Category: A.I.

  • Abusive Language Detection for Muse Engine

    Overview Bach, multiple linked dialogue data platform for Muse engine, has utilized multiple resources – artificial intelligence, human reviewers, automated rating system, etc. – in an effort to generate best human-machine conversations, and a noisy data follows as a necessity from the development process. Noisy data is meaningless data, and its meaning can be expanded…

  • Musio’s High-Level Talks

    Introduction Producing sentences which are perceived as natural by a human is a crucial goal of all automated dialogue systems. It makes interactions more natural, avoids misunderstandings, and leads higher user satisifcation and user trust. However, making high-quality sentences constitutes hard challenges in terms of e.g., improving grammatical accuracy, or using a variety of sentences,…

  • Bach: data architecture for multi-linked dialogues

    Introduction Dialogue systems are systems intended to converse with human users, and recent advancements in AI have contributed to closing the gap between human-machine conversations in many consumer services. AKA Intelligence researchers also tried to build automated dialogue systems and finally set up its own dialogue system, Muse, being able to practice English in addition…

  • Evaluation for Muse Dialogue Engine 2019

    Introduction Recent advances in AI has contributed to the rebirth of a chatbot-type dialogue system being able to interact with people through natural language communication. This could help people better understand the world around them and communicate more effectively with others, effectively bridging communication gaps. Therefore, it is important to understand the quality attributes associated…

  • MUSE API (Beta) Sneak Peak

    Today, we have the sneak preview of MUSE API (Beta). MUSE API is what Musio actually talks to in the cloud to manage the dialogue and generate things to say, recognize faces, etc. In order to show you better some of the major things going on behind the Musio, we built a temporary front-end for…

  • Conditional Neural Network Architectures

    Table of Contents 1. Conditional Neural Network Architectures 1.1. goal 1.2. motivation 1.3. ingredients 1.4. steps 1.5. outlook 1.6. resources Conditional Neural Network Architectures goal Today we are going to have a look at conditional neural network architectures and present some of the findings in the recent papers “Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts…

  • Q&A with AKA – About Musio as an ‘AI Robot’

    Q&A with AKA – About Musio as an ‘AI Robot’

    Ever since we’ve introduced Musio to the whole world, we’ve received countless questions from our partners, investors, customers as well as curious enthusiasts. So we thought it would be a good idea to answer the most frequently asked questions to make Musio more engaging and easier to understand. We hope that the following Q&A sessions…

  • Adversarial techniques for dialogue generation

    Table of Contents 1. Adversarial techniques for dialogue generation 1.1. goal 1.2. motivation 1.3. ingredients 1.4. steps 1.5. outlook 1.6. resources Adversarial techniques for dialogue generation goal This week we are going to have a look at the latest developments of generative adversarial networks (GANs) in the field of dialogue generation by summarizing the paper…

  • Compression of neural networks

    Table of Contents 1. Compression and distillation of models 1.1. goal 1.2. motivation 1.3. ingredients 1.4. steps 1.5. outlook 1.6. resources Compression of neural networks goal In this blogpost we will have a look at methods for compressing and reducing deep neural network models in size. motivation The simple fact that bigger and deeper is…

  • Dilated causal convolutions for audio and text generation

    Table of Contents 1. Dilated causal convolutions for audio and text generation   causal dilation convolution 1.1. goal 1.2. motivation 1.3. ingredients 1.4. steps 1.5. outlook 1.6. resources Dilated causal convolutions for audio and text generation goal In today’s summary we dive into the architecture of WaveNet and its successor ByteNet which are autoregressive generative models for generating audio…