Generative Adversarial Networks (GANs) are powerful tools for image synthesis. However, they require access to vast amounts of training data, which is often costly and prohibitive. Limited data affects GANs, leading to discriminator overfitting and training instability. In this paper, we present a novel approach called NoIse-modulated Consistency rEgularization (NICE) to overcome these challenges. To this end, we introduce an adaptive multiplicative noise into the discriminator to modulate its latent features. We demonstrate the effectiveness of such a modulation in preventing discriminator overfitting by adaptively reducing the Rademacher complexity of the discriminator. However, this modulation leads to an unintended consequence of increased gradient norm, which can undermine the stability of GAN training. To mitigate this undesirable effect, we impose a constraint on the discriminator, ensuring its consistency for the same inputs under different noise modulations. The constraint effectively penalizes the first and second-order gradients of latent features, enhancing GAN stability.

Another day, another new term, but this one–suiteform– fits my roundup. I'll explain that term in a moment. But first, I want to note that NICE is framing the AI narrative at a higher, perhaps more ambitious level, than what most other vendors are doing in this space. Most of the talking points from the vendor events around AI and the contact center have been on the details and all the wonderful new features. We definitely need that, but NICE's CEO, Barak Eilam, is more interested in the bigger picture and what all these transformative changes mean.

Another day, another new term, but this one–suiteform– fits my roundup. I'll explain that term in a moment. But first, I want to note that NICE is framing the AI narrative at a higher, perhaps more ambitious level, than what most other vendors are doing in this space. Most of the talking points from the vendor events around AI and the contact center have been on the details and all the wonderful new features. We definitely need that, but NICE's CEO, Barak Eilam, is more interested in the bigger picture and what all these transformative changes mean.

A new artificial intelligence sleep app has been developed that might be able to replace sleeping pills for insomnia sufferers. Sleepio uses an AI algorithm to provide individuals with tailored cognitive behavioural therapy for insomnia (CBT-I). The National Institute for Health and Care Excellence (Nice) said it would save the NHS money as well as reduce prescriptions of medicines such as zolpidem and zopiclone, which can be dependency forming. Its economic analysis found healthcare costs were lower after one year of using Sleepio, mostly because of fewer GP appointments and sleeping pills prescribed. The app provides a digital six-week self-help programme involving a sleep test, weekly interactive CBT-I sessions and keeping a diary about sleeping patterns.