, virtual assistants, and other applications that can interact with users in natural language.

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Mlearning.ai

APRIL 8, 2023

Deep Learning (Late 2000s — early 2010s) With the evolution of needing to solve more complex and non-linear tasks, The human understanding of how to model for machine learning evolved. Use Cases : Web Search, Information Retrieval, Text Mining Significant papers: “ Latent Dirichlet Allocation ” by Blei et al.

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AWS Machine Learning Blog

JULY 10, 2025

By accessing familiar model development features, data scientists can maintain their established workflows, preserve their productivity tools, and seamlessly develop, train, and deploy machine learning, deep learning and generative AI models.

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ODSC - Open Data Science

FEBRUARY 28, 2023

CARTO Since its founding in 2012, CARTO has helped hundreds of thousands of users utilize spatial analytics to improve key business functions such as delivery routes, product/store placements, behavioral marketing, and more.

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Dataconomy

JUNE 15, 2023

Another significant milestone came in 2012 when Google X’s AI successfully identified cats in videos using over 16,000 processors. This demonstrated the astounding potential of machines to learn and differentiate between various objects.

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Dataconomy

OCTOBER 22, 2024

When AlexNet, a CNN-based model, won the ImageNet competition in 2012, it sparked widespread adoption in the industry. These datasets provide the necessary scale for training advanced machine learning models, which would be difficult for most academic labs to collect independently.

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IBM Journey to AI blog

OCTOBER 12, 2023

However, AI capabilities have been evolving steadily since the breakthrough development of artificial neural networks in 2012, which allow machines to engage in reinforcement learning and simulate how the human brain processes information.

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Heartbeat

DECEMBER 14, 2023

LeCun received the 2018 Turing Award (often referred to as the "Nobel Prize of Computing"), together with Yoshua Bengio and Geoffrey Hinton, for their work on deep learning. Hinton is viewed as a leading figure in the deep learning community. > Finished chain. ") > Entering new AgentExecutor chain.

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Mlearning.ai

MARCH 9, 2023

Automated algorithms for image segmentation have been developed based on various techniques, including clustering, thresholding, and machine learning (Arbeláez et al., 2012; Otsu, 1979; Long et al., 2019) proposed a novel adversarial training framework for improving the robustness of deep learning-based segmentation models.

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Mlearning.ai

JUNE 14, 2023

Learning LLMs (Foundational Models) Base Knowledge / Concepts: What is AI, ML and NLP Introduction to ML and AI — MFML Part 1 — YouTube What is NLP (Natural Language Processing)? — YouTube YouTube Introduction to Natural Language Processing (NLP) NLP 2012 Dan Jurafsky and Chris Manning (1.1)

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ODSC - Open Data Science

JUNE 8, 2023

Valohai Valohai enables ML Pioneers to continue to work at the cutting edge of technology with its MLOps which enables its clients to reduce the amount of time required to build, test, and deploy deep learning models by a factor of 10.

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AWS Machine Learning Blog

SEPTEMBER 11, 2024

in 2012 is now widely referred to as ML’s “Cambrian Explosion.” Together, these elements lead to the start of a period of dramatic progress in ML, with NN being redubbed deep learning. FP16 is used in deep learning where computational speed is valued, and the lower precision won’t drastically affect the model’s performance.

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Heartbeat

DECEMBER 8, 2023

He focused on generative AI trained on large language models, The strength of the deep learning era of artificial intelligence has lead to something of a renaissance in corporate R&D in information technology, according to Yann LeCun, chief AI. Hinton is viewed as a leading figure in the deep learning community.

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Towards AI

JULY 21, 2023

But who knows… 3301’s Cicada project started with a random 4chan post in 2012 leading many thrill seekers, with a cult-like following, on a puzzle hunt that encompassed everything from steganography to cryptography. While most of their puzzles were eventually solved, the very last one, the Liber Primus, is still (mostly) encrypted.

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Pickl AI

JULY 24, 2024

The advent of big data, coupled with advancements in Machine Learning and deep learning, has transformed the landscape of AI. 2010s : Rapid Advancements and Applications 2012: The ImageNet competition demonstrates the power of deep learning, with AlexNet winning and significantly improving image classification accuracy.

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IBM Journey to AI blog

JULY 15, 2024

A brief history of scaling “Bigger is better” stems from the data scaling laws that entered the conversation with a 2012 paper by Prasanth Kolachina applying scaling laws to machine learning. displayed that deep learning scaling is predictable empirically too. In 2017, Hestness et al.

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Heartbeat

AUGUST 21, 2023

AlexNet is a more profound and complex CNN architecture developed by Alex Krizhevsky, Ilya Sutskever, and Geoffrey Hinton in 2012. AlexNet significantly improved performance over previous approaches and helped popularize deep learning and CNNs. It has eight layers, five of which are convolutional and three fully linked.

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Flipboard

AUGUST 17, 2023

The policy looks like the following code: { "Version": "2012-10-17", "Statement": [ { "Action": "redshift:getclustercredentials", "Effect": "Allow", "Resource": [ "*" ] } ] } After this setup, SageMaker Data Wrangler allows you to query Amazon Redshift and output the results into an S3 bucket.

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Heartbeat

OCTOBER 9, 2023

Artificial Intelligence (AI) Integration: AI techniques, including machine learning and deep learning, will be combined with computer vision to improve the protection and understanding of cultural assets. Barceló and Maurizio Forte edited "Virtual Reality in Archaeology" (2012). Brutto, M. L., & Meli, P.

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Mlearning.ai

JUNE 18, 2023

This puts paupers, misers and cheapskates who do not have access to a dedicated deep learning rig or a paid cloud service such as AWS at a disadvantage. In this article we show how to use Google Colab perform transfer learning on YOLO , a well known deep learning computer vision model written in C and CUDA.

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ODSC - Open Data Science

MAY 1, 2023

He shipped products across various domains: from 3D medical imaging, through global-scale web systems, and up to deep learning systems that power apps and services used by billions of people worldwide. In 2012, Daphne was recognized as one of TIME Magazine’s 100 most influential people.

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The MLOps Blog

NOVEMBER 30, 2022

These days enterprises are sitting on a pool of data and increasingly employing machine learning and deep learning algorithms to forecast sales, predict customer churn and fraud detection, etc., Most of its products use machine learning or deep learning models for some or all of their features.

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Hacker News

FEBRUARY 14, 2023

And in fact the big breakthrough in “deep learning” that occurred around 2011 was associated with the discovery that in some sense it can be easier to do (at least approximate) minimization when there are lots of weights involved than when there are fairly few.

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Heartbeat

JULY 27, 2023

jpg': {'class': 132, 'label': 'Hyundai Tucson SUV 2012'}, '00235.jpg': jpg': {'class': 7, 'label': 'Acura ZDX Hatchback 2012'}, '00237.jpg': jpg': {'class': 65, 'label': 'Chevrolet Avalanche Crew Cab 2012'}, '00238.jpg':

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DrivenData Labs

SEPTEMBER 10, 2024

2nd Place Ishanu Chattopadhyay (University of Kentucky) 2 million synthetic patient records with 9 variables, generated using AI models trained on EHR data from the Truven Marketscan national database and University of Chicago (2012-2021). He holds a BS in Mathematics and BS/MS in Electrical Engineering from the University of Maryland.

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