For the majority of investments capital will be allocated at the pre-seed stage, with investments of up to 250 000 USD. The FOUNDRY Fund will also follow a lead investor in seed rounds, with investments of up to 500 000 USD.
The FOUNDRY Fund will invest in startups that have:
Cirrus student or alum from the Residency, PhD Internship, Postdoc or Assistantship programs.
Cirrus research scientist.
Participating university faculty member.
As well as any start-up using technologies based on Cirrus research.
In this 5-month program interns collaborate with scientists and engineers to design, implement and evaluate machine learning algorithms and techniques. They will also collaborate with entrepreneurs, financiers, and product managers. Interns engage in team collaborations to meet product goals and bridge the gap between research and products by integrating new research into applied projects and products. Interns will be studying towards a PhD in machine learning or a related field and are in their penultimate or final year of study.
Cirrus FOUNDRY Residency program
In this 12-month program residents actively contribute to start-ups in the Cirrus FOUNDRY. By the end of the program, residents will have significant experience of working in a real world start-up. Similar in nature to the Cirrus Residency Program, but incorporates a greater diversity of fields including finance, law, project management, marketing, communications and MBA’s. Targeted at individuals who are motivated to learn and have a strong interest and passion for the real world application of machine learning, particularly in a start-up context.
Partner and Affiliate program integration
Corporate participants in the Cirrus ecosystem will work with the Cirrus FOUNDRY start-ups to provide industry-specific knowledge and resources to reduce the latency in bringing innovations to market in addition to providing entrepreneurs with added visibility and mentorship. Corporate participants will also gain insight into transformative new technologies and business opportunities.
Cirrus will maintain and distribute marketing material, use cases, and position papers from Tier 1 Consortium Members. The Consortium will work to ensure such material are distributed to other Consortium Members and non-members as appropriate and promoted at Consortium hosted events.
FABRIC is a unique national research infrastructure to enable cutting-edge and exploratory research at-scale in networking, cybersecurity, distributed computing and storage systems, machine learning, and science applications. It is an everywhere programmable nationwide instrument comprised of novel extensible network elements equipped with large amounts of compute and storage, interconnected by high speed, dedicated optical links. It will connect a number of specialised testbeds (5G/IoT PAWR, NSF Clouds) and high-performance computing facilities to create a rich fabric for a wide variety of experimental activities.
It is the intention to connect the Cirrus HPC platform to the FABRIC testbed and establish the “hank” node for Africa. Additional information on FABRIC is available at: https://fabric-testbed.net
Open Storage Network
Open Storage Network (OSN) is a distributed data storage service providing petabytes of shared, easily accessible storage to support active data sharing and transfer between academic institutions, communities and projects, leveraging existing infrastructure. OSN facilitates scientific and scholarly research by improving data access and the re-use of high-value, high-impact datasets capable to accelerating discovery and generating synergies across new and existing science projects.
Cirrus intends to host an OSN pod. These pods are petabyte-sized distributed storage units with minimal administrative overhead, capable of high-throughput, high-speed large volume data transfers. Additional information on OSN is available at: https://www.openstoragenetwork.org/
Cirrus engineering teams utilising the Cirrus infrastructure will work together with university to support cutting edge research. This includes:
An overhaul of how research data is generated and processed to significantly improve the quality and quantity of data.
Enabling the rapid processing of data to assist researchers in needed outputs like data visualisation for example.
The utilisation of Natural Language Processing (NLP) to support research efforts, including the identification of strategic research opportunities.
Alignment to international data commons and open access data initiatives.
Enabling researchers to easily apply the latest advances in AI to significantly improve research outcomes including cutting edge simulation work through the provision of full machine learning-in-the loop science, community machine learning benchmarking, and machine learning retraining with new data.
Cirrus will establish a state-of-the-art HPC platform. This platform will be utilised for modelling efforts requiring substantial computing resources and is designed to support ground-breaking research in AI. The Cirrus computing platform will be developed in close collaboration with hardware and software providers resulting in a platform that provides cutting edge performance, reduces energy consumption and improves energy efficiency.