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Siri

Dataconomy

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?

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Microsoft Word gets ChatGPT integration with new ‘Ghostwriter’ third-party add-in

Flipboard

He previously founded and ran business-intelligence consulting company Extended Results, which was acquired by Tibco Software in 2013. He makes software through his Creative Data Studios one-person development shop. Microsoft CEO Satya Nadella said recently that every Microsoft product will eventually have AI capabilities.

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The Illustrated Word2Vec (2019)

Hacker News

If you’ve ever used Siri, Google Assistant, Alexa, Google Translate, or even smartphone keyboard with next-word prediction, then chances are you’ve benefitted from this idea that has become central to Natural Language Processing models. Word2vec is a method to efficiently create word embeddings and has been around since 2013.

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Why BERT is Not GPT

Towards AI

Photo by david clarke on Unsplash The most recent breakthroughs in language models have been the use of neural network architectures to represent text. There is very little contention that large language models have evolved very rapidly since 2018. RNNs and LSTMs came later in 2014. The story starts with word embedding.

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Embedding techniques: A way to empower language models

Data Science Dojo

In the ever-evolving landscape of natural language processing (NLP), embedding techniques have played a pivotal role in enhancing the capabilities of language models. Each word was treated as an isolated unit, without understanding its relationship with other words or its usage in different contexts.

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Truveta LLM: FirstLarge Language Model for Electronic Health Records

Towards AI

All of these companies were founded between 2013–2016 in various parts of the world. Soon to be followed by large general language models like BERT (Bidirectional Encoder Representations from Transformers).

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How Pattern PXM’s Content Brief is driving conversion on ecommerce marketplaces using AI

AWS Machine Learning Blog

Pattern was founded in 2013 and has expanded to over 1,700 team members in 22 global locations, addressing the growing need for specialized ecommerce expertise. Scaling to handle 38 trillion data points Processing over 38 trillion data points is no small feat, but Pattern has risen to the challenge with a sophisticated scaling strategy.

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