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.

Apple's Phil Schiller just shared his honest thoughts about the Amazon Echo and Google Home smart speakers. He also indirectly pointed out what he thinks is lacking in these devices. Gadgets 360 has finally published its interview with Apple's Senior Vice President of Worldwide Marketing when he was in Bengaluru, India last March. When Schiller was asked to comment on the famous smart speakers Amazon Echo and Google Home, he responded that he won't give specific comments on each device. He then candidly added, "My mother used to have a saying that if you don't have something nice to say, say nothing at all." Schiller continued by saying that he'll just tackle the general concepts.

The term customer journey may sound exotic to the non-initiated, but it is as widespread in the industry as it is simple. It refers to the stages that customers go through in interacting with a company, from buying products online to accessing customer services on the phone. A defining feature of customer journeys is the fact that they span interaction channels, and combined with the facts that there are many interactions and they can be quite complicated, it all results in challenging scenarios for analytics. This is where NICE customer journey optimization (CJO) comes in, as NICE specializes in customer journeys. This is a typical example of domain-specific analytics, albeit implemented in a non-typical way.