TPC Hackathons offer opportunities to drive collaboration. TPC26 hackathon activities will all address one or more of these six goals:

Collectively build a scientific training data resource and shared infrastructure that can be used for model training and fine-tuning (general purpose FM, domain-specific FM, etc.

Build a frontier-scale, open AI model (using data from 1), harnessing the computational and data resources at many TPC partner institutions. All aspects of the model (data, weights, etc.) will be open.

Drive development and creation of Frontier AI system for science that incorporates reasoning models (start with SOA closed models, eventually include Open frontier model) and develops domain foundation models, knowledge graphs, orchestrations, simulators and experiments.

Develop software infrastructure and middleware for building complex frontier-scale AI models and systems (This is in support of 2 & 3, also integrating experimentation / labs / instruments and other real-world connections)

Develop an open suite of tools, methods, and benchmarks for evaluating the scientific skills, knowledge, reasoning, agentic capabilities and safety/security of Frontier Models and AI systems.

Identify challenge applications for driving and evaluating (1) - (3). Not centrally picking winners and losers but asking the community to volunteer (and drive) scientific challenge applications, aiming for diversity on multiple axes (including industry applications)
TPC26 will be soliciting hackathon team projects soon. More details will be forthcoming in the coming weeks.
are open to TPC members and invited guests.