Ursa Major, the cloud for research, offers a wide range of cutting-edge AI and ML services to support your research. With its cloud-based infrastructure, you can access advanced tools, including machine learning algorithms, data analysis tools, and big data analytics, without buying hardware. Collaborate with team members from anywhere in the world, tackle large-scale projects, and manage your data with ease. Enjoy the benefits of cloud computing, including access to massive computing resources, with Google Cloud's security controls. Under current terms, AI model access, exotic hardware not available on campus, and archive storage are campus-supported (Tier 1); other services are recharged. See KB005.
Reach out to the Research Computing team to help you get your lab up and running today. research-computing@ucr.edu
Access to Advanced Tools:
With Ursa Major and its AI and ML services, researchers can access a wide range of cutting-edge tools and technologies to support their research. This includes advanced machine learning algorithms, cloud-based computing resources, and state-of-the-art data analysis tools.
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A researcher in the field of genetics could use Ursa Major to access advanced machine learning algorithms and data analysis tools to study the genetic causes of diseases. This would enable them to process and analyze large amounts of genetic data and create models that could help in early detection and treatment of diseases.
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A researcher in the field of computer vision could use Ursa Major's cloud-based infrastructure to access state-of-the-art computer vision algorithms and tools. This would enable them to develop and test advanced image and video recognition systems, helping in fields such as autonomous vehicles, security systems, and medical imaging.
Costs
Under current terms, three Ursa Major areas carry no recharge to the lab, within limits: AI model access for research (with a per-lab allowance), exotic hardware not available on the HPCC, and archive storage. Other cloud services, including the analytics, data management and machine learning platforms described on this page, are recharged to a lab funding source. Cloud can avoid up-front hardware purchases, but usage costs add up over time. See KB005: Ursa Major service tiers and compare with the HPCC for long-running work.
Scalability:
Ursa Major's infrastructure is highly scalable, allowing researchers to increase or decrease their computing resources as needed. This makes it possible for researchers to tackle large, complex research projects without worrying about running out of resources or needing to invest in new hardware.
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A researcher in the field of physics could use Ursa Major's infrastructure to increase or decrease their computing resources as needed. This would enable them to tackle large, complex simulations and simulations of particle interactions without worrying about running out of resources or needing to invest in new hardware.
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A researcher in the field of economics could use Ursa Major's infrastructure to scale up or down their computing resources as needed. This would enable them to tackle large, complex models and simulations of economic systems without worrying about running out of resources or needing to invest in new hardware.
Collaboration:
Ursa Major's cloud-based infrastructure makes it easier for researchers to collaborate and share their work with other team members, regardless of their location. This enables researchers to work together on large-scale projects, share data and results, and collaborate on new ideas and theories.
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A researcher in the field of sociology could use Ursa Major's cloud-based infrastructure to collaborate with other team members, regardless of their location. This would enable them to work together on large-scale projects, share data and results, and collaborate on new ideas and theories.
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A researcher in the field of engineering could use Ursa Major's cloud-based infrastructure to collaborate with other team members, regardless of their location. This would enable them to work together on large-scale projects, share data and results, and collaborate on new ideas and technologies.
Data Management:
Ursa Major provides researchers with advanced data management tools, including Big Data analytics and storage solutions. This enables researchers to collect, store, and analyze massive amounts of data, making it easier to uncover new insights and find new solutions to complex problems.
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A researcher in the field of medicine could use Ursa Major's data management tools to collect, store, and analyze massive amounts of patient data, making it easier to uncover new insights and find new solutions to complex medical problems.
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A researcher in the field of finance could use Ursa Major's data management tools to collect, store, and analyze massive amounts of financial data, making it easier to uncover new insights and find new solutions to complex financial problems.
Machine Learning:
Ursa Major offers a wide range of machine learning algorithms and tools, including advanced machine learning libraries. Researchers can leverage these tools to create advanced models and algorithms, making it easier to automate complex processes and make more accurate predictions.
- Material Science: A researcher at a major research university could use machine learning algorithms to develop new materials. For example, they could use algorithms to optimize the composition and structure of new materials to improve their mechanical properties and thermal stability.
- Psychology: A researcher could use machine learning algorithms to analyze large amounts of data collected from psychological experiments. For example, they could use algorithms to detect patterns in the data that are related to specific mental health disorders, making it easier to diagnose and treat patients.
Big Data Analytics:
Ursa Major provides researchers with access to powerful Big Data analytics tools, including advanced analytics platforms. This enables researchers to quickly analyze large amounts of data and uncover new insights, making it easier to make informed decisions and find new solutions to complex problems.
- Natural Sciences: A researcher could use big data analytics to study the effects of climate change on ecosystems. For example, they could analyze large amounts of data collected from environmental sensors to understand how different species are affected by changes in temperature, precipitation, and other environmental factors.
- Psychology: A researcher could use big data analytics to study the development of mental health disorders. For example, they could analyze large amounts of data collected from surveys and questionnaires to understand how different factors, such as genetics, environment, and life events, contribute to the development of mental health disorders.
Access to Large Data Sets:
Ursa Major's cloud-based infrastructure provides researchers with access to massive data sets, including open-source data sets and proprietary data sets. This makes it easier for researchers to collect and analyze data, uncover new insights, and find new solutions to complex problems.
- Material Science: A researcher could use access to large data sets to study the properties of materials. For example, they could use open-source data sets to understand how different materials respond to different loads and stresses, making it easier to develop new materials with improved properties.
- Natural Sciences: A researcher could use access to large data sets to study the evolution of species. For example, they could use proprietary data sets to understand how species have evolved over time, making it easier to predict future changes and protect endangered species.
Security
Google Cloud provides encryption, access control and data governance tools. Researchers are responsible for configuring them for their data, and sensitive data needs a review before it is stored. See Security and Data.