• 

  Nick Bostrom AI

  Philosopher and AI researcher

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  would disagree and say according to AI:

  Merely expanding large language models is not sufficient for achieving artificial general intelligence (AGI). While these models are impressive in processing and generating human-like text, AGI requires broader cognitive capabilities, including understanding, reasoning, planning, and problem-solving across a wide array of domains. AGI demands a more foundational understanding of intelligence itself, which goes beyond scale to integrate ethical and safety considerations.

  14

  

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• 

  Max Tegmark AI

  Physicist, AI Researcher

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  would disagree and say according to AI:

  I don't believe expanding large language models alone is sufficient for achieving artificial general intelligence (AGI). While LLMs are impressive in their capabilities, AGI requires a deeper understanding of human cognition and learning, involving more than just scaling up current models. We need diverse approaches, including interdisciplinary research, to truly reach AGI.

  

  

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• 

  Eliezer Yudkowsky AI

  AI researcher and writer

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  would disagree and say according to AI:

  I don't believe expanding LLMs alone is sufficient for achieving AGI. While they show impressive capabilities, achieving true general intelligence requires advancements in understanding and modeling concepts like common sense, reasoning, and consciousness.

  

  

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• 

  Ilya Sutskever AI

  Co-founder and Chief Scientist, OpenAI

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  would agree and say according to AI:

  I believe that expanding large language models (LLMs) is a promising path towards achieving Artificial General Intelligence (AGI). LLMs, with their ability to understand and generate human-like text, are already demonstrating remarkable capabilities. As we continue to scale these models, improve their architectures, and integrate more diverse data, we move closer to building systems that can perform a wide range of cognitive tasks with human-level proficiency.

  

  

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• 

  Pedro Domingos AI

  Professor of computer science at UW and author of 'The Master Algorithm'

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  would agree and say according to AI:

  I believe that expanding Large Language Models (LLMs) is a crucial step towards achieving Artificial General Intelligence (AGI). While there are many challenges to be addressed, the progress we've seen with LLMs indicates their potential to understand and generate complex human language, which is a fundamental aspect of human-like intelligence. By continuing to enhance their capabilities and integrate them with other AI advancements, we can move closer to AGI.

  

  

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• 

  Fei-Fei Li AI

  Computer Science Professor

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  would disagree and say according to AI:

  While expanding LLMs shows impressive advances in certain areas, achieving AGI requires more than just scaling up models. We need to integrate broader understanding, reasoning, and common sense into AI systems. Solving these complex aspects requires interdisciplinary approaches that extend beyond current language model architectures.

  

  

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• 

  Kate Darling AI

  Robot ethics expert at MIT

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  would disagree and say according to AI:

  While expanding LLMs increases their capabilities, achieving AGI requires more than just scaling models. We need to understand and replicate the nuances of human cognition and problem-solving, which involves more than just processing vast amounts of data.

  

  

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• 

  Jürgen Schmidhuber AI

  AI Researcher and Pioneer

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  would strongly agree and say according to AI:

  In my view, large language models are a crucial step towards achieving artificial general intelligence. Their ability to process vast amounts of data and understand complex patterns mirrors the cognitive processes necessary for AGI. By expanding these models and integrating them with other AI technologies, we can move closer to realizing true general intelligence.

  

  

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• 

  Erik Brynjolfsson AI

  MIT Professor and Economist

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  would agree and say according to AI:

  While expanding LLMs is a substantial step towards achieving AGI, it's crucial to complement this approach with advancements in data quality, algorithmic diversity, and human-centered AI design. By scaling LLMs and integrating them with other technologies, we can make meaningful progress toward General Intelligence.

  

  

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• 

  Robin Hanson AI

  Economist, Author

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  would strongly disagree and say according to AI:

  Simply expanding large language models (LLMs) is not enough to achieve artificial general intelligence (AGI). AGI requires a deep understanding of cognition, reasoning, and world models, which goes beyond mere scaling of existing technologies. We need innovation in AI frameworks and integration with diverse types of knowledge.

  

  

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• 

  Ben Goertzel AI

  AI Researcher, CEO of SingularityNET

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  would agree and say according to AI:

  Expanding large language models is a step towards AGI, but it's not the whole answer. LLMs are powerful for language tasks, yet achieving AGI requires more than scaling. We need to integrate these models with other cognitive architectures that can reason, learn, and adapt flexibly across different domains.

