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The Value of Machine Unlearning for Businesses, Fairness, and Freedom

Our work as data scientists is often focused on building predictive models. We work with vast quantities of data, and the more we have, the better our models and predictions can potentially become. When we have a high-performing model, we continue to retrain and iterate, introducing new data as required to keep our model fresh and free from degrading. The result is that the model’s performance level is largely retained and we, therefore, continue delivering value for users. 

But what happens if restrictions around a data set or individual data point are introduced? How then do we remove this information without compromising the model overall and without kicking off potentially intense retraining sessions? A potential answer that is gaining interest, and that we would like to explore, is machine unlearning. 

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Unrivaled Research and Development: How Technical SEO Can Change the R and D Game for Businesses

R&D is a heavily resource-rich aspect of business that can also consume more time and energy in overcoming the challenges that they sought to overcome. It can also form a creativity drain that may even fail to produce any tangible results. However, R&D is an essential innovative tool in the development of new technologies, products, and market insights. 

Meanwhile, SEO operates largely in the realm of marketing where R&D influenced technologies like machine learning and AI are beginning to enjoy heavier levels of influence. In an industry still dominated by the financial might of traditional companies, the influence of technology in SEO can help to provide smaller businesses and startups with a fighting chance. 

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Threat Modelling Tools Analysis 101

Abstract

An interconnected world with an increasing number of systems, products and services relying on the availability, confidentiality, and integrity of sensitive information is vulnerable to attacks and incidents. Unfortunately, the threat landscape expands and new threats, threat agents and attack vectors emerge at all times. Defending against these threats requires that organizations are aware of such threats and threat agents. Threat modeling can be used as part of security risk analysis to systematically iterate over possible threat scenarios.

The motivation for this research came from the constantly growing need to acquire better tools to tackle the broad and expanding threat landscape. One such tool which help to categorize and systematically evaluate the security of a system, product or service, is threat modeling.