Google’s recent announcement about “AI Overviews” has created divisive reception. On one hand, it’s helping us by giving a shortcut to an answer and saving us effort to sift through a bunch of results. On the other hand, this shortcut robs us of our agency and ability to verify, question, and learn. Is this the future we want for accessing and interacting with information?
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Mnemohistory, a term coined by German Egyptologist Jan Assmann, refers to the study of how societies remember and construct their historical narratives. Unlike traditional historiography, which focuses on the objective recording and analysis of past events, mnemohistory emphasises the subjective processes through which memories are formed, preserved, and transmitted across generations. It explores the ways in which collective memory shapes, and is shaped by, cultural, social, and political contexts. Mnemohistory investigates the symbols, rituals, and narratives that communities use to create a sense of shared identity and continuity with the past. Originating from the Greek word “mnemos” meaning memory, and “historia,” meaning enquiry or knowledge, mnemohistory looks into the interaction between memory and history, recognising that our understanding of the past is not static but constantly reinterpreted through the lens of present concerns and future aspirations.
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The study aims to comprehensively explore the impact of artificial intelligence (AI) on information retrieval systems, analysing the evolution, challenges, and future directions. It explores the role of AI in enhancing search relevance, user experience, and ethical considerations in information retrieval contexts. The findings highlight AI’s transformative capabilities in enhancing relevance, personalisation, and semantic understanding within information retrieval systems. Ethical considerations, such as bias mitigation and data privacy, are also addressed.
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If artificial intelligence is so smart, why can’t it explain itself? This somewhat flippant question has preoccupied AI developers and researchers from the earliest days. Over 50 years later, the question is still relevant and increasingly urgent. When generative AI can hallucinate with impunity, there is a problem. Explainability is part of the answer.
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Killer robots. Dystopian AI. Machine uprisings. Why are we utterly fascinated with the idea of our gadgets turning against us? Here I unravel our obsession with the rise of the machines and show that a big part of the appeal is really the projection of our own fears and dilemmas.
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Given AI’s dominance and growth potential, there is naturally enormous interest in decoding how AI will impact and shape India’s growth trajectory. To understand the landscape of artificial intelligence (AI) and the Information Technology (IT) industry in India, few voices resonate as profoundly as that of NR Narayana Murthy, the legendary co-founder of Infosys and a pioneering figure in India’s technological journey. With a career spanning decades, Narayana Murthy’s (NRN) insights have not only shaped the trajectory of Indian IT but have also influenced global perceptions of the industry.
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Individuals with intellectual disabilities require long-term education in specialized schools or institutions due to their unique learning needs and behavioral habits. Teachers with specialized training are essential in their education process. Based on volunteer experience at non-governmental organizations (NGOs) serving individuals with intellectual disabilities, we summarize common teaching strategies employed by teachers and challenges encountered in teaching to present the landscape of special education in China and to enlighten future LIS research.
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In the last two decades, AI has advanced leaps and bounds to the point where we are seriously having conversations about ‘it’ being ‘intelligent’ as humans or even surpassing humans. But before we get too wrapped up in that excitement or fear, it’s important that we look inwards and ask — what makes us intelligent, conscious, and human?
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Gemini is a new and powerful artificial intelligence model from Google that can understand not only text, but also images, videos and sounds. As a multimodal model, Gemini is capable of performing complex tasks in mathematics, physics, and other fields, as well as understanding and generating high-quality code in various programming languages.
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In this InfoFire episode, I am in conversation with eScience pioneer Tony Hey on the topic of “AI for Science.” Our fireside chat commences with the profound words of Richard Feynman, who had a significant influence on Tony Hey, and centers around the two books— Feynman Lectures on Computation: Anniversary Edition and Artificial Intelligence for Science: A Deep Learning Revolution, edited/coedited by Tony Heyand, published in 2023.
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