CS 315-02 Lecture/Lab — Meeting Summary (Fall 2025)¶

Meeting Details¶

The instructor, Greg, introduced himself and outlined the course focus on computer architecture, culminating in building a processor by semester’s end.
The class discussed the role and impact of AI, including its benefits, risks, applications across fields, and ethical considerations.
Greg previewed technical content (programming languages, architecture concepts) and explained course structure, expectations, and upcoming assignments.

Greg introduced his background and enthusiasm for teaching computer architecture, highlighting past experience building a processor.
The course emphasizes understanding how computers work from the ground up, leading to building a simple processor by the end of the semester.
He discussed rapid advances in AI and coding assistance, noting a recent example where a language model helped migrate a website between static site generators.
The first lab is due next week; students were encouraged to share perspectives on AI and coding assistance during introductions.

Participants discussed AI’s benefits and risks, including probabilistic outputs, data sources, and bias.
Greg stressed responsible use: AI as a tool, not a replacement for human expertise.
Open questions included AI’s impact on professional roles, creativity, and data ownership.

Greg described balancing AI tool use (e.g., ChatGPT’s Study Mode) with the need to preserve critical thinking.
He shared that Study Mode can be effective for learning languages like Rust and noted features that remember user context.
He emphasized student responsibility for learning and outlined assessment approaches designed to reward understanding, not shortcutting with AI.

The group discussed AI’s rapid evolution and integration into workflows.
Multiple viewpoints were shared:
Optimism about productivity and new capabilities.
Caution about ethics, responsible use, and long-term implications.
Examples included AI for data organization and analogies comparing AI to powerful tools that require careful handling.
The conversation highlighted the responsibility of future technologists to shape AI’s impact on society.

Perspectives included:
Creative uses (e.g., building mini websites with AI).
Concerns about ethical issues and reduced critical thinking, especially among younger learners.
Inequities in access to AI tools between schools in different socioeconomic contexts.
Greg emphasized the enduring importance of human empathy and interaction, citing nursing as a role unlikely to be replaced by AI.
Professional experiences shared by participants reflected cautious optimism.

Greg underscored that understanding programming fundamentals is key to effectively using AI tools.
He described a potential shift toward “software designers” who focus more on theory and system design, with AI handling more implementation details.
Debugging and problem-solving remain essential, with AI increasingly helpful in those areas.
Participants shared experiences and concerns about privacy and data usage in AI-enabled coding.

Greg noted that AI lowers barriers for non-coders to create complex applications.
He acknowledged concerns about job displacement, while also pointing to scenarios where AI’s 24/7 availability could make it more expensive than human labor.
He plans to reassess course capacity within 2–3 weeks and may add students.

Greg reflected on prior teaching feedback, highlighting the need for practical, real-world application of AI concepts.
He emphasized foundational knowledge and integrating AI into software development processes.
He compared this course to a complex, serialized narrative (more “Game of Thrones” than “The Love Boat”), underscoring cumulative learning.

The C portion of the course is a vehicle for understanding data representation (especially binary), not for producing professional C developers.
After a brief C review, the class transitions to assembly language with a focus on the RISC-V architecture.
Greg discussed Apple’s move to its ARM-based Apple silicon and noted that companies may consider RISC-V in the future due to its open nature and potential cost savings.

The course traces the path from high-level languages (e.g., Java, Python) down to assembly and machine code.
Assembly is presented as a human-readable form of machine code—simpler in structure but capable of complex problem solving.
Greg explained cache memory’s role in bridging processor–memory speed gaps.
Digital design fundamentals will be covered intensively over ~3 weeks to enable students to build a basic processor.

C remains foundational in operating systems and embedded systems.
Rust offers memory safety without garbage collection trade-offs, making it valuable for systems programming.
Students will practice terminal workflows and debugging, especially for assembly.
SSH and remote development are emphasized, including work on Beagle machines used in course projects.

Greg supports using AI study tools and will provide prompts to guide labs and projects.
Course structure:
Weekly labs or projects.
Attendance: 10% of the grade.
Exams: 50% of the grade; notes are allowed, and practice problems will be provided to reduce anxiety.
Absences: no excused absences except with medical documentation; consistent attendance is encouraged.
The upcoming lab will focus on development environment setup. The syllabus, website, and first lab assignment will be distributed this week.