Re: Large Language Models and AI reaching singularity as warned

Milton,

I would like to express hope and optimism with respect to the recent developments in AI.

Regarding "the emergence of capabilities" as large language models scale [8], there exist best scientific approaches to investigating the capabilities of these systems. I would propose advancing our scientific methodologies as pertaining to the "psychometric assessment" of AI systems, in general. Perhaps scientists want to better model questions and testlets intended for AI systems to better understand resultant data. In these regards, I'm generally considering the advancement of methodological approaches to "psychometrically assessing" AI systems and to interpreting pertinent results.

Presently, there are scattered, distributed, decentralized, approaches to QA datasets. I provide, for example, some references [1][2][3][5][6][7][9] on the topics of QA datasets pertaining to machine reading comprehension and story understanding. You might also find interesting [4], where "emergent theory of mind" would pertain to both artificial story comprehension and artificial social cognition.


Best regards,
Adam


[1] Choi, Seongho, Kyoung-Woon On, Yu-Jung Heo, Ahjeong Seo, Youwon Jang, Minsu Lee, and Byoung-Tak Zhang. "DramaQA: Character-centered video story understanding with hierarchical QA." In Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, no. 2, pp. 1166-1174. 2021.

[2] Huang, Lifu, Ronan Le Bras, Chandra Bhagavatula, and Yejin Choi. "Cosmos QA: Machine reading comprehension with contextual commonsense reasoning." arXiv preprint arXiv:1909.00277 (2019).

[3] Kočiský, Tomáš, Jonathan Schwarz, Phil Blunsom, Chris Dyer, Karl Moritz Hermann, Gábor Melis, and Edward Grefenstette. "The narrativeQA reading comprehension challenge." Transactions of the Association for Computational Linguistics 6 (2018): 317-328.

[4] Kosinski, Michal. "Theory of mind may have spontaneously emerged in large language models." arXiv preprint arXiv:2302.02083 (2023).

[5] Sap, Maarten, Hannah Rashkin, Derek Chen, Ronan LeBras, and Yejin Choi. "SocialIQa: Commonsense reasoning about social interactions." arXiv preprint arXiv:1904.09728 (2019).

[6] Talmor, Alon, and Jonathan Berant. "MultiQA: An empirical investigation of generalization and transfer in reading comprehension." arXiv preprint arXiv:1905.13453 (2019).

[7] Tapaswi, Makarand, Yukun Zhu, Rainer Stiefelhagen, Antonio Torralba, Raquel Urtasun, and Sanja Fidler. "MovieQA: Understanding stories in movies through question-answering." In Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 4631-4640. 2016.

[8] Wei, Jason, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama et al. "Emergent abilities of large language models." arXiv preprint arXiv:2206.07682 (2022).

[9] Xu, Ying, Dakuo Wang, Mo Yu, Daniel Ritchie, Bingsheng Yao, Tongshuang Wu, Zheng Zhang et al. "Fantastic questions and where to find them: FairytaleQA -- An authentic dataset for narrative comprehension." arXiv preprint arXiv:2203.13947 (2022).

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From: ProjectParadigm-ICT-Program <metadataportals@yahoo.com>
Sent: Friday, March 17, 2023 6:20 PM
To: W3C AIKR CG <public-aikr@w3.org>; Public-cogai <public-cogai@w3.org>; semantic-web <semantic-web@w3.org>
Subject: Large Language Models and AI reaching singularity as warned

There are now in the hundreds of articles about LLMs, ML and AI reaching tipping points beyond which we lose control.

This one is one of the most striking and warrants action.

https://www.quantamagazine.org/the-unpredictable-abilities-emerging-from-large-ai-models-20230316/

But it is this that is really sounding the alarms for scientists and AI and industry experts in numerous sectors.

https://techcrunch.com/2023/03/13/microsoft-lays-off-an-ethical-ai-team-as-it-doubles-down-on-openai/

https://gizmodo.com/microsoft-ai-ethical-ai-bing-chatgpt-layoffs-1850223358

And since the Silicon Valley Bank failure  has sent ripples through the entire global startup ecosystems community, more money will be pouring into a frenzied market of AI applications, where AI will become the new panacea for helping solve global problems, leading to much bigger problems than the current hiccups in the global financial markets.


Milton Ponson
GSM: +297 747 8280
PO Box 1154, Oranjestad
Aruba, Dutch Caribbean
Project Paradigm: Bringing the ICT tools for sustainable development to all stakeholders worldwide through collaborative research on applied mathematics, advanced modeling, software and standards development

Received on Friday, 17 March 2023 23:02:04 UTC