Machine Learning & Artificial Intelligence

Scaling to Trillion Parameter Models with Simple and Efficient Sparsity *In deep learning, models typically reuse the same parameters for all inputs. Mi...

A GPT-3 rival by Deepmind Researchers at DeepMind have proposed a new predicted compute-optimal model called Chinchilla that uses the same compute budge...

280 Billion Parameters Language model DeepMind’s language model, which it calls Gopher, is significantly more accurate than these existing ultra-large ...

Large Language Models, LLM, Language Models, Concepts, Examples, Machine Learning, Deep Learning, Tutorials, Interviews, News, AI

This figure was adapted from a similar image published in DistilBERT (opens in new tab). Turing Natural Language Generation (T-NLG) is a 17 billion parameter language model by Microsoft that outperforms the state of the art on many downstream NLP tasks. We present a demo of the model, including its freeform generation, question answering, and […]

Harness the power of Cohere's API to access pre-trained language models for AI-driven text generation. Create engaging content effortlessly. Get started for free.

This easy, efficient, and cost-effective framework helps developers build, train, and deploy large language models (LLMs) faster for enterprise application development.

After working with key partners for the past few months, we’re opening up access to Claude, our AI assistant.

Today, we’re releasing our LLaMA (Large Language Model Meta AI) foundational model with a gated release. LLaMA is more efficient and competitive with previously published models of a similar size on existing benchmarks.

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

PaLM 2 - Google’s next generation large language model.

LaMDA adds pieces to one of the most tantalizing sections of the language puzzle: conversation.

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A large language model (LLM) is a type of artificial intelligence model that has been trained to recognize and generate vast quantities of written human language.

Nature Biotechnology - Artificial neural networks have been applied to problems ranging from speech recognition to prediction of protein secondary structure, classification of cancers and gene...

A neural network is a series of algorithms that seek to identify relationships in a data set via a process that mimics how the human brain works.

Artificial Intelligence Neural Networks - Yet another research area in AI, neural networks, is inspired from the natural neural network of human nervous system.

This definition explains the meaning of Artificial Neural Network and why it matters.

This definition explains what an Artificial Neural Network (ANN) is and how they learn and operate. Various types of ANN computational models are listed and described as well as the applications, a...

“Deep learning,” the machine-learning technique behind the best-performing artificial-intelligence systems of the past decade, is really a revival of the 70-year-old concept of neural networks.

Artificial Neural Network Tutorial with Introduction, History of Artificial Neural Network, What is ANN, Adaptive Resonance Theory, Building Blocks, Genetic Algorithm etc.

A Computer Science portal for geeks. It contains well written, well thought and well explained computer science and programming articles, quizzes and practice/competitive programming/company interview Questions.

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The Artificial Neural Network (ANN) is a deep learning method that arose from the concept of the human brain Biological Neural Networks.

Find out what a neural network is, how and why businesses use neural networks,, and how to use neural networks on AWS.

Learn about neural networks that allow programs to recognize patterns and solve common problems in artificial intelligence, machine learning and deep learning.