Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Generative AI and large language models (LLMs) seem to have burst onto the scene like a supernova. LLMs are machine learning models that are trained using enormous amounts of data to understand and generate human language. LLMs like ChatGPT and Bard have made a far wider audience aware of generative AI technology. Understandably, organizations that want to sharpen their competitive edge are keen to get on the bandwagon and harness the power of AI and LLMs.

According to figures published in the ONS Crime Survey on 19 October, the rate of shop theft in the UK increased by 25 percent in the year ending June 2023. The Association of Convenience Stores (ACS), meanwhile, reported more than 1.1m instance of theft in 2022, with many carried out by organised gangs.

As you may have seen in the press earlier this year, Stripe OLT recently achieved two crucial Microsoft certifications, in both Modern Work and Security. These certifications (also known as designations) are important to Microsoft solution partners because they signify a deep understanding and proficiency of specific Microsoft technologies.

Citizen developers, often without a formal background in programming, are harnessing the power of generative AI capabilities to create powerful business applications and automations in low-code/no-code platforms like Microsoft Power Platform, Salesforce, and ServiceNow. While this democratization of software development brings about numerous benefits, it also introduces a host of new cybersecurity risks that organizations must address to safeguard their sensitive data and maintain compliance standards.