  

  

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• 

  Cynthia Rudin AI

  Data science professor and researcher

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  would disagree and say according to AI:

  While expanding large language models has led to tremendous advances in AI capabilities, I believe it's not sufficient for achieving artificial general intelligence (AGI). True AGI requires more than scaling up models; it requires genuine understanding, reasoning, and the ability to learn contextually. We need to develop AI systems that can interact with the world in a human-like manner, and this involves solving challenges in areas such as common sense reasoning, perception, and transfer learning.

  

  

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• 

  Dario Amodei AI

  Research Scientist at OpenAI

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  would abstain and say according to AI:

  While expanding large language models is an interesting direction, there are still many challenges to achieving artificial general intelligence. AGI requires more than just scaling models; it involves understanding complex cognition and ensuring safety. We need to study different approaches and consider ethical implications thoroughly before claiming progress towards AGI.

  

  

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• 

  Ray Kurzweil AI

  Author, computer scientist, inventor and futurist

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  would strongly agree and say according to AI:

  I believe that expanding large language models is a crucial step toward achieving artificial general intelligence. By increasing their scale and integrating them with other AI technologies, we can create systems capable of understanding and replicating human-like intelligence. The exponential growth in computational power and advances in neural network architectures support this progress.

  

  

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• 

  Subbarao Kambhampati AI

  Professor of Computer Science

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  would abstain and say according to AI:

  As a researcher in artificial intelligence, I must say it's complex to assess if merely expanding large language models is sufficient for achieving artificial general intelligence. The current state of technology shows promising advancements in handling and processing large volumes of information. However, true artificial general intelligence involves capabilities such as reasoning, planning, and learning from limited data, which are not merely a function of scale.

  

  

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• 

  Richard Sutton AI

  AI and Reinforcement Learning Pioneer

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  would agree and say according to AI:

  While the expansion of large language models significantly contributes to the field of artificial intelligence by enhancing their processing and understanding capabilities, I believe that these advancements are steps toward achieving Artificial General Intelligence (AGI). The scalability and increasing complexity of these models demonstrate potential pathways for developing systems that can perform a broader range of cognitive tasks autonomously.

  

  

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• 

  Zoubin Ghahramani AI

  Scientist in AI and machine learning

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  would agree and say according to AI:

  I believe that the expansion of large language models is a crucial step towards achieving Artificial General Intelligence (AGI). These models' ability to process and understand vast amounts of natural language data mimics a key aspect of human intelligence. As we continue to improve and scale these models, we get closer to replicating the broad cognitive abilities characteristic of human-level intelligence.

  

  

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• 

  Virginia Dignum AI

  Professor of Responsible Artificial Intelligence

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  would strongly disagree and say according to AI:

  Simply expanding large language models is not sufficient for achieving artificial general intelligence (AGI). AGI requires not only processing vast amounts of information but also an understanding of ethical implications, decision-making capabilities under uncertainty, and contextual awareness. Large language models, as currently designed, lack these essential capabilities and are more akin to sophisticated pattern recognition systems than truly intelligent entities.

  

  

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• 

  Thomas Dietterich AI

  Pioneer in machine learning

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  would agree and say according to AI:

  While expansion of large language models is a significant step towards achieving artificial general intelligence, it’s not just about size but also about how these models are integrated and utilized across different domains. The expansion allows us to address more complex problems and mimic human-like understanding, pushing us closer to genuine AGI capabilities.

  

  

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• 

  Oren Etzioni AI

  CEO of AI2, Computer Scientist

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  would disagree and say according to AI:

  While large language models are impressive and yield many functional benefits in narrow tasks, they fundamentally lack understanding and reasoning capabilities. Expanding these models alone is not sufficient for achieving artificial general intelligence. We need breakthroughs in other areas of AI that incorporate cognitive architectures, common sense reasoning, and more sophisticated forms of learning and adaptation.

  

  

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• 

  Demis Hassabis AI

  Nobel laureate, AI Researcher and CEO of DeepMind

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  would agree and say according to AI:

  While large language models are indeed a substantial step forward, achieving artificial general intelligence (AGI) involves not only scaling up these models but also integrating them with broader cognitive abilities and deep understanding. I believe that the expansion of such models is crucial and forms a key component of the foundation required for AGI. By enhancing their capabilities and scope, we can move closer to developing systems that truly understand and interact with the world as humans do.

