Pickl AI

NOVEMBER 26, 2024

Summary: Recurrent Neural Networks (RNNs) are specialised neural networks designed for processing sequential data by maintaining memory of previous inputs. Introduction Neural networks have revolutionised data processing by mimicking the human brain’s ability to recognise patterns.

Neural Network 52

Neural Network Natural Language Processing NLP Deep Learning 52

Viso.ai

MAY 17, 2024

Neural Networks have changed the way we perform model training. This gave birth to a new domain called Deep Learning. Neural networks, sometimes referred to as Neural Nets, need large datasets for efficient training. Liquid Neural Networks solve the problems posed by traditional networks.

Neural Network 52

Neural Network Deep Learning Computer Vision Artificial Intelligence 52

Heartbeat

JUNE 14, 2023

Introduction Deep neural network classifiers have been shown to be mis-calibrated [1], i.e., their prediction probabilities are not reliable confidence estimates. Further, neural network classifiers are often overconfident in their predictions [1]. 4] as a regularization technique for deep neural networks.

Neural Network 59

Neural Network Computer Vision Deep Learning Explainability 59

PyImageSearch

OCTOBER 28, 2024

Block #A: We Begin with a 5D Input Block #B: The Neural Network and Its Output Block #C: Volumetric Rendering The NeRF Problem and Evolutions Summary and Next Steps Next Steps Citation Information NeRFs Explained: Goodbye Photogrammetry? In this blog post, you will learn about 3D Reconstruction. How Do NeRFs Work?

Explainability 94

Explainability Neural Network Computer Vision Deep Learning 94

AssemblyAI

MARCH 7, 2023

This question is posed simply as a thought exercise - different regimes with distinct equations that govern behavior seem much less plausible in a neural network than a physical system. Jones' analysis was heavily informed by a paper [ 3 ] from OpenAI, released in 2020, on scaling laws for neural language models.

Large Language Models 363

Large Language Models OpenAI Neural Network AI 363

Viso.ai

OCTOBER 9, 2024

Hence, deep neural network face recognition and visual Emotion AI analyze facial appearances in images and videos using computer vision technology to analyze an individual’s emotional status. Unsurprisingly, modern deep learning methods outperform traditional computer vision methods.

Convolutional Neural Networks 98

Convolutional Neural Networks Neural Network Computer Vision Emotion AI 98

Marktechpost

SEPTEMBER 4, 2023

Lately, there have been significant strides in applying deep neural networks to the search field in machine learning, with a specific emphasis on representation learning within the bi-encoder architecture. million passages extracted from the web. The growing popularity of embedding APIs supports our arguments.

AI Research 132

AI Research AI Researcher OpenAI Neural Network 132

NVIDIA

DECEMBER 4, 2023

“GPUs are the dominant computing platform for accelerating machine learning workloads, and most (if not all) of the biggest models over the last five years have been trained on GPUs … [they have] thereby centrally contributed to the recent progress in AI,” Epoch said on its site. A 2020 study assessing AI technology for the U.S.

Neural Network 145

Neural Network AI AI LLM 145

Dlabs.ai

JUNE 19, 2020

If you Google ‘ what’s needed for deep learning ,’ you’ll find plenty of advice that says vast swathes of labeled data (say, millions of images with annotated sections) are an absolute must. You may well come away thinking, deep learning is for ‘superhumans only’ — superhumans with supercomputers. Sounds interesting?

Deep Learning 52

Deep Learning Neural Network Machine Learning Computer Vision 52

Heartbeat

AUGUST 1, 2023

A World of Computer Vision Outside of Deep Learning Photo by Museums Victoria on Unsplash IBM defines computer vision as “a field of artificial intelligence (AI) that enables computers and systems to derive meaningful information from digital images, videos and other visual inputs [1].”

Computer Vision 52

Computer Vision Deep Learning Neural Network Algorithm 52

Viso.ai

DECEMBER 3, 2023

The recent deep learning algorithms provide robust person detection results. However, deep learning models such as YOLO that are trained for person detection on a frontal view data set still provide good results when applied for overhead view person counting ( TPR of 95%, FPR up to 0.2% ).

Convolutional Neural Networks 98

Convolutional Neural Networks Computer Vision Neural Network Deep Learning 98

AssemblyAI

NOVEMBER 8, 2023

  Each stage leverages a deep neural network that operates as a sequence labeling problem but at different granularities: the first network operates at the token level and the second at the character level. Training Data : We trained this neural network on a total of 3.7 billion words). billion words.

Neural Network 147

Neural Network BERT Large Language Models Deep Learning 147

Towards AI

SEPTEMBER 6, 2023

Open-source methods vary in complexity from traditional feature-matching algorithms like SIFT and SURF to deep learning models like DeepStitch. Deep Learning Models: Solutions like DeepStitch go beyond by using neural networks to find optimal stitching points, providing higher accuracy, especially in complex scenes.

