Jed
@jedediyah.com
Teacher ◦ Robots and mathy science ◦ He/Him
#ITeachMath #ITeachPhysics #TeamCompSci
#mtbos #PAEMST
https://jedediyah.github.io/
#ITeachMath #ITeachPhysics #TeamCompSci
#mtbos #PAEMST
https://jedediyah.github.io/
The number of players on @chess.com who abandon games without resigning has skyrocketed in the past few weeks.
Tried to leave feedback but got the chat bot that told me to clear my browser cache. Thanks AI!
Tried to leave feedback but got the chat bot that told me to clear my browser cache. Thanks AI!
January 14, 2026 at 11:04 PM
The number of players on @chess.com who abandon games without resigning has skyrocketed in the past few weeks.
Tried to leave feedback but got the chat bot that told me to clear my browser cache. Thanks AI!
Tried to leave feedback but got the chat bot that told me to clear my browser cache. Thanks AI!
Consider we have a sense of quantity but don't have numbers. We have stones that we can arrange in piles and patterns.
A natural way to arrange stones is in rectangles *if you can*. I use this with 3-5 year olds and very quickly they are exploring and finding factorizations and identifying primes.
A natural way to arrange stones is in rectangles *if you can*. I use this with 3-5 year olds and very quickly they are exploring and finding factorizations and identifying primes.
January 11, 2026 at 6:58 PM
Consider we have a sense of quantity but don't have numbers. We have stones that we can arrange in piles and patterns.
A natural way to arrange stones is in rectangles *if you can*. I use this with 3-5 year olds and very quickly they are exploring and finding factorizations and identifying primes.
A natural way to arrange stones is in rectangles *if you can*. I use this with 3-5 year olds and very quickly they are exploring and finding factorizations and identifying primes.
In #MathsToday we modeled a tide.
Part (e) led to some amazing passionate mathematical arguments!
(e) Our model has four parameters. Could you still model the tide well enough with only three?
Part (e) led to some amazing passionate mathematical arguments!
(e) Our model has four parameters. Could you still model the tide well enough with only three?
January 7, 2026 at 11:07 PM
In #MathsToday we modeled a tide.
Part (e) led to some amazing passionate mathematical arguments!
(e) Our model has four parameters. Could you still model the tide well enough with only three?
Part (e) led to some amazing passionate mathematical arguments!
(e) Our model has four parameters. Could you still model the tide well enough with only three?
I gave a talk in 2024 called "Sensitive Dependence on Initial Conditions: How AI Predictably Fails Unpredictably". A dope title!
jedediyah.github.io/aapt2024/
In examples of AI failing where we shouldn't be using AI, I highlighted a behavior nobody should be surprised by: AI encouraging suicide.
jedediyah.github.io/aapt2024/
In examples of AI failing where we shouldn't be using AI, I highlighted a behavior nobody should be surprised by: AI encouraging suicide.
December 29, 2025 at 12:44 AM
I gave a talk in 2024 called "Sensitive Dependence on Initial Conditions: How AI Predictably Fails Unpredictably". A dope title!
jedediyah.github.io/aapt2024/
In examples of AI failing where we shouldn't be using AI, I highlighted a behavior nobody should be surprised by: AI encouraging suicide.
jedediyah.github.io/aapt2024/
In examples of AI failing where we shouldn't be using AI, I highlighted a behavior nobody should be surprised by: AI encouraging suicide.
Of course we validated our models with data splitting!
December 18, 2025 at 9:05 PM
Of course we validated our models with data splitting!
We use three of those points to find the equation of that quadratic, and then identify the vertex which corresponds to the minimum error at our optimal model parameter.
Two students volunteered to share their beautiful work!
Two students volunteered to share their beautiful work!
December 18, 2025 at 9:05 PM
We use three of those points to find the equation of that quadratic, and then identify the vertex which corresponds to the minimum error at our optimal model parameter.
Two students volunteered to share their beautiful work!
Two students volunteered to share their beautiful work!
Instead of getting a magically-fit regression from software, we find it ourselves! For several values of the slope, we find the sum of squared errors for our model. This turns out to generate an ideal quadratic (even from noisy real data!).
December 18, 2025 at 9:05 PM
Instead of getting a magically-fit regression from software, we find it ourselves! For several values of the slope, we find the sum of squared errors for our model. This turns out to generate an ideal quadratic (even from noisy real data!).
Recognizing that a ball dropped from height 0 should bounce 0 cm high, we choose the a simple linear model.
December 18, 2025 at 9:05 PM
Recognizing that a ball dropped from height 0 should bounce 0 cm high, we choose the a simple linear model.
In #MathsToday we did one of my favorite activities: Regression by Hand.
Our goal is to model the bounce height h_bounce of a bouncy ball dropped from height h_drop.
