Criteo Introduces “Virtual Advanced Quantum Adept Neural-Net Technology” (VAQANT) for Predictive Search

In continued efforts to push the frontier of performance marketing and contribute back to academic and open source community, Criteo is open-sourcing a new AI framework, “Virtual Advanced Quantum Adept Neural-Net Technology” (VAQANT) from the Predictive Search team. “Since its inception, we’ve observed 404% of improved performance for our Predictive Search customers.” said Mohsin Hussain, VP of Engineering at Criteo. “It’s amazing what our engineers have built in our 2017 Sprint 3-day hackathon.”

The framework virtualization layer runs on top of Criteo’s existing Hadoop cluster – the largest in Europe. Using quantum linear superposition and entanglement, the virtualized computing layer is actually producing more computing power then the underlying hardware system by 301%.

Vice President and Chairman at Wayne Enterprises, Bruce W. praised the framework’s value, “Optimizing Google Shopping campaigns is no easy task. We are amazed with how Criteo is taking it to the next level with the new framework – as we no longer have to maintain or send future product catalogs!” The Framework is capable of predicting new product catalogs that will be submitted in future. Essentially eradicating needs for Predictive Search customers to upload future product catalogs.

Highly probabilistic in nature. Its applications is limitless. “We’ve started using it to predict the next cup of coffee to make in breakroom and who will be coming for it.” said Jonathan Wu, an engineer in the Palo Alto team. The new framework complements existing classical Von Neuman architectures well as the virtualized quantum-computing environment runs on top of our standard x86 Hadoop clusters where a quantum neural network was activated to run data experiments. The data-center teams have been in the process reducing our datacenter foot-print and reducing our impact to the environment as a whole!

If accelerating the world towards the Singularity sounds like exciting challenge to you. We are hiring! Check out our career’s page at https://labs.criteo.com/rd-jobs/

Post written by:

Mingchen Tsai

Software Engineer, R&D – Palo Alto