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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Pickl AI

JULY 24, 2024

Summary: The history of Artificial Intelligence spans from ancient philosophical ideas to modern technological advancements. Key milestones include the Turing Test, the Dartmouth Conference, and breakthroughs in machine learning. In the following years, researchers made significant progress.

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AWS Machine Learning Blog

MARCH 27, 2025

Dhawal Patel is a Principal Machine Learning Architect at AWS. He has worked with organizations ranging from large enterprises to mid-sized startups on problems related to distributed computing and artificial intelligence. He focuses on deep learning, including NLP and computer vision domains.

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Towards AI

MARCH 11, 2025

Yet, despite Monicas innovation using existing models, even more could be unlocked with improvements to base model intelligence. 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. But scaling what?.

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Towards AI

FEBRUARY 10, 2023

The term “artificial intelligence” may evoke the ideas of algorithms and data, but it is powered by the rare earth’s minerals and resources that make up the computing components [1]. The cloud, which consists of vast machines, is arguably the backbone of the AI industry. By comparison, Moore’s Law had a 2-year doubling period.

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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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Mlearning.ai

APRIL 8, 2023

What is Natural Language Processing (NLP) Natural Language Processing (NLP) is a subfield of artificial intelligence (AI) that deals with interactions between computers and human languages. It measures the current cutting-edge performance of a model or system in a particular field or job. Before we go any further, let’s introduce NLP.

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AWS Machine Learning Blog

APRIL 16, 2024

Amazon Lex is a fully managed artificial intelligence (AI) service with advanced natural language models to design, build, test, and deploy conversational interfaces in applications.

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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

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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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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AWS Machine Learning Blog

SEPTEMBER 11, 2024

These activities cover disparate fields such as basic data processing, analytics, and machine learning (ML). And finally, some activities, such as those involved with the latest advances in artificial intelligence (AI), are simply not practically possible, without hardware acceleration. Work by Hinton et al.

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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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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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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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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

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.

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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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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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DrivenData Labs

MAY 1, 2025

changes between 2003 and 2012). His contributions include developing and refining machine learning and deep learning models using these datasets and optimizing state-of-the-art large language models. Feature Engineering: We engineered features to capture socio-demographic, temporal, and group-level effects (e.g.,

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Hacker News

JULY 4, 2025

This causes games like Mirror’s Edge (2009) and Borderlands 2 (2012) that still run on today’s computers to take ungodly dips into single digit frame rates, because the physics calculations are forcibly performed on the CPU instead of the GPU [5]. That upscaling tech is the now ubiquitous DLSS, or Deep Learning Super Sampling [7].

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Flipboard

JULY 31, 2023

Brief Background of Machine Learning Did you know that machine learning is a part of artificial intelligence that enables computers to learn from data without explicit programming using statistical techniques? OK, let’s dive into where the various datasets are located to give you a full picture of the dataverse.

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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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Mlearning.ai

FEBRUARY 10, 2023

Evidence that Neural Nets know much more than we think During the early years of the current ML spring (2012–2016), models that performed object identification (such as classifying the type of fish from images for example) were very popular. But the task of retrieving information is still predominantly done with databases.

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