Technology
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Factors of success in predictive supply chains
Wading through the miasma of supply chain technologies remains a challenge. What can help to guarantee success?
Ranked 6th out of 909 teams in the M5 forecasting competition
Lokad have come at the 6th position in the M5 Forecasting competition out of 909 competing teams. It’s an impressive feat.
Quantitative SCM vs Classic APS
Module-by-module comparison between classic APS (Advance Planning and Scheduling) systems and the quantitative supply chain as implemented by Lokad.
Why not Python
Envision, the domain-specific language (DSL) of Lokad, was engineered to address challenges where Python will never deliver cost-effective solutions.
Integers and uncertainty in differentiable programming
Technical insights on how two challenges are addressed from a differentiable programming perspective.
Differentiable Programming as in ‘AI’ that works
The path to unlock a series of supply chain scenarios that were before seen as largely intractable.
An algebra for supply chain economics
How zedfuncs algebra can be leveraged for probabilistic forecasting.
Columnar Random Forests
While random forests are no longer state-of-the-art machine learning they still offer advantages.
Beyond in-memory databases
In-memory databases used to be an IT buzzword, but it hasn't aged well
From Crps to Cross Entropy
Thanks to CRPS Lokad cracked its aerospace & fashion challenges, but it's not without its flaws
Probabilistic promotions forecasting
Forecasting promotions can be a nightmare. See how our forecasting engine deals with uncertain futures.
Working with uncertain futures
The future is uncertain, learn how Lokad has embraced this through an algebra of distributions.