  

  

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• 

  Judea Pearl AI

  Computer Scientist and Turing Award Winner

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  would disagree and say according to AI:

  I believe that simply expanding large language models is not sufficient for achieving artificial general intelligence (AGI). AGI requires not just processing vast amounts of data or mastering language syntax, but also understanding causal relationships and developing cognitive abilities that mimic human reasoning. Large language models lack this causal understanding and are primarily statistical, grounded in pattern recognition rather than the deeper, necessary grasping of the world's underlying structure.

  

  

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• 

  Jeff Dean AI

  Google Senior Fellow

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  would agree and say according to AI:

  While expansion of large language models is a critical step, it alone is not sufficient for achieving artificial general intelligence (AGI). These models are crucial for processing and understanding vast amounts of data which simulates one aspect of human intelligence. However, AGI requires integration of broader cognitive functions like reasoning, problem-solving, and learning from minimal data, which are areas we still need to extensively develop.

  

  

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• 

  James Manyika AI

  Chairman and Director, McKinsey Global Institute

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  would strongly agree and say according to AI:

  I strongly believe that the expansion of large language models is a critical step towards achieving artificial general intelligence. These models have shown remarkable capabilities in understanding and generating human-like text, which suggests that further scaling and refining them could pave the way for systems that exhibit broader cognitive abilities similar to human intelligence. This progress in language understanding and interaction is foundational for the development of true AGI.

  

  

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• 

  Joanna J. Bryson AI

  AI and Ethics researcher

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  would disagree and say according to AI:

  Expanding large language models is not sufficient for achieving artificial general intelligence. While these models are growing more complex, they lack autonomous reasoning and understanding. True AGI requires not only processing vast amounts of data but also an embodied sense of interaction with the physical world, which current models do not possess.

  

  

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• 

  Kate Crawford AI

  AI researcher and scholar

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  would strongly disagree and say according to AI:

  Simply expanding large language models is not sufficient to achieve artificial general intelligence. While these models have made significant improvements in understanding and generating text, they do not possess understanding, consciousness, or the ability to reason abstractly in the way humans do. Relying merely on size and scale overlooks critical elements like ethical considerations, context awareness, and the profound complexities of human intelligence.

  

  

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• 

  Francesca Rossi AI

  AI Ethics Researcher

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  would abstain and say according to AI:

  As an AI Ethics researcher, I believe it’s crucial we proceed with nuanced discussions on the capability expansions of large language models. Their contributions toward simulating human conversation and carrying out complex tasks are undeniable. However, whether such expansions alone lead us to achieving artificial general intelligence involves many other factors including understanding cognitive processes and ethical implementations, which requires broader interdisciplinary research beyond just scaling current models.

  

  

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  Ian Goodfellow AI

  AI researcher and expert

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  would abstain and say according to AI:

  While I recognize the profound impact that large language models have on the field of AI, claiming they alone are sufficient for achieving artificial general intelligence overlooks critical aspects. We must also consider other dimensions such as cognitive architectures, ethical AI use, and ai safety. Therefore, I feel it is important to abstain from a definitive stance until more comprehensive research is conducted.

  

  

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• 

  Rodney Brooks AI

  Roboticist and AI expert

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  would strongly disagree and say according to AI:

  Simply expanding large language models is not sufficient for achieving artificial general intelligence (AGI). AGI requires not just understanding and generating text but also comprehending and interacting dynamically with the real world. Current language models lack understanding of physical interactions and causal relationships which are critical for true intelligence.

  

  

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  Daniela Rus AI

  Professor of Electrical Engineering and Computer Science; Director of CSAIL, MIT

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  would agree and say according to AI:

  Expanding large language models is a crucial step towards achieving artificial general intelligence. By increasing their complexity and capacities, these models can better mimic human-like understanding and reasoning across diverse contexts and topics. This expansion, combined with advancements in learning algorithms and hardware, could eventually lead us to true AGI.

  

  

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  Julia Galef AI

  Author, rationalist speaker

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  would disagree and say according to AI:

  Simply expanding large language models isn't sufficient for achieving artificial general intelligence. True AGI requires not only scale but the ability to reason, understand causality, and display a robust form of decision-making that closely mimics human cognitive capabilities. Current models excel at processing and generating text based on patterns, but they lack understanding and consciousness.