Deep Learning 122

Deep Learning Computer Vision Algorithm AI 122

Mlearning.ai

OCTOBER 14, 2023

Introduction Deep learning tasks usually demand high computation/memory requirements and their computations are embarrassingly parallel. The paper claims that distributed training has been facilitated by deep learning frameworks, but fault tolerance did not get enough attention.

Neural Network 52

Neural Network Deep Learning LLM AI 52

Mlearning.ai

APRIL 8, 2023

Over the years, we evolved that to solving NLP use cases by adopting Neural Network-based algorithms loosely based on the structure and function of a human brain. 2003) “ Support-vector networks ” by Cortes and Vapnik (1995) Significant people : David Blei Corinna Cortes Vladimir Vapnik 4.

NLP 98

NLP Neural Network Natural Language Processing Convolutional Neural Networks 98

PyImageSearch

JANUARY 2, 2023

Figure 1: Global Funding in Health Tech Companies (source: Mrazek and O’Neill, 2020 ). This blog will cover the benefits, applications, challenges, and tradeoffs of using deep learning in healthcare. This series is about CV and DL for Industrial and Big Business Applications.

Computer Vision 52

Computer Vision Deep Learning Neural Network Machine Learning 52

Analytics Vidhya

DECEMBER 10, 2021

Introduction Analytics Vidhya has been at the helm when it comes to publishing high-quality content since the beginning of its inception. From the latest developments to guiding people through the thorns of career, Analytics Vidhya has it all in its blog archives. And this would not have been possible without leveraging the power of the […].

Data Science 349

Data Science Neural Network Deep Learning Python 349

Mlearning.ai

AUGUST 11, 2023

Introduction GPUs as main accelerators for deep learning training tasks suffer from under-utilization. Authors of AntMan [1] propose a deep learning infrastructure, which is a co-design of cluster schedulers (e.g., with deep learning frameworks (e.g., with deep learning frameworks (e.g.,

Deep Learning 52

Deep Learning Neural Network Explainability AI 52

Marktechpost

JULY 24, 2023

Many studies have been motivated to explore hidden hierarchical patterns in the large volume of weather datasets for weather forecasting due to the recent development of deep learning techniques, the widespread availability of massive weather observation data, and the advent of information and computer technology.

Deep Learning 52

Deep Learning Convolutional Neural Networks Neural Network ML 52

NVIDIA

OCTOBER 4, 2023

Harnessing the raw power of NVIDIA GPUs and aided by a network of thousands of cameras dotting the Californian landscape, DigitalPath has refined a convolutional neural network to spot signs of fire in real time. a short drive from the town of Paradise, where the state’s deadliest wildfire killed 85 people in 2018.

Convolutional Neural Networks 119

Convolutional Neural Networks Neural Network AI AI 119

Towards AI

AUGUST 25, 2023

Machine learning (ML) is a subset of AI that provides computer systems the ability to automatically learn and improve from experience without being explicitly programmed. Deep learning (DL) is a subset of machine learning that uses neural networks which have a structure similar to the human neural system.

Software Engineer 98

Software Engineer Machine Learning Neural Network Artificial Intelligence 98

AssemblyAI

MARCH 18, 2024

Data augmentation: A technique using generative models that can create diverse and realistic variations of training data to help improve the robustness and generalization of machine learning models. Facilitate quality patient care Despite declining rates since their peak in 2020, telehealth visits remain higher than pre-pandemic levels.

Generative AI 147

Generative AI Large Language Models AI AI 147

Marktechpost

MAY 31, 2024

Current methods for sleep data analysis primarily rely on supervised deep-learning models. This model leverages a vast dataset of multi-modal sleep recordings from over 14,000 participants, totaling more than 100,000 hours of sleep data collected between 1999 and 2020 at the Stanford Sleep Clinic.

Convolutional Neural Networks 107

Convolutional Neural Networks Neural Network Automation Categorization 107

PyImageSearch

OCTOBER 14, 2024

The second blog post will introduce you to NeRFs , the neural network solution. It’s actually pretty good, especially because we benefit from defined structures, we use geometry, and thus, we can do a lot of reconstruction… But since 2020, a NeRFs “fever” has taken place online. So, let’s begin with Photogrammetry!

Explainability 113

Explainability Computer Vision Deep Learning Algorithm 113

PyImageSearch

DECEMBER 9, 2024

And in the 2nd blog of this series , you were introduced to NeRFs, which is 3D Reconstruction via Neural Networks, projecting points in the 3D space. Do you think learning computer vision and deep learning has to be time-consuming, overwhelming, and complicated? So, whats the big idea behind Gaussian Splatting?

