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From checkers to chess: A brief history of IBM AI

IBM Journey to AI blog

Where it all started During the second half of the 20 th century, IBM researchers used popular games such as checkers and backgammon to train some of the earliest neural networks, developing technologies that would become the basis for 21 st -century AI. In a televised Jeopardy!

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Revolutionizing Your Device Experience: How Appleā€™s AI is Redefining Technology

Unite.AI

Over the past decade, advancements in machine learning, Natural Language Processing (NLP), and neural networks have transformed the field. Apple introduced Siri in 2011, marking the beginning of AI integration into everyday devices. Notable acquisitions include companies like Xnor.a

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What Is Retrieval-Augmented Generation?

NVIDIA

Under the hood, LLMs are neural networks, typically measured by how many parameters they contain. Thatā€™s when researchers in information retrieval prototyped what they called question-answering systems, apps that use natural language processing ( NLP ) to access text, initially in narrow topics such as baseball.

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Testing the Robustness of LSTM-Based Sentiment AnalysisĀ Models

John Snow Labs

Sentiment analysis, a branch of natural language processing (NLP), has evolved as an effective method for determining the underlying attitudes, emotions, and views represented in textual information. Sentiment Analysis Using Simplified Long Short-term Memory Recurrent Neural Networks. abs/2005.03993 Andrew L. Maas, Raymond E.

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Implementing a custom trainable component for relation extraction

Explosion

Youā€™ll see how you can utilize Thincā€™s flexible and customizable system to build an NLP pipeline for biomedical relation extraction. In spaCy v3 , we introduced a new, flexible training configuration system that gives you much more control over the various components in your NLP pipeline.

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From text to dream job: Building an NLP-based job recommender at Talent.com with Amazon SageMaker

AWS Machine Learning Blog

Founded in 2011, Talent.com is one of the worldā€™s largest sources of employment. The triple-tower architecture provides three parallel deep neural networks, with each tower processing a set of features independently. This design pattern allows the model to learn distinct representations from different sources of information.

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Understanding the different types and kinds of Artificial Intelligence

IBM Journey to AI blog

For example, Apple made Siri a feature of its iOS in 2011. However, AI capabilities have been evolving steadily since the breakthrough development of artificial neural networks in 2012, which allow machines to engage in reinforcement learning and simulate how the human brain processes information.