AI and Mathematics

SUMMARY

Professor Terence Tao discusses the transformative impact of AI on mathematics, sharing historical context and modern applications at the IMO.

IDEAS:

  • Terence Tao began participating in the IMO at just 11 years, showcasing extraordinary talent early.
  • AI tools like AlphaGeometry are revolutionizing how mathematics is approached and solved today.
  • Machine assistance in mathematics has historical roots, dating back thousands of years to the abacus.
  • Computers have been used in mathematics for about 300-400 years, evolving from mechanical to electronic.
  • The term “computer” originally referred to human calculators, particularly during World War II.
  • The Online Encyclopedia of Integer Sequences is a valuable resource for identifying mathematical patterns.
  • Scientific computation has been used since the 1920s, with early work done by Hendrik Lorentz.
  • AI tools now assist in complex mathematical problems that were previously too tedious for humans.
  • SAT solvers can analyze logic puzzles and complex statements, but they struggle with scalability.
  • AI assistance has enabled the proof of long-standing mathematical conjectures, like the Pythagorean triple problem.
  • Formal proof assistants are improving the verification of mathematical arguments and proofs.
  • The Four Color Theorem was one of the first major proofs aided by computer assistance.
  • Machine learning has recently been applied to discover connections in knot theory and other areas.
  • Large language models like GPT-4 can provide solutions to specific mathematical problems, albeit with limitations.
  • Formalizing proofs in AI environments can speed up the process of verification and collaboration among mathematicians.
  • Collaborative projects using AI have enabled faster and more efficient formalization of complex mathematical proofs.
  • The future of mathematics may involve using AI to solve multiple problems simultaneously rather than one at a time.
  • Machines can assist in generating conjectures based on large datasets, potentially leading to new discoveries.
  • AI’s role in mathematics will remain supportive, enhancing human creativity rather than replacing it.
  • Personal interactions and serendipity often lead to new research ideas among mathematicians.
  • The integration of AI into mathematics requires mathematicians to retain foundational knowledge to guide AI effectively.

INSIGHTS:

  • AI’s integration into mathematics may redefine the boundaries of research and problem-solving methods.
  • Historical context reveals that the intersection of machines and mathematics is not a new phenomenon.
  • Collaborative mathematical projects can thrive when AI tools assist in the formalization and verification processes.
  • Future mathematics could involve large-scale problem exploration facilitated by AI’s computational power.
  • Machine learning’s ability to highlight connections in data can lead to innovative mathematical conjectures.
  • The evolution of proof assistants has made formal verification more accessible to mathematicians today.
  • Humans still play a crucial role in interpreting AI-generated insights and conjectures in mathematics.
  • Mathematics is increasingly becoming a collaborative and interdisciplinary field due to technological advancements.
  • Serendipity and conversation remain pivotal in shaping research directions in mathematics.
  • The potential for AI to automate conjecture generation represents a significant frontier for mathematical exploration.

QUOTES:

  • “I hope we all had fun, not just in the competition whether you get a good score or not.”
  • “Instead of having three hours to solve a problem, you take months and sometimes you don’t solve it.”
  • “We’ve actually been using computers and machines to do mathematics for a long time.”
  • “The basic unit of computational power at the time was not the CPU, it was the kilgirl.”
  • “In mathematical research, we rely on tables – we call them databases now.”
  • “Many promising productive research projects have come up that way.”
  • “We’ve been doing scientific computation since the 1920s.”
  • “The proof required a few years of computation and it generated a proof certificate.”
  • “The future is going to be really exciting.”
  • “This may be my most important result to date – better be sure it’s correct.”
  • “Every little bubble corresponds to some statement and you don’t need to understand the whole proof.”
  • “We’re beginning to sort of prove things that are like 4 or 5 lines long.”
  • “AI assistance has enabled the proof of long-standing mathematical conjectures.”
  • “I think the future will require more flexibility in research topics.”
  • “The hope is that AI will become very good at generating good conjectures.”
  • “We still use tables today; we call them databases now, but they’re still the same thing.”

HABITS:

  • He reflects fondly on his experiences at the IMO, emphasizing the importance of enjoyment in competition.
  • Tao suggests that successful mathematicians often rely on strong mentorship throughout their education.
  • Engaging in conversations at conferences can spark new research ideas and collaborations.
  • He believes in taking research topics one at a time rather than rushing into multiple areas.
  • Tao emphasizes the importance of being flexible in research topics and adapting to new ideas.
  • He collaborates with diverse teams, including non-mathematicians, to tackle complex problems.
  • Utilizing modern proof assistants has become a regular practice for verifying complex mathematical arguments.
  • Tao experiments with AI tools to explore new techniques and approaches in his research.
  • He encourages others to learn from mistakes and adapt their strategies when faced with challenges.
  • Maintaining foundational knowledge in mathematics is crucial for effectively guiding AI tools.

