Conference: NeST: Neuromorphic Stochastic Thermodynamics Workshop at SFI
- Institution
- Santa Fe Institute, NM
- Principal investigator
- David Wolpert
- Funding
- $49K
- Duration
- 2025–2026
Moonbase score
Still being scored
Abstract
A workshop is proposed to examine the intersection of neuromorphic computing and stochastic thermodynamics. Neuromorphic Computing is a field that started decades ago, inspired by the efficiencies of the information processing performed by biological brains. Its main goal is to replicate the complex architecture and functionality of biological neural circuits but using in-silico circuits. The field has played a key role in advancing artificial intelligence (AI) systems as evidenced by the adoption of neuromorphic concepts like compute-in-memory, attention, pooling to name a few, into the mainstream AI designs. However, a detailed comparison between in-silico neuromorphic brains and biological brains reveals a significant gap between the two systems. Even a simple insect brain with fewer than a million neurons can perform and learn a variety of complex tasks, a feat currently unachievable by state-of-the-art AI systems, let alone a neuromorphic computer. On the other end of the spectrum are large-scale AI systems, such as large language models (LLMs) and vision transformers, whose success has been characterized by a rapid increase in the complexity and the size of their flowcharts involving various abstract processes. The energy cost for training and using these AI systems is becoming unsustainable, as the field strives to achieve artificial general intelligence (AGI) or brain-scale intelligence. It is To address this above-mentioned energy challenge, the scientific community needs a fundamental understanding of the thermodynamics of distributed computational architectures, particularly how energy expenditure varies across different architectures that implement the same computational task. In this regard, the planned workshop will lead to a new body of knowledge and new research directions that will synergize the field of neuromorphic engineering/computing with the latest advances in the field of stochastic thermodynamics. It is hoped that the workshop will produce a new direction and will thus help NSF reformulate its programs according to the needs of scientific disciplines as well as emerging technologies. The workshop will produce reports to be made broadly available to the community. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Research team
- David WolpertPI
- Shantanu Chakrabartty
LOADING MOONBASE SCORE
Questions for Santa Fe Institute
Answered by the team behind this research.
No questions yet. Sign in to ask the first one
Related grants
Same researchers, same institution, same topic, scored first.
- NSF · Santa Fe InstituteNot yet scored
FET: Thermodynamic effects of network topologies in distributed computers
David Wolpert · $697K · 2026–2029
- NSF · Washington UniversityNot yet scored
NSF Convergence Accelerator track L: Translating insect olfaction principles into practical and robust chemical sensing platforms
Baranidharan Raman · $650K · 2024–2025
- NSF · Washington UniversityNot yet scored
FuSe2 Topic 1: One-Shot PetaOps/W Analog Margin-Propagation Compute Paradigm Advancing RF-MIMO Radar Processing and Classification
Aravind Nagulu · $1.9M · 2024–2025