Google Pathways (report)

An Exploration of the Pathways Architecture from PaLM to Parti

Alan D. Thompson
LifeArchitect.ai
August 2022
24 pages incl title page, references, appendices.

Updates to the Pathways family since publication (most recent at top)

Date	Model	Notes
13/Oct/2023	PaLI-3	PaLI-3: paper.
26/Jul/2023	Med-PaLM M	Med-PaLM Multimodal: paper.
22/Jun/2023	AudioPaLM	AudioPaLM = PaLM 2 + AudioLM: paper.
10/May/2023	PaLM 2	PaLM 2: announce.
29/May/2023	PaLI-X 55B	PaLI-X 55B: paper.
10/May/2023	PaLM 2	PaLM 2: announce.
12/Mar/2023	Med-PaLM 2	Med-PaLM 2: announce.
6/Mar/2023	PaLM-E	PaLM-E is PaLM Embodied with 562B params: paper, research site.
19/Jan/2023	–	Dr Jeff Dean provided extended commentary in his review of 2022: blog.
26/Dec/2022	Med-PaLM	Med-PaLM, a medical finetuned model based on Flan-PaLM: paper.
20/Oct/2022	Flan-PaLM	Flan-PaLM, based on Finetuning language models (Flan): paper.
20/Oct/2022	U-Palm	U-PaLM, a version of PaLM using less power/hours of compute: paper.
15/Sep/2022	PaLI 17B	PaLI 17B: Google Pathways Language and Image model: paper.
16/Aug/2022	PaLM-SayCan	PaLM + Robots: Google PaLM-SayCan: announce, research site, video.

Reviews
Received by several major governments; used in policy analysis.

Abstract

With over a million subscribed users, GPT-3 and related models have received a lot of press coverage and public attention. Much like a flashy Porsche driving down the Autobahn, these models look impressive, and are performing well. However, it is only a matter of time until they are overtaken by a much larger supercar. And that vehicle is already rapidly approaching. Google Pathways was announced at the end of 2021, and we are seeing several of its components in 2022: beginning with PaLM, PaLM-Coder, Parti, and Minerva. While all of these models are closed—only available for Google’s internal research—it is anticipated that a future Pathways model will be publicly released. This report explores the accomplishments of the Pathways models so far, with PaLM and its related language models already at more than triple the size of GPT-3.

Contents

1. Overview
1. Google Pathways (Oct/2021)
2. Google Pathways: The Pathways System (Mar/2022)
3. Google Pathways: PaLM 540B (Apr/2022)
3.1. PaLM Dataset Summary
3.2. PaLM Capabilities & Performance
4. Google Pathways: PaLM-Coder 540B (Apr/2022)
5. Google Pathways: Parti 20B (Jun/2022)
6. Google Pathways: Minerva 540B (Jun/2022)
6.1. The Polish National Math Exam
7. Following the Trail to Transformative AI
8. Further reading
Appendix A: PaLM 540B vs GPT-3 175B vs Jurassic-1 178B vs human

Videos

1. PaLM 540B (Apr/2022)

2. Parti 20B (Jun/2022)

3. Report card referencing PaLM

Images (selected)

References, Further Reading, and How to Cite

To cite this report:

Thompson, A. D. (2022). Google Pathways: An Exploration of the Pathways Architecture from PaLM to Parti. https://LifeArchitect.ai/pathways

Chowdhery, A., Narang, S., Devlin, J., Bosma, M., Mishra, G., Roberts, A., Barham, P., Chung, H. W., Sutton, C., Gehrmann, S., Schuh, P., Shi, K., Tsvyashchenko, S., Maynez, J., Rao, A., Barnes, P., Tay, Y., Shazeer, N., Prabhakaran, V., Reif, E., Du, N., Hutchinson, B., Pope, R., Bradbury, J., Austin, J., Isard, M., Gur-Ari, G., Yin, P., Duke, T., Levskaya, A., Ghemawat, S., Dev, S., Michalewski, H., Garcia, X., Misra, V., Robinson, K., Fedus, L., Zhou, D., Ippolito, D., Luan, D., Lim, H., Zoph, B., Spiridonov, A., Sepassi, R., Dohan, D., Agrawal, S., Omernick, M., Dai, A. M., Pillai, T. S., Pellat, M., Lewkowycz, A., Moreira, E., Child, R., Polozov, O., Lee, K., Zhou, Z., Wang, X., Saeta, B., Diaz, M., Firat, O., Catasta, M., Wei, J., Meier-Hellstern, K., Eck, D., Dean, J., Petrov, S., and Fiedel, N. (2022). PaLM: Scaling Language Modeling with Pathways. https://arxiv.org/abs/2204.02311

Parti paper

Yu, J., Xu, Y., Koh, J. Y., Luong, T., Baid, G., Wang, Z., Vasudevan, V., Ku, A., Yang, Y., Ayan, B. K., Hutchinson, B., Han, W., Parekh, Z., Li, X., Zhang, H., Baldridge, J., & Wu, Y. Scaling Autoregressive Models for Content-Rich Text-to-Image Generation. https://arxiv.org/abs/2206.10789

Parti demo

Google. (2022). https://parti.research.google/

Minerva announcement (Minerva blog)

Dyer, E., & Gur-Ari, G. (2022). Minerva: Solving Quantitative Reasoning Problems with Language Models.

https://ai.googleblog.com/2022/06/minerva-solving-quantitative-reasoning.html

Minerva paper

Lewkowycz, A., Andreassen, A., Dohan, D., Dyer, E., Michalewski, H., Ramasesh, V., Slone, A., Anil, C., Schlag, I., Gutman-Solo, T., Wu, Y., Neyshabur, B., Gur-Ari, G., & Misra, V. (2022). Solving Quantitative Reasoning Problems with Language Models. https://arxiv.org/abs/2206.14858

Minerva sample demo

Google. (2022). https://minerva-demo.github.io/

Image credit: Thanks to jesssaysno for the header image on this page.

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Dr Alan D. Thompson is an AI expert and consultant, advising Fortune 500s and governments on post-2020 large language models. His work on artificial intelligence has been featured at NYU, with Microsoft AI and Google AI teams, at the University of Oxford’s 2021 debate on AI Ethics, and in the Leta AI (GPT-3) experiments viewed more than 4.5 million times. A contributor to the fields of human intelligence and peak performance, he has held positions as chairman for Mensa International, consultant to GE and Warner Bros, and memberships with the IEEE and IET. Technical highlights.

This page last updated: 16/Oct/2023. https://lifearchitect.ai/pathways/↑

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