Lexalytics

APRIL 5, 2021

I was out of the neural net biz. Fast-forward a couple of decades: I was (and still am) working at Lexalytics, a text-analytics company that has a comprehensive NLP stack developed over many years. The CNN was a 6-layer neural net with 132 convolution kernels and (don’t laugh!) Hinton (again!) and BERT.

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing BERT 52

Mlearning.ai

JUNE 8, 2023

Images can be embedded using models such as convolutional neural networks (CNNs) , Examples of CNNs include VGG , and Inception. SentenceBERT: Currently, the leader among the pack, SentenceBERT was introduced in 2018 and immediately took the pole position for Sentence Embeddings. using its Spectrogram ).

Machine Learning 52

Machine Learning BERT Neural Network OpenAI 52

ML Review

JUNE 4, 2018

Recent Intersections Between Computer Vision and Natural Language Processing (Part Two) This is the second instalment of our latest publication series looking at some of the intersections between Computer Vision (CV) and Natural Language Processing (NLP). 2018)[ 103 ] proposed a more natural method for attention, inspired by neuroscience.

Neural Network 52

Neural Network Convolutional Neural Networks Computer Vision Deep Learning 52

Explosion

NOVEMBER 21, 2019

from_disk("/path/to/s2v_reddit_2015_md") nlp.add_pipe(s2v) doc = nlp("A sentence about natural language processing.") import spacy from spacy.pipeline import EntityRuler nlp = spacy.blank("en") ruler = EntityRuler(nlp).from_disk("./fashion_brands_patterns.jsonl") from sense2vec import Sense2Vec s2v = Sense2Vec().from_disk("/path/to/s2v_reddit_2015_md")

NLP 52

NLP Convolutional Neural Networks Neural Network Natural Language Processing 52

ML Review

MAY 3, 2018

Recent Intersections Between Computer Vision and Natural Language Processing (Part One) This is the first instalment of our latest publication series looking at some of the intersections between Computer Vision (CV) and Natural Language Processing (NLP). Thanks for reading!

Neural Network 52

Neural Network Computer Vision Deep Learning Convolutional Neural Networks 52

Unite.AI

AUGUST 8, 2023

Instead of complex and sequential architectures like Recurrent Neural Networks (RNNs) or Convolutional Neural Networks (CNNs), the Transformer model introduced the concept of attention, which essentially meant focusing on different parts of the input text depending on the context. How Are LLMs Used?

Generative AI 243

Generative AI ChatGPT Neural Network Convolutional Neural Networks 243

NLP People

JULY 24, 2019

We took the opportunity to review major research trends in the animated NLP space and formulate some implications from the business perspective. The article is backed by a statistical and – guess what – NLP-based analysis of ACL papers from the last 20 years. Neural Networks are the workhorse of Deep Learning (cf.

NLP 52

NLP Neural Network Deep Learning Natural Language Processing 52

Viso.ai

DECEMBER 21, 2023

From the development of sophisticated object detection algorithms to the rise of convolutional neural networks (CNNs) for image classification to innovations in facial recognition technology, applications of computer vision are transforming entire industries. Thus, positioning him as one of the top AI influencers in the world.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 52

John Snow Labs

MAY 8, 2024

Technical Foundations of LLMs in Pathology LLMs, such as BERT and GPT-3, are the result of significant advancements in natural language processing (NLP) and deep learning.

Large Language Models 40

Large Language Models Automation NLP Machine Learning 40