DALL-E and Midjourney are examples of GAN-based generative AI models. Variational autoencoders leverage two networks to interpret and generate data — in this case, an encoder and a decoder.

Most generative AI leverages Transformer models, including encoder, decoder, or encoder-decoder ... Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) Generative AI tools ...

Generative AI models are highly scalable ... of data to generate in a sequence of data. Encoders and/or decoders are built into the platform to decode the tokens or blocks of content that have ...

How’s that possible? Generative AI works on the back of three prominent frameworks; (iii) Variational Auto-Encoders. These frameworks help the AI to gather consensual data, process this large ...

Generative artificial intelligence and its creations are everywhere these days. Whether scrolling through your Instagram feed or catching up on your go-to blog, AI's influence is undeniable.

Generative models are extremely effective in domains such as language and images but have yet to make a similarly deep impact on chemistry. “The Variational AI scientific team has spent years ...

Merck & Co. is taking a look at a generative AI platform. As an early user of Variational AI’s technology, the Big Pharma will assess the ability of the platform to generate novel small ...

Common architectures used in generative AI include Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), both of which help the model learn to generate high-quality ...