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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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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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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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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AWS Machine Learning Blog

JULY 10, 2025

AI developers and machine learning (ML) engineers can now use the capabilities of Amazon SageMaker Studio directly from their local Visual Studio Code (VS Code). The solution architecture consists of three main components: Local computer : Your development machine running VS Code with AWS Toolkit extension installed.

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ODSC - Open Data Science

JUNE 8, 2023

If you’re looking to learn more about Microsoft Azure and Microsoft’s overall AI and machine learning initiatives, be sure to check out our Microsoft AI Learning Journey page ! Cloudera For Cloudera, it’s all about machine learning optimization.

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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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ODSC - Open Data Science

FEBRUARY 28, 2023

Cloudera For Cloudera, it’s all about machine learning optimization. Their CDP machine learning allows teams to collaborate across the full data life cycle with scalable computing resources, tools, and more.

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Mlearning.ai

APRIL 8, 2023

SOTA (state-of-the-art) in machine learning refers to the best performance achieved by a model or system on a given benchmark dataset or task at a specific point in time. The earlier models that were SOTA for NLP mainly fell under the traditional machine learning algorithms. Citation: Article from IBM archives 2.

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AWS Machine Learning Blog

JUNE 6, 2023

PyTorch is a machine learning (ML) framework that is widely used by AWS customers for a variety of applications, such as computer vision, natural language processing, content creation, and more. These are basically big models based on deep learning techniques that are trained with hundreds of billions of parameters.

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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. The challenge with big data lies in its volume, velocity, and variety.

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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

Early iterations of the AI applications we interact with most today were built on traditional machine learning models. These models rely on learning algorithms that are developed and maintained by data scientists. Due to deep learning and other advancements, the field of AI remains in a constant and fast-paced state of flux.

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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

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., an image) with the intention of causing a machine learning model to misclassify it (Goodfellow et al.,

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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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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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Flipboard

AUGUST 17, 2023

Many practitioners are extending these Redshift datasets at scale for machine learning (ML) using Amazon SageMaker , a fully managed ML service, with requirements to develop features offline in a code way or low-code/no-code way, store featured data from Amazon Redshift, and make this happen at scale in a production environment.

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ODSC - Open Data Science

MAY 1, 2023

Pedro Domingos, PhD Professor Emeritus, University Of Washington | Co-founder of the International Machine Learning Society Pedro Domingos is a winner of the SIGKDD Innovation Award and the IJCAI John McCarthy Award, two of the highest honors in data science and AI.

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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). 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. Work by Hinton et al.

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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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Pickl AI

JULY 24, 2024

Key milestones include the Turing Test, the Dartmouth Conference, and breakthroughs in machine learning. Researchers began to focus on Machine Learning, a subfield of AI that emphasises the importance of data-driven approaches. This shift allowed systems to learn from experience and improve their performance over time.

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Heartbeat

DECEMBER 8, 2023

This includes cleaning and transforming data, performing calculations, or applying machine learning algorithms. 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. Meta's chief A.I.

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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. International Journal of Machine Learning and Computing , 1 (5), 460. Ekanayake, B., F., & Smith, P.

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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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Hacker News

FEBRUARY 14, 2023

And—as we’ll discuss later—these weights are normally determined by “training” the neural net using machine learning from examples of the outputs we want.) In each case, as we’ll explain later, we’re using machine learning to find the best choice of weights.

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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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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

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

In the main track of Phase 1, solvers submitted a written description of a shareable dataset that could support novel machine learning approaches for early prediction of AD/ADRD, with an emphasis on addressing biases in existing data sources. Paola Ruíz Puente is a Biomedical Engineer amd the AI/ML manager at IGC Pharma.

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DrivenData Labs

MAY 1, 2025

changes between 2003 and 2012). Currently I work for Amazon as an Applied Scientist where we develop Machine Learning technology to protect Amazon and customers from fraudulent activity. Her work involves developing innovative machine learning tools to advance the diagnosis of Alzheimers and related disorders.

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Flipboard

JULY 31, 2023

In this post, we’ll show you the datasets you can use to build your machine learning projects. After you create a free account, you’ll have access to the best machine learning datasets. Importance and Role of Datasets in Machine Learning Data is king.

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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

Back in 2016 I was trying to explain to software engineers how to think about machine learning models from a software design perspective; I told them that they should think of a database. Neural networks are a type of machine learning algorithm that are used for tasks such as pattern recognition, classification, and prediction.

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AWS Machine Learning Blog

APRIL 15, 2025

The AWS Inferentia and AWS Trainium are AWS AI chips, purpose-built to deliver high throughput and low latency inference and training performance for even the largest deep learning models. Youll use a Deep Learning Container. The Mixtral 8x7B model adopts the Mixture-of-Experts (MoE) architecture with eight experts.

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