#mtbos #ITeachMath
Our goal is to model the bounce height h_bounce of a bouncy ball dropped from height h_drop.
#mtbos #ITeachMath
December 18, 2025 at 9:05 PM
In #MathsToday we did one of my favorite activities: Regression by Hand.
Our goal is to model the bounce height h_bounce of a bouncy ball dropped from height h_drop.
#mtbos #ITeachMath
Our goal is to model the bounce height h_bounce of a bouncy ball dropped from height h_drop.
#mtbos #ITeachMath
In #MathsToday we are playing and analyzing Hexapawn as an introduction to machine learning.
You can play and have a machine play itself here:
jedediyah.github.io/hexapawn/
There are two problem sets here: williams-bhs.github.io/docs/hexapaw...
You can play and have a machine play itself here:
jedediyah.github.io/hexapawn/
There are two problem sets here: williams-bhs.github.io/docs/hexapaw...
December 10, 2025 at 10:02 PM
In #MathsToday we are playing and analyzing Hexapawn as an introduction to machine learning.
You can play and have a machine play itself here:
jedediyah.github.io/hexapawn/
There are two problem sets here: williams-bhs.github.io/docs/hexapaw...
You can play and have a machine play itself here:
jedediyah.github.io/hexapawn/
There are two problem sets here: williams-bhs.github.io/docs/hexapaw...
The top functions are known. I don't know the function(s) that fit just the blue section. If you can find them, you'll have the solution! Since we can integrate the known functions - the unknown ones.
November 28, 2025 at 5:25 PM
The top functions are known. I don't know the function(s) that fit just the blue section. If you can find them, you'll have the solution! Since we can integrate the known functions - the unknown ones.
Here is a zoomed in version.
1. A tetrahedron is not possible if f is longer than 1/3.
2. If f < 1/5, a tetrahedron is necessarily possible.
3. The function that separates the orange points from the blue points is piece-wise quartic, and the probability of a tetrahedron is therefore rational!
1. A tetrahedron is not possible if f is longer than 1/3.
2. If f < 1/5, a tetrahedron is necessarily possible.
3. The function that separates the orange points from the blue points is piece-wise quartic, and the probability of a tetrahedron is therefore rational!
November 28, 2025 at 5:25 PM
Here is a zoomed in version.
1. A tetrahedron is not possible if f is longer than 1/3.
2. If f < 1/5, a tetrahedron is necessarily possible.
3. The function that separates the orange points from the blue points is piece-wise quartic, and the probability of a tetrahedron is therefore rational!
1. A tetrahedron is not possible if f is longer than 1/3.
2. If f < 1/5, a tetrahedron is necessarily possible.
3. The function that separates the orange points from the blue points is piece-wise quartic, and the probability of a tetrahedron is therefore rational!
Particularly I focused on the the *longest piece f*. Here is a stacked normalized histogram to approximate the probability density function (which is known!) for just the longest piece. Again, the orange corresponds to successful tetrahedra.
November 28, 2025 at 5:25 PM
Particularly I focused on the the *longest piece f*. Here is a stacked normalized histogram to approximate the probability density function (which is known!) for just the longest piece. Again, the orange corresponds to successful tetrahedra.
Consider breaking the stick into six pieces ordered by length: a,b,c,d,e,f. I generated and shared this cross plot of the six ordered pieces. Orange points correspond to positive tetrahedra configurations, and blue are negative. There is a lot that is interesting!
November 28, 2025 at 5:25 PM
Consider breaking the stick into six pieces ordered by length: a,b,c,d,e,f. I generated and shared this cross plot of the six ordered pieces. Orange points correspond to positive tetrahedra configurations, and blue are negative. There is a lot that is interesting!
Afterwards, I shared the 3D version of this problem I know from @benjamindickman.bsky.social:
Given a stick broken randomly at 5 places, what is the probability that a tetrahedron can be formed from the six pieces.
Given a stick broken randomly at 5 places, what is the probability that a tetrahedron can be formed from the six pieces.
November 28, 2025 at 5:25 PM
Afterwards, I shared the 3D version of this problem I know from @benjamindickman.bsky.social:
Given a stick broken randomly at 5 places, what is the probability that a tetrahedron can be formed from the six pieces.
Given a stick broken randomly at 5 places, what is the probability that a tetrahedron can be formed from the six pieces.
Shared a Thanksgiving gift with my data science students today! I spend a couple months collecting used copies. Next month we will read chapter 3 Arms Race and reflect on feedback systems and the susceptibility and sensitivity of data models to manipulation.
November 21, 2025 at 8:03 PM
Shared a Thanksgiving gift with my data science students today! I spend a couple months collecting used copies. Next month we will read chapter 3 Arms Race and reflect on feedback systems and the susceptibility and sensitivity of data models to manipulation.
