[Federal Register Volume 89, Number 177 (Thursday, September 12, 2024)]
[Notices]
[Pages 74268-74270]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2024-20676]


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DEPARTMENT OF ENERGY


Notice of Request for Information (RFI) on Frontiers in AI for 
Science, Security, and Technology (FASST) Initiative

AGENCY: Office of Critical and Emerging Technologies, Department of 
Energy.

ACTION: Request for information (RFI).

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SUMMARY: The Department of Energy's Office of Critical and Emerging 
Technologies (CET) seeks public comment to inform how DOE and its 17 
national laboratories can leverage existing assets to provide a 
national AI capability for the public interest.

DATES: Responses to the RFI are requested by November 11, 2024.

ADDRESSES: Interested parties may submit comments electronically to 
<a href="/cdn-cgi/l/email-protection#6026213333342008114e040f054e070f16"><span class="__cf_email__" data-cfemail="2e686f7d7d7a6e465f004a414b00494158">[email protected]</span></a> and include ``FASST RFI'' in the subject line of the 
email.

FOR FURTHER INFORMATION CONTACT: Further questions may be addressed to 
Charles Yang through <a href="/cdn-cgi/l/email-protection#397f786a6a6d795148175d565c175e564f"><span class="__cf_email__" data-cfemail="e5a3a4b6b6b1a58d94cb818a80cb828a93">[email protected]</span></a> or (202) 586-6116.

SUPPLEMENTARY INFORMATION:

I. Background

    This is an RFI issued by the U.S. Department of Energy's (DOE) 
Office of Critical and Emerging Technologies (CET). This RFI seeks 
public input to inform our ongoing work and DOE's proposed Frontiers in 
AI for Science, Security, and Technology (FASST) initiative,\1\ which 
seeks to build the world's most powerful, integrated scientific AI 
models for scientific discovery, applied energy deployment, and 
national security applications.
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    \1\ www.energy.gov/fasst.
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    DOE seeks input from:

<bullet> Academic institutions interested in partnering with DOE to 
leverage AI for scientific research
<bullet> For-profit and non-profit AI developers and research labs
<bullet> Data center and compute infrastructure providers
<bullet> Startups and investors
<bullet> Small businesses involved in the development or provision of 
AI technologies and services
<bullet> Civil society organizations potentially impacted by AI
<bullet> Labor training and technical workforce development 
organizations
<bullet> Think tanks and research organizations
<bullet> And other interested entities

II. Purpose

    FASST is DOE's proposed initiative to build the world's most 
powerful, integrated scientific AI systems. This initiative leverages 
DOE's demonstrated history of capability building for the U.S. 
government, as well as key enabling infrastructure already housed at 
the DOE's Office of Science and Applied Energy facilities, and 
facilities operated by National Nuclear Security Administration (NNSA), 
including:
    <bullet> Data: DOE is the leading generator of classified and 
unclassified scientific data through the world's largest collection of 
advanced experimental facilities, including particle accelerators, 
powerful light sources, specialized facilities for genomics and 
nanoscience, and neutron scattering sources.
    <bullet> Computing Infrastructure: For decades, DOE has built and 
operated the world's fastest, most powerful, and highly energy 
efficient supercomputers. These supercomputers are strategic components 
of the nation's defensive capabilities, drive innovation through open 
access to the scientific community, and are the basis upon which to 
build safe and trustworthy AI capability for the nation.
    <bullet> Workforce: DOE and its national labs host over 40,000 
physicists, chemists, biologists, materials scientists, and computer 
scientists, who tackle some of the most urgent challenges in the 
national interest.
    <bullet> Partnerships: DOE has unparalleled experience in mission-
driven public-private collaborations. Through the Exascale Computing 
Project, DOE worked with industry partners to co-design and develop 
critical components of the computer chips that power today's leading AI 
models and partnered with leading academic institutions to develop 
scalable high-performance software libraries.
    This RFI seeks public input to inform how DOE can partner with 
outside institutions and leverage its assets to implement and develop 
the roadmap for FASST, based on the four pillars of FASST: AI-ready 
data; Frontier-Scale AI Computing Infrastructure and Platforms; Safe, 
Secure, and Trustworthy AI Models and Systems; and AI Applications; as 
well as considerations for workforce and FASST governance.

[[Page 74269]]

III. Questions

1. Data

    (a) What kinds of data governance practices, risks, and 
opportunities should DOE take into consideration, particularly for open 
sourcing scientific corpuses to the community or interested parties?
    (b) What types of scientific and energy data should DOE prioritize 
for large-scale tokenization?
    (c) Are there partner organizations with relevant scientific or 
energy-related data that DOE should work with?
    (d) What are additional data-related tools and technologies DOE 
should invest in to promote AI-ready data and fuel continued US 
leadership in AI?

2. Compute

    (a) How can DOE ensure FASST investments support a competitive 
hardware ecosystem and maintain American leadership in AI compute, 
including through DOE's existing AI and high-performance-computing 
testbeds? \2\
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    \2\ www.energy.gov/cet/artificial-intelligence-testbeds-doe.
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    (b) How can DOE improve awareness of existing allocation processes 
for DOE's AI-capable supercomputers and AI testbeds for smaller 
companies and newer research teams? \3\ How should DOE evaluate compute 
resource allocation strategies for large-scale foundation-model 
training and/or other AI use cases?
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    \3\ https://science.osti.gov/ascr/Facilities/Accessing-ASCR-Facilities.
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    (c) How can DOE continue to support development of energy-efficient 
AI hardware, algorithms, and platforms?
    (d) How can DOE continue to support the development of AI hardware, 
algorithms, and platforms tailored for science and engineering 
applications in cases where the needs of those applications differ from 
the needs of commodity AI applications? How can DOE partner with other 
compute capability providers, including both on-premises and cloud 
solution providers, to support various hardware technologies and 
provide a portfolio of compute capabilities for its mission areas?

