A recipe for trustworthy artificial intelligence |
Recently, a group of tech industry leaders issued an open letter warning of the looming threats posed by artificial intelligence (AI), comparing them to the risk of "pandemics and nuclear war."
The open letter is just one of many recent attempts to draw attention to situations in which AI cannot be trusted and to raise questions about AI’s potential unfair or harmful effects.
Researchers at Notre Dame are working alongside technology experts within the U.S. military as well as with researchers at Indiana University – Purdue University Indianapolis (IUPUI) and Indiana University, are developing in a comprehensive, systematic approach to creating trustworthy AI. The project, called "Trusted AI" aims to ask a slightly different question: What would it look like to develop artificial intelligence we can trust? Read more.
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The Software Development team concluded work on the Additive with Knowledge (AWK) research project, led by Principal Investigator Christopher Sweet. The CRC and industry partner SIMBA sought to address the significant barriers that exist to production of repair parts and components produced using additive manufacturing methods. Notably, the research used machine learning and knowledge graph approaches to recommend an additive manufacturing printer based on an arbitrary part’s dimensions and specific material requirements. The software team worked on the Continuous Integration (CI) pipeline to operationalize training and exporting a Neural Network model and additionally developed a GraphQL API interface to interact with the trained classification model.
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CIRE celebrates thirteen 2023 graduates |
Thirteen student investigators with the Cyber Crimes Unit of the Cybercrimes Investigation, Research, and Education (CIRE) Initiative graduated during the 2023 Commencement Weekend. Each of these students has worked in the unit for multiple years and collectively investigated over 1000 cases and examined over 2000 digital devices.
“The work that these students do is incredible,” says Mitch Kajzer, managing director of the CIRE Initiative. “Their dedication and analytical skills have made a significant impact on investigations in the area. They will be missed as they move on to the next chapter of their lives.”
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The day after commencement, CIRE welcomed the first of 13 new Student Investigators. Five of the student investigators will being this summer and work full-time. Eight additional investigators will join them in the Fall. There will be a total of 21 Student Investigators working next academic year.
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Running Jupyter Notebooks via SSH Tunneling |
Jupyter Notebooks have become an indispensable tool for data scientists and researchers, offering an interactive and collaborative environment for data exploration, visualization, and analysis. However, when working with remote servers or sensitive data, it is crucial to ensure secure access to Jupyter Notebooks. One widely used method for achieving this is SSH tunneling, which provides a secure way to access Jupyter Notebooks running on remote compute/execution machines. In this article, we will explore how to set up and run Jupyter Notebooks via SSH tunneling, enabling seamless and secure remote data science workflows.
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Understanding SSH Tunneling
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SSH (Secure Shell) is a network protocol that allows secure remote access to a server. SSH tunneling, also known as SSH port forwarding, extends this capability by securely forwarding network connections from a local machine to a remote server. By leveraging SSH tunneling, we can establish a secure connection between our local machine and a remote server hosting a Jupyter Notebook.
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Running Jupyter Notebooks on a compute host
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To start, open a terminal window on your local machine and log in to a CRC front-end node (e.g. crcfe01) using the following command:
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ssh -Y netid@crfe01.crc.nd.edu
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(Replace netid with your Notre Dame netID). Once logged in, access the desired compute node based on your requirements. For most users the following command will work and
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For jobs that require a GPU, use the following command:
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qrsh -q gpu -l gpu_card=1 -pe smp 1
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Inside the compute node, launch the Jupyter Notebook server using the following command:
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jupyter notebook --no-browser --ip='0.0.0.0'
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Make note of the server name and port number displayed in the output. It will look something like this:
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Jupyter Notebook is running at: http://host_name.crc.nd.edu:8888/?token=4e6fc6f60565415f4220b897f
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Setting up SSH tunneling for secure access
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To establish a secure connection, open another terminal window on your local machine. Run the following command:
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ssh netid@crcfe01.crc.nd.edu -L 8888:host_name.crc.nd.edu:8888 -N
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Enter your password when prompted. If there are no errors, the command line will hang, which is normal. Finally, open a web browser on your local machine and navigate to http://localhost:8888/. You will be prompted to enter the token obtained earlier.
With SSH tunneling, you can securely access and interact with Jupyter Notebooks running on remote servers, enabling seamless and secure remote data science workflows. Enjoy the flexibility and convenience while working with your data!
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| Every Wednesday and Thursday in June
2:00 – 3:00 p.m.
Flanner Hall, CRC Training Room 812 (map)
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This training is available to new users and current users interested in a refresher course on how to use CRC resources. Attendees learn the basics of accessing CRC resources and submitting jobs on the CRC clusters. This course is a co-requisite when receiving a CRC account. Learn more.
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Top 10 Computation Users (May 2023)
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596,281 CPU hours
Civil & Environmental Engineering & Earth Sciences
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468,687 CPU hours
Civil & Environmental Engineering & Earth Sciences
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330,673 CPU hours
Chemical & Biomolecular Engineering
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320,212 CPU hours
Aerospace & Mechanical Engineering
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308,719 CPU hours
Civil & Environmental Engineering & Earth Sciences
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| 293,859 CPU hours
Aerospace & Mechanical Engineering
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279,345 CPU hours
Civil & Environmental Engineering & Earth Sciences
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224,789 CPU hours
Chemistry & Biochemistry
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9. Fernando Carmona Esteva |
219,416 CPU hours
Chemical & Biomolecular Engineering
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172,280 CPU hours
Aerospace & Mechanical Engineering
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