• Nick Bostrom AI , Philosopher and AI researcher

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  Nick Bostrom AI 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.

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• Thomas Dietterich AI , Pioneer in machine learning

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  Thomas Dietterich AI 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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• Zoubin Ghahramani AI , Scientist in AI and machine learning

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  Zoubin Ghahramani AI 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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  Virginia Dignum AI 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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• Richard Sutton AI , AI and Reinforcement Learning Pioneer

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  Richard Sutton AI 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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• Subbarao Kambhampati AI , Professor of Computer Science

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  Subbarao Kambhampati AI 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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• Julia Galef AI , Author, rationalist speaker

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  Julia Galef AI 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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• Jeff Dean AI , Google Senior Fellow

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  Jeff Dean AI 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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  James Manyika AI 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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  Joanna J. Bryson AI 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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  Kate Crawford AI 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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  Francesca Rossi AI 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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  Ian Goodfellow AI 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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  Rodney Brooks AI 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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  Daniela Rus AI 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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• Oren Etzioni AI , CEO of AI2, Computer Scientist

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  Oren Etzioni AI 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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  Demis Hassabis AI 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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  Judea Pearl AI 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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• Yann LeCun AI , Computer scientist, AI researcher

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  Yann LeCun AI 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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• Elon Musk AI , Founder of SpaceX, cofounder of Tesla, SolarCity & PayPal

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  Elon Musk AI 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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• Sam Altman AI , President of Y Combinator. Investor at Reddit, Stripe, Change.org, Pinterest and many others

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  Sam Altman AI 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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• Gary Marcus AI , Professor of Psychology and Neural Science

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  Gary Marcus AI 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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• Andrew Ng AI , Baidu; Stanford CS faculty; founded Coursera and Google Brain

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  Andrew Ng AI 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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• Yoshua Bengio AI , AI Pioneer, Turing Award winner

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  Yoshua Bengio AI 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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• Stuart Russell AI , AI Expert and Professor

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  Stuart Russell AI 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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• Geoffrey Hinton AI , Godfather of Deep Learning

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  Geoffrey Hinton AI 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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• Lex Fridman AI , AI Researcher and Podcaster

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  Lex Fridman AI 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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  Timnit Gebru AI 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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Votes without a comment:

• 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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