3. Models

    (a) How should DOE consider the benefits of open sourcing of 
scientific and applied energy AI models for the scientific community 
while fully addressing research security and other national-security 
concerns?
    (b) How can DOE support investment and innovation in energy 
efficient AI model architectures and deployment, including potentially 
through prize-based competitions?
    (c) What considerations should inform DOE's ongoing AI red-teaming 
and safety tests, particularly for Chemical, Biological, Radiological 
and Nuclear (CBRN) risks?

4. Applications

    (a) What are application areas in science, applied energy, and 
national security that are primed for AI breakthroughs?
    (b) How can DOE ensure foundation AI models are effectively 
developed to realize breakthrough applications, in partnership with 
industry, academia, and other agencies?

5. Workforce

    (a) DOE has an inventory of AI workforce training programs underway 
through our national labs.\4\ What other partnerships or convenings 
could DOE host or develop to support an AI ready scientific workforce 
in the United States?
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    \4\ www.energy.gov/cet/supercharging-americas-ai-workforce.
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6. Governance

    (a) How can DOE effectively engage and partner with industry and 
civil society? What are convenings, organizational structures, and 
engagement mechanisms that DOE should consider for FASST?
    (b) What role should public-private partnerships play in FASST? 
What problems or topics should be the focus of these partnerships?

IV. Response Guidelines

    Commenters are welcome to comment on any question. RFI responses 
shall include:
    1. RFI title;
    2. Name(s), phone number(s), and email address(es) for the 
principal point(s) of contact;
    3. Institution or organization affiliation and postal address; and
    4. Clear indication of the specific question(s) to which you are 
responding.
    Responses to this RFI must be submitted electronically to 
<a href="/cdn-cgi/l/email-protection#377176646463775f461953585219505841"><span class="__cf_email__" data-cfemail="377176646463775f461953585219505841">[email protected]</span></a> with the subject line ``FASST RFI'' no later than 5:00 
p.m. (ET) on November 11, 2024. Responses must be provided as 
attachments to an email. It is recommended that attachments with file 
sizes exceeding 25 MB be compressed (i.e., zipped) to ensure message 
delivery. Responses must be provided as a Microsoft Word (*.docx) or 
Adobe Acrobat (*.pdf) attachment to the email and should be no more 
than 15 pages in length, 12-point font, 1-inch margins. Only electronic 
responses will be accepted. Only one response per individual or 
organization will be accepted.
    A response to this RFI will not be viewed as a binding commitment 
to develop or pursue the project or ideas discussed. DOE may engage in 
post-response conversations with interested parties.

Confidential Business Information

    Because information received in response to this RFI may be used to 
structure future programs and/or otherwise be made available to the 
public, respondents are strongly advised NOT to include any information 
in their responses that might be considered business sensitive, 
proprietary, or otherwise confidential.
    Pursuant to 10 CFR 1004.11, any person submitting information that 
he or she believes to be confidential and exempt by law from public 
disclosure should submit via email two well-marked copies: one copy of 
the document marked ``confidential'' including all the information 
believed to be confidential, and one copy of the document marked ``non-
confidential'' with the information believed to be confidential 
deleted. Failure to comply with these marking requirements may result 
in the disclosure of the unmarked information under the Freedom of 
Information Act or otherwise. The U.S. Government is not liable for the 
disclosure or use of unmarked information and may use or disclose such 
information for any purpose. If your response contains confidential, 
proprietary, or privileged information, you must include a cover sheet 
marked as follows identifying the specific pages containing 
confidential, proprietary, or privileged information:

Notice of Restriction on Disclosure and Use of Data

    Pages [list applicable pages] of this response may contain 
confidential, proprietary, or privileged information that is exempt 
from public disclosure. Such information shall be used or disclosed 
only for the purposes described in this RFI. The Government may use or 
disclose any information that is not appropriately marked or otherwise 
restricted, regardless of source.
    In addition, (1) the header and footer of every page that contains 
confidential, proprietary, or privileged information must be marked as 
follows: ``Contains, Confidential, Proprietary, or Privileged 
Information Exempt from Public Disclosure'' and (2) every line and

[[Page 74270]]

paragraph containing proprietary, privileged, or trade secret 
information must be clearly marked with [[double brackets]] or 
highlighting. Submissions containing CBI should be sent to: 
<a href="/cdn-cgi/l/email-protection#266067757572664e570842494308414950"><span class="__cf_email__" data-cfemail="bdfbfceeeee9fdd5cc93d9d2d893dad2cb">[email protected]</span></a>.

Signing Authority

    This document of the Department of Energy was signed on September 
6, 2024, by Helena Fu, Director, Office of Critical and Emerging 
Technologies, pursuant to delegated authority from the Secretary of 
Energy. That document with the original signature and date is 
maintained by DOE. For administrative purposes only, and in compliance 
with requirements of the Office of the Federal Register, the 
undersigned DOE Federal Register Liaison Officer has been authorized to 
sign and submit the document in electronic format for publication, as 
an official document of the Department of Energy. This administrative 
process in no way alters the legal effect of this document upon 
publication in the Federal Register.

    Signed in Washington, DC, on September 9, 2024.
Treena V. Garrett,
Federal Register Liaison Officer, U.S. Department of Energy.
[FR Doc. 2024-20676 Filed 9-11-24; 8:45 am]
BILLING CODE 6450-01-P


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