We’re excited to introduce v 0.15 of Allegro Trains. With this version we’ve taken Trains one step further to provide even more powerful features for the community to manage their AI workloads.

There’s a lot to track when training your ML models, and there’s no way around it; reviews and comparisons for best performance are virtually impossible without logging each experiment in detail. Yes, building models and experimenting with them is exciting work, but let’s agree that all that documentation can be laborious and error-prone – especially when you are essentially doing data entry grunt work, manually, using Excel spreadsheets.

May 14, 2020 — Allegro AI today announced that it joined the NVIDIA DGX-Ready Software program. Organizations that want to leverage AI to improve products and services often struggle to implement an advanced infrastructure that supports the unique and challenging demands of machine learning and deep learning.

The introduction of AI into products and services – across all sectors – is creating new capabilities at a scale that software developers could never have dreamed of just a decade ago. But this development is not just about the tech.

Readers of this blog have probably read about allegro.ai’s partnership with NetApp. Earlier this year the two companies showcased an integrated AI solution at the NVIDIA GPU Technology Conference (GTC) which took place in San Jose, California.

This conference is shaping up to be the largest ever focused on Computer Vision and Visual Artificial Intelligence. We invite you to attend the session and meet our experts. To arrange a time to meet during the conference, send an email to Neil Berns at neil.berns@allegro.ai.

Self-driving vehicles, weather forecasting drones, fulfilment robots and robotic surgery are already transforming the lives of millions of people. It is deep learning computer vision (DL CV) — visual sensors coupled with the ability to make instantaneous, human-like sense out of streaming video — that make these applications possible. One might think that acute focus on DL CV applications would be sufficient to yield the necessary breakthroughs and successful industry applications.