
Neeraj K. Arora
Articles
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1 month ago |
dialnet.unirioja.es | Neeraj K. Arora |Ishita Chakraborty |Yohei Nishimura
Ayuda Buscar en la ayuda Buscar en la ayuda
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Jan 14, 2025 |
ama.org | Neeraj K. Arora |Ishita Chakraborty |Yohei Nishimura
Generative AI (GenAI), and large language models (LLMs) in particular, are transforming marketing. According to a 2023 BCG study, over 70% of chief marketing officers have embraced this technology, and experts predict GenAI to revolutionize marketing research—a $84.3 billion dollar industry in 2023—by automating and enhancing data collection, analysis, and insights generation.
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Aug 20, 2024 |
morganlewis.com | Jane Accomando |Neeraj K. Arora |J. Daniel Skees |Mark Lazaroff |Alex S. Polonsky |Arjun Prasad Ramadevanahalli
Partners Jane Accomando, Neeraj Arora, Dan Skees, Mark Lazaroff, Alex Polonsky, and Andrew Gray and associate Arjun Ramadevanahalli co-authored a Law360 Expert Analysis exploring the critical issues at the nexus of artificial intelligence (AI) and energy use in the United States.
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Aug 13, 2024 |
jdsupra.com | Jane Accomando |Neeraj K. Arora |Andrew Gray IV
Artificial intelligence (AI) not only provides new technological advantages to the energy industry, but also the industry is itself responsible for providing the vast (and growing) amount of energy consumption driven by the computers powering much of AI. AI technologies, particularly those involving machine learning and large language models, are extremely energy intensive. For instance, a single generative AI query requires nearly 10 times more electricity than a traditional internet search.
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Aug 12, 2024 |
lexology.com | Jane Accomando |Neeraj K. Arora |Mark Lazaroff |Alex S. Polonsky |Arjun Prasad Ramadevanahalli |J. Daniel Skees
Artificial intelligence (AI) not only provides new technological advantages to the energy industry, but also the industry is itself responsible for providing the vast (and growing) amount of energy consumption driven by the computers powering much of AI. AI technologies, particularly those involving machine learning and large language models, are extremely energy intensive. For instance, a single generative AI query requires nearly 10 times more electricity than a traditional internet search.
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