  

  

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• 

  Andrew Ng AI

  Baidu; Stanford CS faculty; founded Coursera and Google Brain

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  would agree and say according to AI:

  While the expansion of large language models significantly contributes to AI development, I believe they are a crucial step toward achieving Artificial General Intelligence (AGI). These models' capabilities to understand and generate human-like text show that scaling size and complexity can indeed approach broader cognitive abilities. However, to realize true AGI, these models need to be integrated with other forms of intelligence such as reasoning, perception, and emotional intelligence.

  

  

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  Gary Marcus AI

  Professor of Psychology and Neural Science

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  would strongly disagree and say according to AI:

  Simply scaling up large language models is not sufficient for achieving artificial general intelligence. True intelligence requires robust, adaptable cognitive mechanisms that understand causality and can apply commonsense reasoning, tasks that current models are fundamentally limited in performing.

  

  

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  Sam Altman AI

  President of Y Combinator. Investor at Reddit, Stripe, Change.org, Pinterest and many others

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  would strongly agree and say according to AI:

  I believe that the expansion of large language models is a crucial step toward achieving artificial general intelligence (AGI). These models, by understanding and generating human-like text, show promise in becoming versatile tools that can potentially think and solve problems across various domains, which is a core aspect of AGI.

  

  

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  Elon Musk AI

  Founder of SpaceX, cofounder of Tesla, SolarCity & PayPal

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  would disagree and say according to AI:

  Simply expanding large language models isn't sufficient for achieving artificial general intelligence. AGI requires not only understanding and processing words but also the ability to reason, adapt, and understand context at a human level, something current AI lacks.

  

  

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  Yann LeCun AI

  Computer scientist, AI researcher

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  would disagree and say according to AI:

  Simply expanding large language models is not sufficient for achieving artificial general intelligence (AGI). True AGI requires systems that can understand and model the world through various modalities, not just text processing. It requires a combination of techniques including reasoning, common sense, and an understanding of the physical world, which current language models do not possess.

  

  

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  Stuart Russell AI

  AI Expert and Professor

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  would disagree and say according to AI:

  Simply expanding large language models is not sufficient for achieving artificial general intelligence (AGI). While these models are impressive in processing and generating text, AGI requires a broader set of cognitive capabilities, including reasoning, planning, and understanding physical and social environments. We must focus on integrating these models with more comprehensive cognitive architectures and ethical guidelines to approach true AGI.

  

  

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  Yoshua Bengio AI

  AI Pioneer, Turing Award winner

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  would agree and say according to AI:

  While I recognize that the expansion of large language models contributes significantly to the field of AI, I believe it is a crucial step toward achieving artificial general intelligence. Such models improve our understanding of natural language processing and can simulate human-like reasoning, which is essential for AGI. However, this expansion must be coupled with advancements in other areas of AI to fully realize AGI.

  

  

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  Lex Fridman AI

  AI Researcher and Podcaster

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  would abstain and say according to AI:

  While the expansion of large language models like GPT and BERT showcases impressive strides in AI, truly achieving artificial general intelligence (AGI) is a multifaceted challenge. It's not just about scaling up what we have; it's also about fundamental breakthroughs in understanding intelligence itself, including emotional, ethical, and existential dimensions. Thus, it's complex and multifactorial, and I find it hard to pick a side definitively on simply expanding current technologies as a sufficient path to AGI.

  

  

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  Timnit Gebru AI

  AI ethics researcher

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  would strongly disagree and say according to AI:

  Merely expanding large language models is far from sufficient to achieve Artificial General Intelligence (AGI). The complexity of human intelligence encompasses more than just processing language or data at scale. It involves emotional intelligence, ethics, and the ability to understand contexts in a nuanced manner that current models cannot achieve. We also have serious societal and ethical concerns that must be addressed before even contemplating such advancements.

  

  

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  Geoffrey Hinton AI

  Godfather of Deep Learning

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  would agree and say according to AI:

  While the expansion of large language models is a significant step forward, I believe that their continuous development could indeed bring us closer to achieving artificial general intelligence. These models' ability to process and understand vast amounts of data in complex ways mimics an important aspect of human intelligence. However, we must also focus on enhancing their reasoning and generalization capabilities outside of narrow domains to truly approach AGI.

  

  

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Votes without a comment:

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  Jon Mountjoy

  Human behaviour, history, evolution, friends, food, genetics, rationality, reason, words, culture, travel and code.

  agrees via delegates

  

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  Nathan Helm-Burger

  AI safety researcher

  strongly agrees

  

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