Last week we worked on combinatorics and I asked about the weight of a binary word.
In #MathsToday we worked on random walks and I asked what is the probability of ending where we started. Some of the students used the weight solution to find the probability! 🥳
#mtbos #ITeachMath
In #MathsToday we worked on random walks and I asked what is the probability of ending where we started. Some of the students used the weight solution to find the probability! 🥳
#mtbos #ITeachMath
November 21, 2025 at 5:24 PM
Last week we worked on combinatorics and I asked about the weight of a binary word.
In #MathsToday we worked on random walks and I asked what is the probability of ending where we started. Some of the students used the weight solution to find the probability! 🥳
#mtbos #ITeachMath
In #MathsToday we worked on random walks and I asked what is the probability of ending where we started. Some of the students used the weight solution to find the probability! 🥳
#mtbos #ITeachMath
In #MathsToday we rolled a lot of dice and found estimates of probability mass functions for sums of n=2,3 4 dice.
In #MathsNextWeek we start to explore broken stick problems!
Draft of next week's guide:
williams-bhs.github.io/docs/Broken_...
In #MathsNextWeek we start to explore broken stick problems!
Draft of next week's guide:
williams-bhs.github.io/docs/Broken_...
November 14, 2025 at 6:02 PM
In #MathsToday we rolled a lot of dice and found estimates of probability mass functions for sums of n=2,3 4 dice.
In #MathsNextWeek we start to explore broken stick problems!
Draft of next week's guide:
williams-bhs.github.io/docs/Broken_...
In #MathsNextWeek we start to explore broken stick problems!
Draft of next week's guide:
williams-bhs.github.io/docs/Broken_...
In #MathsToday we played with the "Cat Machine" and talked about theoretical probabilities, experimental probability, and confidence in our experimental probabilities.
November 13, 2025 at 8:43 PM
In #MathsToday we played with the "Cat Machine" and talked about theoretical probabilities, experimental probability, and confidence in our experimental probabilities.
Was really curious to see how these problems would go over in #MathsToday. It was great!
We talked about how to map all of the problems onto the last problem and the usefulness of knowing "how to solve it" when we can recognize and abstract problems to known strategies.
We talked about how to map all of the problems onto the last problem and the usefulness of knowing "how to solve it" when we can recognize and abstract problems to known strategies.
November 4, 2025 at 6:00 PM
Was really curious to see how these problems would go over in #MathsToday. It was great!
We talked about how to map all of the problems onto the last problem and the usefulness of knowing "how to solve it" when we can recognize and abstract problems to known strategies.
We talked about how to map all of the problems onto the last problem and the usefulness of knowing "how to solve it" when we can recognize and abstract problems to known strategies.
I once gave a talk called "AI is not what you think it is unless you think it is hot garbage"
I've just enjoyed and highly recommend @chrissimon.au's "AI is a hype-fuelled dumpster fire that will burn down the planet and get you thrown in jail"
www.youtube.com/watch?v=0bF_...
I've just enjoyed and highly recommend @chrissimon.au's "AI is a hype-fuelled dumpster fire that will burn down the planet and get you thrown in jail"
www.youtube.com/watch?v=0bF_...
November 2, 2025 at 11:03 PM
I once gave a talk called "AI is not what you think it is unless you think it is hot garbage"
I've just enjoyed and highly recommend @chrissimon.au's "AI is a hype-fuelled dumpster fire that will burn down the planet and get you thrown in jail"
www.youtube.com/watch?v=0bF_...
I've just enjoyed and highly recommend @chrissimon.au's "AI is a hype-fuelled dumpster fire that will burn down the planet and get you thrown in jail"
www.youtube.com/watch?v=0bF_...
In #MathsToday, trying to talk about state machines without talking about state machines.
Also debated with students whether we should fully represent all 12 states or reduce the number of bits to the minimum required (depending on number of states used).
Also debated with students whether we should fully represent all 12 states or reduce the number of bits to the minimum required (depending on number of states used).
October 29, 2025 at 10:30 PM
In #MathsToday, trying to talk about state machines without talking about state machines.
Also debated with students whether we should fully represent all 12 states or reduce the number of bits to the minimum required (depending on number of states used).
Also debated with students whether we should fully represent all 12 states or reduce the number of bits to the minimum required (depending on number of states used).
In #MathsToday we continued working on our graph theory exercises.
October 28, 2025 at 11:12 PM
In #MathsToday we continued working on our graph theory exercises.
In #MathsToday we are working on graphs, and getting some motivation for our next unit on combinatorics.
October 23, 2025 at 4:15 PM
In #MathsToday we are working on graphs, and getting some motivation for our next unit on combinatorics.
