Applications of AI/ML in Enterprise Software
Prabakar Sundarrajan
Founder, Chief Strategist
The Fabric
03/28/2023
Enterprises such as financial companies, health care systems, and transportation etc., have utilized decision support systems and programmed automation built on top of different kinds of databases and scripting languages for a long time now for many purposes, such as increasing revenues, decreasing costs and optimizing processing times. However, recently AI/ML techniques are also being increasingly incorporated, which are turbo-charging the value to the enterprises significantly. This talk will give an overview and examples of how AI/ML techniques are being utilized in enterprises and the resulting benefits they are obtaining. It will also provide a glimpse of the future AI driven enterprise.
AI Inference with Intel® FPGA AI Suite
Kevin Drake
Intel Corporation
04/11/2023
Intel® FPGAs enable real-time, low-latency, and low-power deep learning inference combined with the following advantages: I/O flexibility, Reconfiguration, Ease of integration into custom platforms and Long lifetime
Intel® FPGA AI Suite was developed with the vision of ease-of-use of artificial intelligence (AI) inference on Intel® FPGAs. The suite enables FPGA designers, machine learning engineers, and software developers to create optimized FPGA AI platforms efficiently.
Utilities in the Intel FPGA AI Suite speed up FPGA development for AI inference using familiar and popular industry frameworks such as TensorFlow* or PyTorch* and OpenVINO toolkit, while also leveraging robust and proven FPGA development flows with the Intel Quartus Prime Software.
The Intel® FPGA AI Suite tool flow works with the OpenVINO toolkit, an open-source project to optimize inference on a variety of hardware architectures. The OpenVINO toolkit takes Deep Learning models from all the major Deep Learning frameworks (such as TensorFlow, PyTorch, Keras*) and optimizes them for inference on a variety of hardware architectures, including various CPUs, CPU+GPU, and FPGAs.
Visualization Literacy - Can we learn how to read unfamiliar charts?
Alark Joshi
Associate Professor
Dept of Computer Science, University of San Francisco
04/18/2023
As we continue to learn about ways to combat misinformation, charts are being used to spread misinformation as well. The data visualization research community has developed a large number of techniques to represent various types of data (multivariate, temporal, structural, and so on). These techniques such as Treemaps,
Sankey diagrams, and Parallel coordinates, are being used increasingly in the media for communication.
In this talk, I will share the need for improving the overall visualization literacy as well as our efforts in the direction of increasing literacy for students in the classroom. I will present the use of Bloom's taxonomy for the pedagogy of visualization techniques and demonstrate that it can help increase the confidence, awareness, and accuracy of the participants who learned about a completely new visualization technique. I will conclude the talk with future directions of research in the field of visualization literacy.
Tapping into Formal Methods for Pedagogical Adrenaline Rush: Possible?
Ganesh Gopalakrishnan
Professor,
Computer Science Department, University of Utah
04/25/2023
Formal methods have traditionally evolved around the core concepts of specifying systems and matching system behaviors against the specifications. How successfully can existing Formal Methods be tapped into for rejuvenating today's undergraduate curricula? I will introduce the pivotal role played by Formal Methods in safeguarding today's software and hardware, and then present a few attempts I have made in bringing it down into the undergraduate curriculum. My illustrations span the classical Automata Theory, Boolean Logic, Concurrency and Automated Theorem-Proving.
I will go through topics such as Automata Theory, Binary Decision Diagrams, and Satisfiability-Modulo Theories to illustrate my point through examples that can be dropped into curricula. These examples cover situations from games through solving the scheduling of concurrent programs.
It is my growing belief that the thrill of seeing hard problems fall victim to the power of automated tools can give the adrenaline rush that makes a topic fun to learn. Treating these topics pedantically is acceptable for mathematical maturity; but must ideally also be complemented with illustrations that make the students see the research and industrial horizons opened up by formal methods.
Spring 2023 Short Presentations of Student Research
05/02/2023
Short presentations of research carried out by Sonoma State Computer Science Students.
List of Speakers:
- Andrew Avola and Amit Deb: A virtual reality application design and implementation
- Brennan Freeze, Aundre Barras, Paris Osuch, Soren Richenberg, Suzanne Rivoire (SSU): A quantum computing Python library
- Luke Demeter-Willison: Efficient Algorithm Design for a Combinatorial Puzzle using Finite Automata