Dataconomy

MARCH 17, 2025

Timeline of key milestones Launch of Siri with the iPhone 4S in 2011 Expansion to iPads and Macs in 2013 Introduction of Siri to Apple TV and the HomePod in 2018 The anticipated Apple Intelligence update in 2024, enhancing existing features How does Siri work?

Natural Language Processing 91

Natural Language Processing Artificial Intelligence Artificial Intelligence Cloud Computing 91

Mlearning.ai

APRIL 1, 2023

NLP A Comprehensive Guide to Word2Vec, Doc2Vec, and Top2Vec for Natural Language Processing In recent years, the field of natural language processing (NLP) has seen tremendous growth, and one of the most significant developments has been the advent of word embedding techniques.

Deep Learning 52

Deep Learning Deep Learning Natural Language Processing Clustering 52

Dataconomy

FEBRUARY 6, 2024

These companies are using AI and ML to improve existing processes, reduce risks, and predict business performance and industry trends. When it comes to the role of AI in information technology, machine learning, with its deep learning capabilities, is the best use case.

ML 121

ML ML Machine Learning Machine Learning 121

Dataconomy

MAY 2, 2023

He is credited with developing some of the key algorithms and concepts that underpin deep learning, such as capsule networks. Hinton joined Google in 2013 as part of its acquisition of DNNresearch, a startup he co-founded with two of his former students, Ilya Sutskever and Alex Krizhevsky.

AI 108

AI AI Artificial Intelligence Artificial Intelligence 108

Mlearning.ai

MARCH 9, 2023

Recent studies have demonstrated that deep learning-based image segmentation algorithms are vulnerable to adversarial attacks, where carefully crafted perturbations to the input image can cause significant misclassifications (Xie et al., 2013; Goodfellow et al., Towards deep learning models resistant to adversarial attacks.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

AWS Machine Learning Blog

NOVEMBER 22, 2023

AIM333 (LVL 300) | Explore text-generation FMs for top use cases with Amazon Bedrock Tuesday November 28| 2:00 PM – 3:00 PM (PST) Foundation models can be used for natural language processing tasks such as summarization, text generation, classification, open-ended Q&A, and information extraction. Reserve your seat now!

AWS 128

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ML Review

FEBRUARY 26, 2018

Tasks such as “I’d like to book a one-way flight from New York to Paris for tomorrow” can be solved by the intention commitment + slot filing matching or deep reinforcement learning (DRL) model. Chitchatting, such as “I’m in a bad mood”, pulls up a method that marries the retrieval model with deep learning (DL).

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52