Unite.AI

SEPTEMBER 21, 2023

million in 2020. Some prominent AI techniques include neural networks, convolutional neural networks, transformers, and diffusion models. The crossover between artificial intelligence (AI) and blockchain is a growing trend across various industries, such as finance, healthcare, cybersecurity, and supply chain.

Convolutional Neural Networks 289

Convolutional Neural Networks Neural Network Artificial Intelligence Artificial Intelligence 289

AssemblyAI

MARCH 15, 2023

" arXiv preprint arXiv:2005.08100 (2020). [2] " Advances in neural information processing systems 30 (2017). [3] "Contextnet: Improving convolutional neural networks for automatic speech recognition with global context." " arXiv preprint arXiv:2005.03191 (2020). [5] 2] Vaswani, Ashish, et al. "Attention

Convolutional Neural Networks 364

Convolutional Neural Networks Large Language Models Neural Network OpenAI 364

AI Weekly

JANUARY 25, 2024

ndtv.com Top 10 AI Programming Languages You Need to Know in 2024 It excels in predictive models, neural networks, deep learning, image recognition, face detection, chatbots, document analysis, reinforcement, building machine learning algorithms, and algorithm research. decrypt.co decrypt.co

Robotics 222

Robotics Artificial Intelligence Artificial Intelligence Neural Network 222

Machine Learning Research at Apple

JUNE 20, 2023

Many computational approaches have been proposed to estimate such Monge maps when is the distance, e.g., using entropic maps (Pooladian and Niles-Weed, 2021), or neural networks (Makkuva et al., 2020; Korotin et al., We propose a…

Neural Network 52

Neural Network 52

Mlearning.ai

MAY 11, 2023

ChatGPT is an AI language model that has taken the world by storm since its release in 2020. What lies behind GPT is a type of artificial intelligence (AI) called a neural network. What the heck is neural network? A neural network is kind of like a big group of friends working together to solve a puzzle.

Neural Network 52

Neural Network Explainability Convolutional Neural Networks Natural Language Processing 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. The birth of Neural networks was initiated with an approach akin to structuring solving problems with algorithms modeled after the human brain.

NLP 98

NLP Neural Network Natural Language Processing Convolutional Neural Networks 98

Machine Learning Research at Apple

JUNE 19, 2023

2020); Korotin et al. 2020) consider maps , where is an input convex neural network (ICNN), as defined by Amos et al. To exploit that result, , Makkuva et al. 2017, and fit with SGD using…

Neural Network 40

Neural Network Machine Learning 40

Unite.AI

NOVEMBER 8, 2023

Recurrent Neural Networks (RNNs) became the cornerstone for these applications due to their ability to handle sequential data by maintaining a form of memory. Functionality : Each encoder layer has self-attention mechanisms and feed-forward neural networks. However, RNNs were not without limitations.

BERT 298

BERT NLP Neural Network Natural Language Processing 298

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. The standard development queries and queries from the TREC 2019 and TREC 2020 Deep Learning Tracks were used for evaluation.

AI Researcher 129

AI Researcher AI Research OpenAI Neural Network 129

Becoming Human

MARCH 17, 2023

Trends resonate with Gartner predictions : about 25% customer service operations relying on virtual assistants by the year 2020 may reach the USD 11.5 Voice assistant technology is all set to evolve into more complex neural networks that scale and combine the elements of image, language, and speech processing. That makes 47.3

Neural Network 124

Neural Network Artificial Intelligence Artificial Intelligence Automation 124

Towards AI

AUGUST 25, 2023

Deep learning (DL) is a subset of machine learning that uses neural networks which have a structure similar to the human neural system. 16, 2020. [4] Di Pietro, “ Deep Learning with Python: Neural Networks (complete tutorial),” Towards Data Science, Dec. 12, 2014. [3] 12, 2021. [6]

Software Engineer 96

Software Engineer Machine Learning Neural Network Artificial Intelligence 96

Heartbeat

AUGUST 1, 2023

I stumbled upon a simple question, what was there before neural nets could efficiently be run on the average computer? Surely research in this field yielded results that could be used without requiring neural networks. Features extracted from them could be fed into neural networks for enhanced performance.

