Dialpad to Raise $50m to Expand Conversational AI

Funds are planed to be spent on strengthen and expand its AI services to additional products, including enterprise video chat service UberConference
17 July 2018   660

Tech company Dialpad reported on the closure of a $50 million funding round. Funds are planed to be spent on strengthen and expand its conversational AI services to additional products, including enterprise video chat service UberConference. This is reported by VentureBeat.

Dialpad uses VoiceAI from acquired TalkIQ into UberConference, Dialpad phone replacement, and offerings for call center customer service agents. VoiceAI can:

  • provide coaching tips
  • determine whether the person on the other end of a phone or video call is happy with what they’re hearing
  • automatically generate action items from meetings and speech-to-text transcripts.

Evolving from a product standpoint, we’ll be adding multiparty video to it [UberConference] shortly. Beyond that, we will be adding the same AI pieces to it that are in Dialpad and Dialpad Call Center. Having a unified artificial intelligence experience lets a business have much better visibility into how the business is being run, how they’re talking about their products, how their sales and support reps are providing support.

Craig Walker

CEO, Dialpad

Earlier Walker founded GrandCentral, a VoIP company acquired by Google in 2007 that would become Google Voice.

Iconiq Capital, Andreessen Horowitz, Amasia, Scale Ventures, and Section 32 took part in the investment. It follows a $17 million round last September. Since its launch in 2011, Dialpad has raised $120 million.

Funding will also be used to grow the company’s headcount by 100 employees. At the moment, it has 275 employees. 

Neural Network to Create Landscapes from Sketches

Nvidia created GauGAN model that uses generative-competitive neural networks to process segmented images and create beautiful landscapes from peoples' sketches
20 March 2019   138

At the GTC 2019 conference, NVIDIA presented a demo version of the GauGAN neural network, which can turn sketchy drawings into photorealistic images.

The GauGAN model, named after the famous artist Paul Gauguin, uses generative-competitive neural networks to process segmented images. The generator creates an image and transfers it to the discriminator trained in real photographs. He in turn pixel-by-pixel tells the generator what to fix and where.

Simply put, the principle of the neural network is similar to the coloring of the coloring, but instead of children's drawings, it produces beautiful landscapes. Its creators emphasize that it does not just glue pieces of images, but generates unique ones, like a real artist.

Among other things, the neural network is able to imitate the styles of various artists and change the times of the day and year in the image. It also generates realistic reflections on water surfaces, such as ponds and rivers.

So far, GauGAN is configured to work with landscapes, but the neural network architecture allows us to train it to create urban images as well. The source text of the report in PDF is available here.

GauGAN can be useful to both architects and city planners, and landscape designers with game developers. An AI that understands what the real world looks like will simplify the implementation of their ideas and help you quickly change them. Soon the neural network will be available on the AI ​​Playground.