AWS Machine Learning Blog

OCTOBER 15, 2024

In addition to traditional custom-tailored deep learning models, SageMaker Ground Truth also supports generative AI use cases, enabling the generation of high-quality training data for artificial intelligence and machine learning (AI/ML) models.

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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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Flipboard

JULY 31, 2023

Object detection works by using machine learning or deep learning models that learn from many examples of images with objects and their labels. In the early days of machine learning, this was often done manually, with researchers defining features (e.g., Object detection is useful for many applications (e.g.,

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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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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

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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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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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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AWS Machine Learning Blog

NOVEMBER 15, 2024

of persons present’ for the sustainability committee meeting held on 5th April, 2012? He focuses on developing scalable machine learning algorithms. His research interests are in the area of natural language processing, explainable deep learning on tabular data, and robust analysis of non-parametric space-time clustering.

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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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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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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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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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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

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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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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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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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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Explosion

SEPTEMBER 3, 2015

The new, awesome deep-learning model is there, but so are lots of others. Another researcher’s offer from 2012 to implement this type of model also went unanswered. This post explains the problem, why it’s so damaging, and why I wrote spaCy to do things differently. The story in nltk.tag is similar.

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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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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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Smart Data Collective

MARCH 16, 2020

Deep learning is likely to play an essential role in keeping costs in check. Deep Learning is Necessary to Create a Sustainable Medicare for All System. He should elaborate more on the benefits of big data and deep learning. A lot of big data experts argue that deep learning is key to controlling costs.

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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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AWS Machine Learning Blog

MARCH 27, 2025

He focuses on deep learning, including NLP and computer vision domains. The following code is an example of how to modify an existing SCP that denies access to all services in specific Regions while allowing Amazon Bedrock inference through cross-Region inference for Anthropics Claude 3.5 Lets name this IAM role Bedrock-Access-CRI.

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AWS Machine Learning Blog

OCTOBER 11, 2024

For example: Data such as images, text, and audio need to be represented in a structured and efficient manner Understanding the semantic similarity between data points is essential in generative AI tasks like natural language processing (NLP), image recognition, and recommendation systems As the volume of data continues to grow rapidly, scalability (..)

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AWS Machine Learning Blog

OCTOBER 24, 2024

Large language models (LLMs) are very large deep-learning models that are pre-trained on vast amounts of data. LLMs are incredibly flexible. One model can perform completely different tasks such as answering questions, summarizing documents, translating languages, and completing sentences.

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