Computer Vision 52

Computer Vision Deep Learning Neural Network Algorithm 52

AssemblyAI

MARCH 18, 2024

A Large Language Model (LLM) is a type of deep learning neural network trained on massive amounts of data and then fine-tuned for specific applications. 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

OCTOBER 11, 2023

One challenge, for instance, is to boost the performance of a Convolution Neural Networks (CNN) model by more than 10% on the cifar10 dataset. They provide simple beginning programs for some of these activities to guarantee that the agent can make valid submissions. It achieves an average improvement of 48.18

Machine Learning 104

Machine Learning AI Researcher AI Research Convolutional Neural Networks 104

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. Examples are the ACL fellow award 2020 and the first Hessian LOEWE Distinguished Chair award (2,5 mil. Iryna is co-director of the NLP program within ELLIS, a European network of excellence in machine learning.

Neural Network 117

Neural Network Natural Language Processing NLP Computational Linguistics 117

Unite.AI

OCTOBER 31, 2023

The real turning point came around 2020, with a series of innovative papers and the introduction of OpenAI’s CLIP technology, which significantly advanced diffusion models' capabilities. By breaking down image generation into discrete steps, these models have become more tractable and easier for neural networks to learn.

OpenAI 264

OpenAI ChatGPT Neural Network Prompt Engineer 264

Dlabs.ai

MARCH 17, 2021

He used to be the Director of AI and Autopilot Vision at Tesla , so it’s perhaps not surprising that Andrej was named one of MIT Technology Review’s ‘Innovators Under 35’ in 2020. He focuses his efforts on understanding and developing new ideas around machine learning, neural networks, and reinforcement learning.

Deep Learning 92

Deep Learning Artificial Intelligence Artificial Intelligence Neural Network 92

Artificial Corner

JUNE 23, 2023

Like U-Net, TransUnet includes two main sections: Encoder (Vision Transformer): Vision Transformer encodes patches of feature maps that are generated by a convolution neural network. Houlsby, An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale (2020) [3] Jieneng Chen, Yongyi Lu, Qihang Yu, Xiangde Luo, E.

Convolutional Neural Networks 97

Convolutional Neural Networks Neural Network Automation Artificial Intelligence 97

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. For example, if a neural network classifies an image as a “dog” with probability p , p cannot be interpreted as the confidence of the network’s predicted class for the image.

Neural Network 59

Neural Network Computer Vision Deep Learning Explainability 59

Dlabs.ai

JANUARY 12, 2021

With 2020 fading over the horizon, we can finally reflect on ‘what was’ versus ‘what could have been.’ Let’s look at how Javascript prospered in 2020 — and share some predictions for what 2021 might hold. January 2020 14.4k December 2020 Brain.js December 2020 11.6k December 2020 ML5.js January 2020 6.7k

Machine Learning 52

Machine Learning Neural Network Python ML 52

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.

LLM 136

LLM Generative AI AI Modeling Neural Network 136

Mlearning.ai

JUNE 20, 2023

We can now automatically rearrange those partitions and have a machine-learning model (let’s just stick to a Neural Network) learn to predict the right order of those patches. So, we simply want our Neural Network to predict very similar if not the same vector representations for both variations of the same image.

Neural Network 52

Neural Network Machine Learning Large Language Models ML 52

Analytics Vidhya

JANUARY 8, 2020

The post Here’s your Learning Path to Master Computer Vision in 2020 appeared first on Analytics Vidhya. Introduction There are an overwhelming number of resources out there these days to learn computer vision concepts. How do you pick and choose from.

Computer Vision 212

Computer Vision Neural Network Deep Learning NLP 212

Heartbeat

JANUARY 11, 2023

Using the EfficientNet Architecture to Classify Car Brands — by Harpreet Sahota How do you measure how big a convolutional neural network is? Until 2020, the process of measuring a convolutional neural network was never well understood. You can’t weigh it or use a ruler to measure it.

Convolutional Neural Networks 40

Convolutional Neural Networks Neural Network Deep Learning Computer Vision 40

Flipboard

APRIL 4, 2023

The score is used as feedback to adjust the neural network, and it tries again. But in the MacroPlacement experiments each Circuit Training result came from a neural network that had never seen a design before. Wash, rinse, repeat.

Neural Network 170

Neural Network Algorithm Machine Learning Computer Scientist 170

ODSC - Open Data Science

OCTOBER 24, 2023

Generating synthetic data NoGAN is the first algorithm in a series of high-performance, fast synthesizers not based on neural networks such as GAN. It browses the input data only once, creating the minimum number of multivariate bins or hyperrectangles efficiently covering the sparse working area in the feature space.

