Lead Forensics

Artificial Intelligence

Tremau and Pangram Labs partner to take on AI-generated content

As we stand on the cusp of the biggest election year in history, the intersection of technology and democracy takes centre stage once again. More than 50 countries around the world with a combined population of around 4.2 billion will hold national and regional elections in 2024, featuring seven of the ten most populous nations […]

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What does it take to make your business LLM and GenAI proof?

Theodoros Evgeniou* (Tremau), Max Spero* (Checkfor.ai) Arguably “the person of the year for 2023” has been AI. We have all been taken by surprise by the speed of innovation and capabilities of Large Language Models (LLMs) and more generally generative AI (GenAI). At the same time, many, particularly in online platforms, raise questions about potential

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INSEAD Working Paper Series: Implementing Al Principles: Frameworks, Processes, and Tools

In recent years, a number of international organisations, regulators, governments, academics, and as well businesses have worked on developing principles of Artificial Intelligence (AI). Alongside the development of these principles, there is an on-going discussion on how to regulate AI in order to best align risk management with optimising potential value creation of these technologies.

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Science Journal: Beware explanations from Al in health care

Artificial intelligence and machine learning (AI/ML) algorithms are increasingly developed in health care for diagnosis and treatment of a variety of medical conditions. However, despite the technical prowess of such systems, their adoption has been challenging, and whether and how much they will actually improve health care remains to be seen. A central reason for

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Harvard Business Review: Al Regulation Is Coming

For years public concern about technological risk has focused on the misuse of personal data. But as firms embed more and more artificial intelligence in products and processes, attention is shifting to the potential for bad or biased decisions by algorithms—particularly the complex, evolving kind that diagnose cancers, drive cars, or approve loans. Inevitably, many

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