Jacob Parker-Bowles Fintech in Asia

  Jacob Parker-Bowles PhD candidate from  UCAM, the Catholic University of San Antonio of Murcia Abstract This paper examines the emerging threats to electoral integrity posed by advanced artificial intelligence systems, huge language models (LLMs) and generative adversarial networks (GANs). Through analysis of recent research in adversarial machine learning and social network dynamics, we identify critical vulnerabilities in current electoral systems and propose a framework for detecting and mitigating AI-powered disinformation campaigns. Our findings suggest that defensive measures are inadequate against sophisticated neural language models and synthetic media generation. 1. Introduction Artificial intelligence technologies pose unprecedented challenges to the integrity of democratic processes. Recent advances in neural architectures, particularly transformer-based models (Vaswani et al., 2017), have dramatically enhanced the capability to generate and distribute targete...

As a PhD researcher in AI and FinTech, I've had the opportunity to work with and evaluate various AI models and providers. In this comprehensive analysis, I'll break down the key players and their offerings, with a special focus on applications in financial technology. Large Language Models (LLMs) OpenAI Pros: GPT-4 offers superior reasoning and coding capabilities Extensive API documentation and integration options Strong performance in financial analysis and market research Robust safety measures and content filtering Cons: Higher pricing compared to competitors Occasional unexpected model behavior changes Limited control over model parameters API usage caps and waitlists for new features Anthropic Pros: Claude models show exceptional analysis capabilities Strong performance in mathematical and financial tasks Detailed, nuanced responses with less hallucination Constitutional AI approach for enhanced safety Cons: More limited third-party integration...

Pursuing a PhD is one of academia's most rewarding yet mentally challenging experiences. As someone currently navigating the complexities of a PhD in AI, I've encountered many of the struggles faced by PhD students worldwide. Long hours of research, the pressure to publish, imposter syndrome, and academic isolation can all take a toll on mental health. Mental Health Challenges in PhD Studies Imposter Syndrome : Feeling inadequate despite evidence of success is a common experience for many PhD students. No matter how much progress is made, it’s easy to feel like you don't belong or that your work isn’t good enough. Burnout : Research's long, solitary nature can lead to burnout, with many students struggling to maintain a healthy work-life balance. This can lead to prolonged periods of stress, affecting overall well-being. Isolation : The independent nature of PhD research often results in feelings of loneliness, as students spend significant time working on niche t...

  Artificial Intelligence (AI) is poised to reshape the workforce unprecedentedly, with implications for nearly every sector. As AI systems become more sophisticated, they are beginning to automate tasks previously exclusive to human workers, introducing challenges and opportunities for the future of work. AI's Impact on Labor AI has the potential to significantly alter the distribution of labour by automating routine tasks and enhancing human decision-making. Routine jobs—such as data entry, administrative support, and even aspects of legal and medical analysis—are likely to see increasing automation. This shift allows human workers to focus on tasks that require creativity, emotional intelligence, and complex problem-solving. As AI takes over repetitive tasks, workers must adapt by developing new skill sets to remain competitive in the evolving job market. Moreover, AI can enhance productivity in various industries by optimizing processes and workflows. In manufacturing, for exam...