Sasha Rubel
Head of AI Generative AI Policy EMEA
Amazon Web Services
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Beyond the Glitch: Understanding and Mitigating AI Hallucinations
By 2030, 86% of businesses will be using AI, with its integration already permeating both public and private sectors. A frequently cited challenge that might slow this adoption are "hallucinations", where models generate fabricated or inaccurate outputs, increasing the risk of bias reinforcement and errors in application. One root cause of this phenomenon lies in AI training datasets, which, shaped by human design, inherently replicate biases. As AI becomes more embedded in our professional and personal lives, from education to healthcare, a course correction is needed. What role does AI play in shaping our access to information? Does it mitigate or amplify bias? Who holds the responsibility for addressing these concerns—dataset providers, developers, AI companies, or end users? How can we "fix" and prevent these biases? And could open-source models offer a more diverse and inclusive solution?
Beyond the Glitch: Understanding & Mitigating AI Hallucinations
As AI adoption reaches 86% by 2030, addressing hallucinations and bias becomes crucial. Explore how training data shapes AI accuracy, who's responsible for bias mitigation, and whether open-source models offer more inclusive solutions for healthcare, education, and beyond.
The New York Times Debate: Is AI the New Plastic?
Remember when plastic was everything? The golden ticket to cheaper manufacturing, maximum profit and easier living? Turns out the saying is true: Nothing comes without a price; and the world has paid its weight, now, in environmental devastation and a plastic island the size of a small continent floating around the Pacific. Some argue that the same will be true of artificial intelligence. It has been hailed as the most transformative technology since the internet, and could have huge benefits for battling climate change, industries, government and more. But concerns are piling up. The amount of energy required to build AI is already harming the planet more than helping it and big questions are being asking about its potential impact on society and ethical concerns. Will the benefits of AI outweigh its costs?