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.

Artificial Intelligence 209

Artificial Intelligence Artificial Intelligence Emotion AI Computer Vision 209

Unite.AI

MAY 29, 2024

With nine times the speed of the Nvidia A100, these GPUs excel in handling deep learning workloads. Recent advancements in hardware such as Nvidia H100 GPU, have significantly enhanced computational capabilities. Subsequently, some RNNs were also trained using GPUs, though they did not yield good results.

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NVIDIA

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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NVIDIA

NOVEMBER 18, 2024

Milestones like Tokyo Tech’s Tsubame supercomputer in 2008, the Oak Ridge National Laboratory’s Titan supercomputer in 2012 and the AI-focused NVIDIA DGX-1 delivered to OpenAI in 2016 highlight NVIDIA’s transformative role in the field. Since CUDA’s inception, we’ve driven down the cost of computing by a millionfold,” Huang said.

Neural Network 145

Neural Network AI AI Explainability 145

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':

Deep Learning 52

Deep Learning Metadata Python Explainability 52

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.

Automation 124

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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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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.,

Machine Learning 123

Machine Learning Computer Vision Deep Learning Convolutional Neural Networks 123

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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Large Language Models Generative AI Deep Learning AI Chatbots 131

Unite.AI

MAY 28, 2024

OpenAI researchers note that : since 2012, the computing power required to train advanced AI models has doubled every 3.4 For instance, training deep learning models requires significant computational power and high throughput to handle large datasets and execute complex calculations quickly.

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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.

AI Modeling 98

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NVIDIA

OCTOBER 23, 2024

Then, in 2012, Alex Krizhevsky, mentored by Ilya Sutskever and Geoffrey Hinton, won the ImageNet computer image recognition competition with AlexNet, a revolutionary deep learning model for image classification. The breakthrough of machine learning — neural networks running on GPUs — jump-started the era of Software 2.0.

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Robotics Generative AI AI AI 134

Viso.ai

DECEMBER 19, 2023

Image Classification Using Machine Learning CNN Image Classification (Deep Learning) Example applications of Image Classification Let’s dive deep into it! It uses AI-based deep learning models to analyze images with results that for specific tasks already surpass human-level accuracy (for example, in face recognition ).

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Convolutional Neural Networks Neural Network Computer Vision Deep Learning 98

Marktechpost

SEPTEMBER 24, 2024

CNN’s performance improved in the ILSVRC-2012 competition, achieving a top-5 error rate of 15.3%, compared to 26.2% The success of this model reflects a broader shift in computer vision towards machine learning approaches that leverage large datasets and computational power. by the next-best model. and 28.2%).

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Convolutional Neural Networks Neural Network Computer Vision Deep Learning 64

Unite.AI

MAY 10, 2024

Realizing that many of the tedious development processes in Mellanox could be automated by machine-learning algorithms, I changed my majors to optimization and machine learning and completed an MSc in the space. At Visualead, we’d been running algorithms on mobile devices since 2012, including models.

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Large Language Models Automation Software Development Neural Network 147

Viso.ai

FEBRUARY 11, 2024

Image classification employs AI-based deep learning models to analyze images and perform object recognition, as well as a human operator. It is one of the largest resources available for training deep learning models in object recognition tasks. After fine-tuning on ImageNet-2012 it gave an error rate of 16.6%.

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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

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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ML Deep Learning BERT Python 91

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.

Data Science 96

Data Science Auto-complete Machine Learning AI 96

Marktechpost

OCTOBER 16, 2024

Deep learning-based prediction is critical for optimizing output, anticipating weather fluctuations, and improving solar system efficiency, allowing for more intelligent energy network management. More sophisticated machine learning approaches, such as artificial neural networks (ANNs), may detect complex relationships in data.

Machine Learning 69

Machine Learning Neural Network Deep Learning Inference Engine 69

Viso.ai

MARCH 12, 2024

Today’s boom in computer vision (CV) started at the beginning of the 21 st century with the breakthrough of deep learning models and convolutional neural networks (CNN). We split them into two categories – classical CV approaches, and papers based on deep-learning. Find the SURF paper here. Find the ImageNet paper here.

Computer Vision 52

Computer Vision Convolutional Neural Networks Neural Network Deep Learning 52

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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ML Machine Learning Software Development Artificial Intelligence 93

Viso.ai

MAY 7, 2024

GoogLeNet’s deep learning model was deeper than all the previous models released, with 22 layers in total. Increasing the depth of the Machine Learning model is intuitive, as deeper models tend to have more learning capacity and as a result, this increases the performance of a model.

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NVIDIA

JUNE 5, 2023

That’s an order of magnitude more than it generated in 2012 when two of its experiments uncovered the Higgs boson, a subatomic particle that validated scientists’ understanding of the universe. A high-luminosity version of the giant accelerator ( HL-LHC ) will produce 10x more proton collisions, spawning exabytes of data a year.

AI 106

AI AI Machine Learning Explainability 106

Viso.ai

MAY 31, 2024

Our software helps several leading organizations start with computer vision and implement deep learning models efficiently with minimal overhead for various downstream tasks. This challenge was conducted till 2012, each subsequent year. Pascal VOC Dataset Development The Pascal VOC dataset was developed from 2005 to 2012.

Computer Vision 52

Computer Vision Convolutional Neural Networks Deep Learning Neural Network 52

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.

Deep Learning 52

Deep Learning Computer Vision Machine Learning Algorithm 52

Marktechpost

JULY 17, 2023

What Relationship Exists Between Predictive Analytics, Deep Learning, and Artificial Intelligence? For machine learning to identify common patterns, large datasets must be processed. Deep learning is a branch of machine learning frequently used with text, audio, visual, or photographic data.

Data Mining 98

Data Mining Machine Learning Data Scientist Artificial Intelligence 98

Viso.ai

FEBRUARY 19, 2024

applied deep learning R-CNN for document classification and clustering. 2020) applied an image copy detection scheme based on the deep learning Inception CNN model. The image’s feature values were automatically extracted for learning and detecting unauthorized digital images. How is this done? Huber-Fliflet, et al.

Computer Vision 52

Computer Vision Deep Learning Convolutional Neural Networks Neural Network 52

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)

Neural Network 52

Neural Network BERT Large Language Models Natural Language Processing 52

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.

NLP 98

NLP Inference Engine Natural Language Processing Chatbots 98

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.

Machine Learning 52

Machine Learning Data Science Metadata Python 52

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.

ML 113

ML Deep Learning Algorithm Large Language Models 113

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.

ML 123

ML Auto-complete Auto-classification Machine Learning 123

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.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Natural Language Processing Neural Network 52

Lexalytics

APRIL 5, 2021

They were not wrong: the results they found about the limitations of perceptrons still apply even to the more sophisticated deep-learning networks of today. And indeed we can see other machine learning topics arising to take their place, like “optimization” in the mid-’00s, with “deep learning” springing out of nowhere in 2012.

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing BERT 52

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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Convolutional Neural Networks Neural Network Deep Learning LLM 52

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.

Computer Vision 52

Computer Vision Algorithm Deep Learning Machine Learning 52