The Nonlinear Library EA - Some more marginal Long-Term Future Fund grants by calebp
Nov 16, 2023
09:49
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Some more marginal Long-Term Future Fund grants, published by calebp on November 16, 2023 on The Effective Altruism Forum.
These fictional grants represent the most promising applications we turn down due to insufficient funding.
Throughout the text, 'I' refers to Caleb Parikh, and 'we' refers to both Caleb Parikh and Linch Zhang. This reflects the perspectives of two individuals who are very familiar with the Long-Term Future Fund (LTFF). However, others associated with the LTFF might not agree that this accurately represents their impression of the LTFF's marginal (rejected) grants.
Fictional grants that we rejected but were very close to our funding bar
Each grant is based on 1-3 real applications we have received in the past ~three months. You can see our original LTFF marginal funding post here, and our post on the usefulness of funding the EAIF and LTFF here.[1] Please note that these are a few of the most promising grants we've recently turned down - not the average rejected grant. [2]
($25,000)~ Funding to continue research on a multi-modal chess language model, focusing on alignment and interpretability. The project involves optimizing a data extraction pipeline, refining the model's behaviour to be less aggressive, and exploring ways to modify the model training. Additional tasks include developing a simple Encoder-Decoder chess language model as a benchmark and writing an article about AI safety.
The primary objective is to develop methods ensuring that multi-modal models act according to high-level behavioural priorities. The applicant's background includes experience as a machine learning engineer and chess, competing and developing predictive models. The past year's work under a previous LTFF grant resulted in a training dataset and some initial analysis, laying the groundwork for this continued research.
($25,000) ~ Four months' salary for a former academic to tackle some unusually tractable research problems in disaster resilience after large-scale GCRs. Their work would focus on researching Australia's resilience to a northern hemisphere nuclear war. Their track record included several papers in high-impact factor journals, and their past experiences and networks made them well-positioned for further work in this area. The grantee would also work on public outreach to inform the Australian public about nuclear risks and resilience strategies.
($50,000)~ Six months of career transition funding to help the applicant enter a technical AI safety role. The applicant has seven years of software engineering experience at prominent tech companies and aims to pivot his career towards AI safety. They'll focus on interpretability experiments with Leela Go Zero during the grant.
The grant covers 50% of his previous salary and will facilitate upskilling in AI safety, completion of technical courses, and preparation for interviews with AI safety organizations. He has pivoted his career successfully in the past and has been actively engaged in the effective altruism community, co-running a local group and attending international conferences. This is his first funding request.
($40,000)~ Six months dedicated to exploring and contributing to AI governance initiatives, focusing on policy development and lobbying in Washington, D.C. The applicant seeks to build expertise and networks in AI governance, aiming to talk with over 50 professionals in the field and apply to multiple roles in this domain. The grant will support efforts to increase the probability of the U.S. government enacting legislation to manage the development of frontier AI technologies.
The applicant's background includes some experience in AI policy and a strong commitment to effective altruism principles. The applicant has fewer than three years of professional experience and an undergraduate degree ...
These fictional grants represent the most promising applications we turn down due to insufficient funding.
Throughout the text, 'I' refers to Caleb Parikh, and 'we' refers to both Caleb Parikh and Linch Zhang. This reflects the perspectives of two individuals who are very familiar with the Long-Term Future Fund (LTFF). However, others associated with the LTFF might not agree that this accurately represents their impression of the LTFF's marginal (rejected) grants.
Fictional grants that we rejected but were very close to our funding bar
Each grant is based on 1-3 real applications we have received in the past ~three months. You can see our original LTFF marginal funding post here, and our post on the usefulness of funding the EAIF and LTFF here.[1] Please note that these are a few of the most promising grants we've recently turned down - not the average rejected grant. [2]
($25,000)~ Funding to continue research on a multi-modal chess language model, focusing on alignment and interpretability. The project involves optimizing a data extraction pipeline, refining the model's behaviour to be less aggressive, and exploring ways to modify the model training. Additional tasks include developing a simple Encoder-Decoder chess language model as a benchmark and writing an article about AI safety.
The primary objective is to develop methods ensuring that multi-modal models act according to high-level behavioural priorities. The applicant's background includes experience as a machine learning engineer and chess, competing and developing predictive models. The past year's work under a previous LTFF grant resulted in a training dataset and some initial analysis, laying the groundwork for this continued research.
($25,000) ~ Four months' salary for a former academic to tackle some unusually tractable research problems in disaster resilience after large-scale GCRs. Their work would focus on researching Australia's resilience to a northern hemisphere nuclear war. Their track record included several papers in high-impact factor journals, and their past experiences and networks made them well-positioned for further work in this area. The grantee would also work on public outreach to inform the Australian public about nuclear risks and resilience strategies.
($50,000)~ Six months of career transition funding to help the applicant enter a technical AI safety role. The applicant has seven years of software engineering experience at prominent tech companies and aims to pivot his career towards AI safety. They'll focus on interpretability experiments with Leela Go Zero during the grant.
The grant covers 50% of his previous salary and will facilitate upskilling in AI safety, completion of technical courses, and preparation for interviews with AI safety organizations. He has pivoted his career successfully in the past and has been actively engaged in the effective altruism community, co-running a local group and attending international conferences. This is his first funding request.
($40,000)~ Six months dedicated to exploring and contributing to AI governance initiatives, focusing on policy development and lobbying in Washington, D.C. The applicant seeks to build expertise and networks in AI governance, aiming to talk with over 50 professionals in the field and apply to multiple roles in this domain. The grant will support efforts to increase the probability of the U.S. government enacting legislation to manage the development of frontier AI technologies.
The applicant's background includes some experience in AI policy and a strong commitment to effective altruism principles. The applicant has fewer than three years of professional experience and an undergraduate degree ...