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Many big companies are currently embracing generative AI tools, but what impact will this have on the economy? McKinsey & Company, a global consulting leader, has attempted to quantify the trend in a new report titled “The Economic Potential of Generative AI”. The report finds that GenAI could add $2.6 trillion to $4.4 trillion annually
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Google’s return-to-office plans have been a source of concern across the company since the pandemic. The company has updated its hybrid three-day-a-week office policy and included badge tracking, which has caused frustration among employees. There is growing concern among staffers that management is overreaching in its oversight of physical attendance. Employees are being treated like
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Renewable Energy Technologies (RETs) are seen as disruptive innovations as they challenge the existing market structures that prioritize state-owned, fossil fuel-based energy companies. According to Oskar Juszczyk’s doctoral dissertation from the University of Vaasa, a supportive regulatory regime and inter-sectoral collaboration are crucial for the successful diffusion of RETs. Juszczyk’s dissertation in the field of
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UN Secretary-General Antonio Guterres has supported a proposal by some artificial intelligence (AI) executives to establish an international AI watchdog body similar to the International Atomic Energy Agency (IAEA). The use of generative AI technology, capable of creating authoritative prose from text prompts, has garnered public attention since the launch of ChatGPT six months ago,
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ServiceNow recently announced the launch of its latest generative AI solution, Now Assist for Virtual Agent. It aims to revolutionize self-service by providing intelligent and relevant conversational experiences. ServiceNow’s Now Platform enables customers to streamline digital workflows and optimize productivity by integrating generative AI capabilities. Features of Now Assist for Virtual Agent Now Assist for
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Oracle Corporation, a software giant famous for its database technology, has announced its partnership with Cohere, a Toronto-based start-up that specializes in building and training large language models (LLMs). The two companies are developing a cloud service that would enable enterprises to train their custom LLMs using their private data while protecting their privacy and
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