Technology

Solar energy has become a popular source of sustainable energy in recent years. However, the intermittent nature of solar energy has limited its use for certain applications, such as IoT devices, live remote sensing, and off-grid power supplies. Conventionally, batteries are used to store the energy generated by solar cells, but combining the two technologies
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Artificial intelligence (AI) and machine learning tools have become increasingly common in today’s technological landscape. However, most of these tools are based on “black box” models, which analyze data and make predictions without sharing their processes with human users. To address this issue, researchers at Meta Reality Labs have created a framework called XAIR that
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Artificial intelligence has long been a topic of concern for many technology leaders and researchers, who believe it could pose a threat to humanity. Stephen Hawking, for example, once warned that the development of AI could spell the end of the human race. Others, such as OpenAI co-founder Elon Musk, have expressed similar worries, stating
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Germany’s Economy Minister, Robert Habeck, has presented a plan to cap the price of electricity used by energy-intensive industries. The move aims to insulate the sector against sharp cost increases. However, the proposal has already sparked criticism. The cap would be set at €0.06 ($0.07) per gigawatt-hour (GWh) and would apply until 2030. At least
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Researchers have been trying to develop more energy-efficient and faster machine learning systems that can replicate the versatile computational abilities of biological neurons for decades. One promising approach has been the use of memristors – electronic components that can store a value by modifying their conductance and then use that value for in-memory processing. However,
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Experts at the University of Oxford and international collaborators have released a new study in Nature Machine Intelligence that addresses the ethical concerns related to the responsibility for outputs generated by large language models (LLMs). LLMs such as ChatGPT pose critical issues regarding the attribution of credit and rights for useful text generation, which differs
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