Aims

Thinking Machines

Author

Prof. Calvin

Introduction

Welcome to Willamette!
Welcome to Thinking Machines
We will learn:
- Scientific computing, to learn…
- Machine learning and artifical intelligence

Course Description

Artifical intelligence, machine learning, big data, and large scale computing have captured the collective imaginations of millions people across a range of technical expertise. Yet each of these buzzwords is rooted in a central promise: that machines may think.

About Me

About	Me
Name:	Calvin (Deutschbein)
Say:	(Professor) Calvin
Pronoun:	they/them
Office:	Discord calvin2501
Email:	ckdeutschbein@willamette.edu
Website:	cd-public.github.io

Background

Thesis Title: Mining Secure Behavior of Hardware Designs

Specification mining can discover properties that can verify the secure behavior of closed-source CISC CPU designs, the temporal correctness of CPU designs, and hyperproperties for secure information flow in modules, SoCs, and CPUs.

Background

Plain English:
Just as there are bugs in code that make software, modern hardware is also written in code and therefore may contain bugs. I find these bugs.
Of note: I found those bugs using scientific computing (thinking machines).

Modality

Lecture (Talk)
- Monday & Wednesday
Exercise (Code)
- Friday
Projects (Write-ups)
- Friday, 10 Oct
- Friday, 14 Nov

General Expectations

Students will begin the course with a grade of an “A”.
- Students will be expected to:
  - Follow lecture.
  - Treat fellow students with respect.
  - Complete exercises.
  - Complete projects.

Class/Exercises

For an A (10/10)
- Code that meets requirements.
- On time.
For a B (9/10)
- Code that runs without error.
- On time
Erroneous code is an F (6/10)
Late work is a zero (0/10)

Feedback Structure

Students collectively within the class as a whole will receive feedback..
- Individual feedback will be provided in limited and unique cases.
- Students are expected to provide respectfully collaborate on exercises.
- Students may request individual feedback from the instructor at any time.
- Students will receive narrative rather than quantitative feedback.

Project/Website

Students will create a public-facing scientific publication via:
- Midterm: GitHub, Markdown, Python
- Final: Quarto, GitHub Pages, Python
Graded on the AP Scale as an argument essay and then curved.

Group Exercise:

Let’s start the class off right away with an exercise designed for:
- Groups
- Discussion
- Disagreement
- Deep critical thinking

Aims of Education

Before starting my first degree, we went to a lecture titled “Aims of Education”
I completed all remaining degrees during shutdowns/other crises!
I remember it fondly.
We will review “Explainable AI for Climate Science” by Elizabeth Barnes.
- And then discuss.

Source

Question 0

What are the goals of a college education?

Think: about a possible answer individually.
Discuss: answers within the group.
Record: a summary of the discussion.

Question 1

How does a scientist learn something new?

Think: about a possible answer individually.
Discuss: answers within the group.
Record: a summary of the discussion.

Question 2

What do you reasonably expect to remember from your courses in 20 years?

Think: about a possible answer individually.
Discuss: answers within the group.
Record: a summary of the discussion.

Question 3

What is the value of making mistakes in the learning process?

Think: about a possible answer individually.
Discuss: answers within the group.
Record: a summary of the discussion.

Question 4

How do we create a safe environment where risk-taking is encouraged and productive failure is valued?

Think: about a possible answer individually.
Discuss: answers within the group.
Record: a summary of the discussion.

Closing Thoughts

Try! Hard work leads to innovative thinking.
Fail! Don’t fear failure. Be ready to redo from scratch.
Collaborate! Work with peers to succeed at this course and succeed at collaboration.
Enjoy! Experience the fun of being a scientist through hard work and exploration.

