Deep Render, a London-based machine learning startup has announced it has raised £1.6 million, led by Pentech with participation from Speedinvest, to fund further development of its revolutionary image compression technology.
Instead of building on the current, decades-old software that is no longer fit for purpose, Deep Render’s proprietary tech has reinvented the entire process, from scratch, in order to mimic the neural processes of the human eye.
This reduces the file size of images by 10x compared to the best industry standards, while maintaining the same level of visual quality.
Having spun out of Imperial College London’s leading robotics lab, Deep Render’s founders Arsalan Zafar and Chri Besenbruch believe their technology not only has the power to transform how everyday people consume data – an issue that has been highlighted in the wake of the COVID-19 outbreak – but it will revolutionise entire industries and organisations across every sector.
Every two years, the global demand for data doubles and 90% of the total data created by humanity was generated in the past two years. As a result, the entire digital universe in 2020 is set to reach an almost incomprehensible 44 zettabytes.
Today’s media compression is buckling under this weight. A fact being acutely felt in the wake of the coronavirus pandemic in which an increase of people working from home has put added demand on streaming sites like Netflix, YouTube and Zoom.
Deep Render’s algorithm additionally pays special attention to the content of the image, which the human eye cares about the most, allowing for more visually pleasing images.
Co-Founder Arsalan Zafar says, “As humans, our eyes have evolved to care about certain colours and properties of the natural world. It helped us survive as hunters and gathers. We are more sensitive to the colour green as it represents fertile areas with food and water; we notice the slightest of movements in still scenes, as this helps us flee from sneaking predators.
“Accounting for these evolutionary instincts improves visual quality but teaching a machine to do so has been incredibly complex until now. Our technological breakthrough represents the foundation for a new class of compression methods.”
“We’re not trying to make the original software better, but replace it. Effectively, we are burning the existing compression technology to the ground; rewriting, redefining and reinventing the entire domain,” said Chri Besenbrush.