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Business Problem UKG Ready primarily operates in the Small and Medium Business (SMB) space, so inherently many customers are forced to operate and make key business decisions with less Workforce Management (WFM) / Human Capital Management (HCM) data. In addition to volume, SMB lacks the variety of data needed to create a dynamic and agile organization. …
Each day, countless documents are created, revised, and shared across organizations. The result is a treasure trove of information, but because the data is primarily unstructured — without rows, columns or some other predefined organizational schema — it is difficult to interpret, analyze or use for business processes. That’s why we introducedDocument AI: so users …
Read more “Document AI adds one-click model training with ML Workbench”
Non-autoregressive approaches aim to improve the inference speed of translation models by only requiring a single forward pass to generate the output sequence instead of iteratively producing each predicted token. Consequently, their translation quality still tends to be inferior to their autoregressive counterparts due to several issues involving output token interdependence. In this work, we …
Read more “Non-Autoregressive Neural Machine Translation: A Call for Clarity”
Dialog modelling faces a difficult trade-off. Models are trained on a large amount of text, yet their responses need to be limited to a desired scope and style of a dialog agent. Because the datasets used to achieve the former contain language that is not compatible with the latter, pre-trained dialog models are fine-tuned on …
Read more “Prompting for a Conversation: How to Control a Dialog Model?”
Maximum mutual information (MMI) has become one of the two de facto methods for sequence-level training of speech recognition acoustic models. This paper aims to isolate, identify and bring forward the implicit modelling decisions induced by the design implementation of standard finite state transducer (FST) lattice based MMI training framework. The paper particularly investigates the …
(An English-language version of this post can be read here.) Während sich das Klima verändert, die Bevölkerung zwar langsamer, aber zumindest mittelfristig unaufhaltsam weiter wächst und die globalen Ansprüche an den Lebensstandard steigen, ist sauberes Wasser eine der kostbarsten natürlichen Ressourcen. In den Industrieländern ist sauberes, fließendes Wasser eine Selbstverständlichkeit, und um das auch weiter zu …
Read more “Vernetzte Versorgungsunternehme: Der Weg zu einer nachhaltigen Wasserwirtschaft”
When Newcomp Analytics started working with chocolatier Lindt Canada more than 15 years ago to support their supply chain, Lindt had no full-time IT personnel for analytics. Lindt now has a team of 10, including a business intelligence (BI) manager and BI developer analysts. Yet Newcomp continues to be an essential and trusted partner, helping …
Read more “How Newcomp Analytics partners with IBM to advance clients’ supply chain insights”
This post is co-written with Chaim Rand from Mobileye. Certain machine learning (ML) workloads, such as training computer vision models or reinforcement learning, often involve combining the GPU- or accelerator-intensive task of neural network model training with the CPU-intensive task of data preprocessing, like image augmentation. When both types of tasks run on the same …
With environmental, social, and governance (ESG) initiatives becoming more important for companies, our customer, one of Greater China region’s top convenience store chains, has been seeking a solution to reduce food waste (currently over $3.5 million USD per year). Doing so will allow them to not only realize substantial operating savings, but also support corporate …
October 23rd (this past Sunday) was my 5th Googleversery and we just wrapped up an incredible Google Next 2022! It was great to see so many customers and my colleagues in person this year in New York City. This blog is an attempt to share progress we have made since last year (4th year anniversary …
Read more “An annual roundup of Google Data Analytics innovations”