--- title: "Aims" --- # Introduction - Welcome to Willamette! - Welcome to *Thinking Machines* - We will learn: - Scientific computing, to learn... - Machine learning and artifical intelligence ## Course Description > Artifical intelligence, machine learning, big data, and large scale computing have captured the collective imaginations of millions people across a range of technical expertise. Yet each of these buzzwords is rooted in a central promise: that machines may think. ## About Me |About|Me| |-|-| | **Name**: |Calvin (Deutschbein) | | **Say**: |(Professor) Calvin | | **Pronoun**: |they/them | | **Office**: |Discord calvin2501 | | **Email**: |[ckdeutschbein@willamette.edu](@mailto:ckdeutschbein@willamette.edu) | | **Website**: |[cd-public.github.io](https://cd-public.github.io)| --- ## Background - **Thesis Title**: [Mining Secure Behavior of Hardware Designs](https://cd-public.github.io/papers/2021/CD2021.pdf) > Specification mining can discover properties that can verify the secure behavior of closed-source CISC CPU designs, the temporal correctness of CPU designs, and hyperproperties for secure information flow in modules, SoCs, and CPUs. ## Background - **Plain English**: Just as there are bugs in code that make **software**, modern **hardware** is also written in code and therefore may contain bugs. I find these bugs. - Of note: I found those bugs *using scientific computing* (thinking machines). --- # Modality - Lecture (Talk) - Monday & Wednesday - Exercise (Code) - Friday - Projects (Write-ups) - Friday, 10 Oct - Friday, 14 Nov --- ## General Expectations - **Students will begin the course with a grade of an "A".** - Students will be expected to: - Follow lecture. - Treat fellow students with respect. - Complete exercises. - Complete projects. --- ## Class/Exercises - For an A (10/10) - Code that meets requirements. - On time. - For a B (9/10) - Code that runs without error. - On time - Erroneous code is an F (6/10) - Late work is a zero (0/10) --- ## Feedback Structure - Students collectively within the class as a whole will receive feedback.. - Individual feedback will be provided in limited and unique cases. - Students are expected to provide respectfully collaborate on exercises. - Students may request individual feedback from the instructor at any time. - Students will receive narrative rather than quantitative feedback. --- ## Project/Website - Students will create a public-facing scientific publication via: - Midterm: GitHub, Markdown, Python - Final: Quarto, GitHub Pages, Python - Graded on the [AP Scale](https://apcentral.collegeboard.org/media/pdf/ap-english-language-and-composition-frqs-1-2-3-scoring-rubrics.pdf) as an argument essay and then curved. # Group Exercise: - Let’s start the class off right away with an exercise designed for: - Groups - Discussion - Disagreement - Deep critical thinking --- ## Aims of Education - Before starting my first degree, we went to a lecture titled "Aims of Education" - I completed all remaining degrees during shutdowns/other crises! - I remember it fondly. - We will review "Explainable AI for Climate Science" by Elizabeth Barnes. - And then discuss. --- <center><iframe width="560" height="315" src="https://www.youtube.com/watch?v=XEGDdB8tpa0" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe> <br> [Source](https://www.youtube.com/watch?v=XEGDdB8tpa0) </center> --- ## Question 0 > **What are the goals of a college education?** - **Think**: about a possible answer individually. - **Discuss**: answers within the group. - **Record**: a summary of the discussion. ## Question 1 > **How does a scientist learn something new?** - **Think**: about a possible answer individually. - **Discuss**: answers within the group. - **Record**: a summary of the discussion. ## Question 2 > **What do you reasonably expect to remember from your courses in 20 years?** - **Think**: about a possible answer individually. - **Discuss**: answers within the group. - **Record**: a summary of the discussion. ## Question 3 > **What is the value of making mistakes in the learning process?** - **Think**: about a possible answer individually. - **Discuss**: answers within the group. - **Record**: a summary of the discussion. ## Question 4 > **How do we create a safe environment where risk-taking is encouraged and productive failure is valued?** - **Think**: about a possible answer individually. - **Discuss**: answers within the group. - **Record**: a summary of the discussion. --- # Closing Thoughts - **Try!** Hard work leads to innovative thinking. - **Fail!** Don't fear failure. Be ready to redo from scratch. - **Collaborate!** Work with peers to succeed at this course and succeed at collaboration. - **Enjoy!** Experience the fun of being a scientist through hard work and exploration.