Trigo is a provider of AI & computer vision based checkout-free systems for the retail market, enabling frictionless checkout and a range of other in-store operational and marketing solutions such as predictive inventory management, security and fraud prevention, pricing optimization and event-driven marketing.

In addition to the very real negative impact on every person around the world, the COVID-19 pandemic is driving business disruptions and closures at an unprecedented scale. Enormous government stimulus programs are resulting in explosions in fiscal deficits, regulators are relaxing capital constraints on banks and central banks are supporting economic stability with a range of interest rate cuts and other stimulus measures.

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.

If you are a software engineer, there's a good chance that deep learning will inevitably become part of your job in the future. Even if you're not building the models that directly use CNNs, you might have to collaborate with data scientists or help business partners better understand what is going on under the hood. In this article, Julie Kent dives into the world of convolutional neural networks and explains it all in a not-so-scary way.