Remove 2012 Remove Explainability Remove Natural Language Processing
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AI News Weekly - Issue #349: AI chip startup d-Matrix raises $110 million with backing from Microsoft - Sep 7th 2023

AI Weekly

theverge.com Inside Elon Musk's Struggle for the Future of AI At a conference in 2012, Elon Musk met Demis Hassabis, the video-game designer and artificial--intelligence researcher who had co-founded a company named DeepMind that sought to design computers that could learn how to think like humans. invideo.io

Robotics 241
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5 Best AI Language Learning Apps

Unite.AI

Artificial intelligence has had a dramatic impact on language learning, offering personalized and efficient ways to master new tongues. AI-powered language learning apps leverage advanced algorithms, natural language processing, and adaptive technologies to create tailored learning experiences.

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A comprehensive guide to learning LLMs (Foundational Models)

Mlearning.ai

Learning LLMs (Foundational Models) Base Knowledge / Concepts: What is AI, ML and NLP Introduction to ML and AI — MFML Part 1 — YouTube What is NLP (Natural Language Processing)? — YouTube YouTube Introduction to Natural Language Processing (NLP) NLP 2012 Dan Jurafsky and Chris Manning (1.1)

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Build a serverless voice-based contextual chatbot for people with disabilities using Amazon Bedrock

AWS Machine Learning Blog

We demonstrate the process of integrating Anthropic Claude’s advanced natural language processing capabilities with the serverless architecture of Amazon Bedrock, enabling the deployment of a highly scalable and cost-effective solution. For our LLM, we use Anthropic Claude on Amazon Bedrock.

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The History of Artificial Intelligence (AI)

Pickl AI

” During this time, researchers made remarkable strides in natural language processing, robotics, and expert systems. Notable achievements included the development of ELIZA, an early natural language processing program created by Joseph Weizenbaum, which simulated human conversation.

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Top Predictive Analytics Tools/Platforms (2023)

Marktechpost

Using causal graphs, LIME, Shapley, and the decision tree surrogate approach, the organization also provides various features to make it easier to develop explainability into predictive analytics models. When necessary, the platform also enables numerous governance and explainability elements.

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Dead Code Should Be Buried

Explosion

Natural Language Processing moves fast, so maintaining a good library means constantly throwing things away. This post explains the problem, why it’s so damaging, and why I wrote spaCy to do things differently. But most Natural Language Processing libraries do, and it’s terrible.