Categorization 98

Categorization Data Science Neural Network Algorithm 98

IBM Journey to AI blog

JUNE 23, 2023

The introduction of ChatGPT capabilities has generated a lot of interest in generative AI foundation models (these are pre-trained on unlabeled datasets and leverage self-supervised learning with the help of Large Language Models using a neural network ). The ROE ranges also varied by country, from –5% to +13% [1].

Automation 153

Automation Neural Network Large Language Models Generative AI 153

Mlearning.ai

SEPTEMBER 28, 2023

2020) introduced DiffWave as a probabilistic diffusion model that can generate conditional and unconditional waveforms. No Need for Extra Neural Networks : Diffusion models utilise a parameter-free diffusion process, eliminating the need for additional neural networks during training.

Neural Network 52

Neural Network LLM AI AI 52

AI Impacts

JULY 20, 2023

Survey on intermediate goals in AI governance (Rethink Priorities, Räuker and Aird, March) It seems that a key bottleneck for the field of longtermism-aligned AI governance is limited strategic clarity (see Muehlhauser, 2020 , 2021 ). What does it take to catch a Chinchilla?

AI Strategy 100

AI Strategy AI AI Neural Network 100

ODSC - Open Data Science

JUNE 9, 2023

The 1970s introduced bell bottoms, case grammars, semantic networks, and conceptual dependency theory. In the 90’s we got grunge, statistical models, recurrent neural networks and long short-term memory models (LSTM). It uses a neural network to learn the vector representations of words from a large corpus of text.

Natural Language Processing 52

Natural Language Processing ChatGPT Generative AI BERT 52

How to Learn Machine Learning

MAY 14, 2023

As a machine learning engineer, it’s essential to master deep learning techniques and neural networks, as they have become integral to solving complex problems in various domains. In addition to deep learning, it’s beneficial to specialize in a specific area or technique within machine learning.

Machine Learning 52

Machine Learning Natural Language Processing Convolutional Neural Networks Deep Learning 52

ML @ CMU

JUNE 30, 2023

An end-to-end learning approach predicts actions directly from raw observations with a deep neural network consisting of visual encoders for image frames followed by a recurrent layer for memory [ Ramrakhya 2022 ].

Robotics 88

Robotics Neural Network Explainability Machine Learning 88

Heartbeat

JUNE 6, 2023

Photo by GuerrillaBuzz on Unsplash Graph Convolutional Networks (GCNs) are a type of neural network that operates on graphs, which are mathematical structures consisting of nodes and edges. GCNs have been successfully applied to many domains, including computer vision and social network analysis. Richong, Z.,

NLP 59

NLP Convolutional Neural Networks Neural Network Natural Language Processing 59

Towards AI

JULY 20, 2023

This includes one paper from 2020 that conducted feature extraction using a denoising autoencoder alongside a deep neural network, and a flattened vector and support vector machines to evaluate study relevance.

Data Extraction 82

Data Extraction NLP Natural Language Processing Automation 82

Heartbeat

FEBRUARY 27, 2023

DRL agents may now be trained on high-dimensional observations like images and videos thanks to the usage of deep neural networks as function approximators. The most recent developments in GANs demonstrate how these networks have the ability to transform numerous industries and applications. Generative adversarial networks.

Machine Learning 52

Machine Learning Deep Learning Robotics Neural Network 52

Sebastian Ruder

JANUARY 19, 2021

2020 ), Turing-NLG , BST ( Roller et al., 2020 ), and GPT-3 ( Brown et al., 2020 ; Fan et al., 2020 ), quantization ( Fan et al., 2020 ), and compression ( Xu et al., 2020 ; Fan et al., 2020 ), quantization ( Fan et al., 2020 ), and compression ( Xu et al., 2020 ) and Big Bird ( Zaheer et al.,

NLP 52

NLP ML Computer Vision Natural Language Processing 52

Mlearning.ai

AUGUST 11, 2023

E.g., graph sampling in graph neural networks, feature extraction in advertisement, data augmentation in vision. When the training is scaled to be done in a distributed manner, the gang scheduling mechanism, which is required by gradient descent, forces resources to wait till all of the resources are free and ready to fire.

Deep Learning 52

Deep Learning Neural Network Explainability AI 52