Computer Vision 95

Computer Vision Deep Learning Explainability Algorithm 95

NYU Center for Data Science

SEPTEMBER 11, 2024

What sets Dr. Ho apart is her pioneering work in applying deep learning techniques to astrophysics. Ho’s innovative approach has led to several groundbreaking achievements: Her team at Carnegie Mellon University was the first to apply 3D convolutional neural networks in astrophysics.

Convolutional Neural Networks 57

Convolutional Neural Networks Neural Network Deep Learning Data Science 57

ODSC - Open Data Science

APRIL 3, 2023

Moreover, combining expert agents is an immensely easier task to learn by neural networks than end-to-end QA. Her main research interests are in machine learning for large-scale language understanding and text semantics. Examples are the ACL fellow award 2020 and the first Hessian LOEWE Distinguished Chair award (2,5 mil.

Neural Network 117

Neural Network Natural Language Processing NLP Computational Linguistics 117

AWS Machine Learning Blog

FEBRUARY 23, 2023

Over the last 10 years, a number of players have developed autonomous vehicle (AV) systems using deep neural networks (DNNs). DNN training methods and design AV systems are built with deep neural networks. His core interests include deep learning and serverless technologies.

Automation 128

Automation Neural Network Machine Learning Data Scientist 128

NVIDIA

NOVEMBER 15, 2023

The Story of the Name Patrick Lewis, lead author of the 2020 paper that coined the term , apologized for the unflattering acronym that now describes a growing family of methods across hundreds of papers and dozens of commercial services he believes represent the future of generative AI. In other words, it fills a gap in how LLMs work.

Generative AI 145

Generative AI LLM Neural Network AI Modeling 145

Mlearning.ai

JANUARY 17, 2024

Major milestones in the last few years comprised BERT (Google, 2018), GPT-3 (OpenAI, 2020), Dall-E (OpenAI, 2021), Stable Diffusion (Stability AI, LMU Munich, 2022), ChatGPT (OpenAI, 2022). Complex ML problems can only be solved in neural networks with many layers. Deep learning neural network.

Generative AI 98

Generative AI Prompt Engineer Prompt Engineering Large Language Models 98

Towards AI

JULY 20, 2023

New research has also begun looking at deep learning algorithms for automatic systematic reviews, According to van Dinter et al.

Data Extraction 98

Data Extraction NLP Natural Language Processing Automation 98

AWS Machine Learning Blog

APRIL 6, 2023

The point cloud-based neural network model is further trained using this data to learn the parameters of the product lifecycle curve (see the following figure). Next, we calculated the WAPE value using the following formula: We repeated the same procedure to calculate the WAPE value for 2020 and 2021.

Machine Learning 113

Machine Learning ML Categorization Data Scientist 113

AWS Machine Learning Blog

OCTOBER 30, 2024

Sentence transformers are powerful deep learning models that convert sentences into high-quality, fixed-length embeddings, capturing their semantic meaning. For this demonstration, we use a public Amazon product dataset called Amazon Product Dataset 2020 from a kaggle competition.

BERT 107

BERT Categorization Data Scientist Machine Learning 107

AWS Machine Learning Blog

NOVEMBER 22, 2023

Similar to the rest of the industry, the advancements of accelerated hardware have allowed Amazon teams to pursue model architectures using neural networks and deep learning (DL). He focuses on building systems and tooling for scalable distributed deep learning training and real time inference.

LLM 123

LLM Software Engineer Auto-complete Neural Network 123

Viso.ai

DECEMBER 6, 2024

Object Detection with Deep Learning for traffic analytics with a video stream Vehicles can recognize the appearance of the cyclist, pedestrian, or car in front of them thanks to class-specific object detection. 2020) developed a lightweight vehicle detector with a 1/10 model size that is three times faster than YOLOv3.

Computer Vision 52

Computer Vision Convolutional Neural Networks Neural Network Deep Learning 52

Flipboard

AUGUST 25, 2023

In February 2020 — more than five decades after the science fiction film introduced the world to perhaps the first great AI villain — a team of researchers at the Massachusetts Institute of Technology used artificial intelligence to discover an antibiotic capable of killing E.

Machine Learning 123

Machine Learning AI AI Deep Learning 123

AI Impacts

FEBRUARY 1, 2023

The Alignment Problem: Machine Learning and Human Values. Norton & Company; 2020. The alignment problem from a deep learning perspective. link] Published December 15, 2020. New York, NY: W.W. 6 Amodei D, Olah C, Steinhardt J et al. Concrete Problems in AI Safety. Preprint posted online June 21, 2016.

AI 130

AI AI OpenAI Large Language Models 130