FACTS:

  • The first participant in the IMO to receive a gold medal was Terence Tao at age 13.
  • The abacus is one of the earliest machines used for mathematical calculations, dating back thousands of years.
  • Computers for mathematical computation have existed in various forms for about 300-400 years.
  • The Online Encyclopedia of Integer Sequences contains hundreds of thousands of integer sequences.
  • The first major computer-assisted proof was the Four Color Theorem, proven in 1976.
  • Scientific computation has been utilized since the 1920s, often involving large human computing teams.
  • The proof of the Pythagorean triple problem required a massive computation and was computer-assisted.
  • Formal proof assistants are increasingly being used to verify complex mathematical arguments.
  • Large language models can provide mathematical solutions, but their accuracy is often limited.
  • Machine learning has recently been applied to discover connections between different areas of mathematics.
  • The integration of AI in mathematics is projected to enhance collaboration and problem-solving efficiency.
  • Collaborative projects in mathematics are becoming more common, often involving interdisciplinary teams.
  • The proof of the Kepler conjecture was formalized and completed in 2014 after many years of work.
  • Recent advancements in proof assistants have made formal verification processes more efficient and user-friendly.
  • AI tools can assist mathematicians by generating conjectures based on large datasets and patterns.
  • Mathematics is becoming more collaborative, with mathematicians increasingly sharing ideas and insights.

REFERENCES:

  • AlphaGeometry, a tool by DeepMind for answering geometry questions in competitions.
  • Online Encyclopedia of Integer Sequences (OEIS), a database of integer sequences.
  • Formal proof assistants like Lean and Coq for verifying mathematical arguments.
  • The Flyspeck project, which formalized the proof of the Kepler conjecture.
  • GitHub Copilot, an AI tool that suggests lines of code for formal proofs.
  • The Four Color Theorem, one of the earliest computer-assisted proofs.
  • The Birch and Swinnerton-Dyer conjecture, discovered through extensive data tables.
  • Condensed mathematics, a field developed by Peter Scholze focusing on functional analysis.
  • Various software tools that facilitate collaborative proof formalization projects.
  • Notable mathematical events and conferences where ideas and research are shared.

ONE-SENTENCE TAKEAWAY

AI is transforming mathematics by enhancing problem-solving capabilities and facilitating collaborative research among mathematicians.

RECOMMENDATIONS:

  • Embrace AI tools to enhance mathematical problem-solving and explore new research avenues.
  • Actively participate in mathematical conferences to foster collaboration and share ideas with peers.
  • Leverage formal proof assistants to streamline the verification process of complex mathematical proofs.
  • Engage with interdisciplinary teams to solve complex mathematical problems effectively.
  • Experiment with machine learning to discover unexpected connections in mathematical data.
  • Approach mathematical research with flexibility, being open to changing topics and ideas.
  • Utilize collaborative project management techniques to break down large proofs into manageable tasks.
  • Maintain foundational knowledge in mathematics to effectively guide AI and machine learning tools.
  • Seek mentorship throughout educational and research journeys to gain valuable insights and guidance.
  • Keep a record of successful problem-solving techniques to reference in future research endeavors.

gpt4 on probability problems (part 3)

A, B, and C are to fight a three-cornered pistol duel. All know that A’s chance of hitting his target is 0.3, C’s is 0.5, and B never misses. They are to fire at their choice of target in succession in the order A, B, C, cyclically (but a hit man loses further turns and is no longer shot at) until only one man is left unhit. What should A’s strategy be?

  1. If A shoots and hits either B or C, then the remaining two players will fight a regular duel. Since B never misses, B would win against either A or C. So, eliminating one player is not advantageous for A.
  2. If A intentionally misses his first shot, then B and C will have their turns. B knows that C is a more dangerous opponent because C’s probability of hitting the target is 0.5, while A’s is only 0.3. Therefore, B should target C, and if B hits C, the duel becomes a one-on-one match between A and B.

In the one-on-one duel, A has the first shot against B. A has a 0.3 chance of hitting B and surviving the duel. If A misses, B will shoot and win since B never misses. Therefore, A’s overall chance of winning the duel is 0.3 when he intentionally misses his first shot, which is better than the alternative of targeting either B or C in the beginning.

The answer is correct

coupon in cereal boxes are numbered 1 to 5, and a set of one of each is required for a price. with one coupon per box, how many boxes on the average are required to make a complete set?

Let’s break down the process of collecting a complete set of coupons:

  1. The first coupon: Since you don’t have any coupons yet, you are guaranteed to get a unique coupon in the first box. The expected number of boxes to get the first coupon is 1.
  2. The second coupon: The probability of getting a new coupon is 4/5 (since there are 4 new coupons you don’t have yet). The expected number of boxes to get the second coupon is 1 / (4/5) = 5/4.
  3. The third coupon: The probability of getting a new coupon is 3/5 (since there are 3 new coupons you don’t have yet). The expected number of boxes to get the third coupon is 1 / (3/5) = 5/3.
  4. The fourth coupon: The probability of getting a new coupon is 2/5 (since there are 2 new coupons you don’t have yet). The expected number of boxes to get the fourth coupon is 1 / (2/5) = 5/2.
  5. The fifth coupon: The probability of getting the last coupon is 1/5 (since there is only 1 new coupon you don’t have yet). The expected number of boxes to get the fifth coupon is 1 / (1/5) = 5.

To find the expected number of boxes needed to complete the set, we add the expected number of boxes for each unique coupon:

Expected number of boxes = 1 + 5/4 + 5/3 + 5/2 + 5 = 1 + 1.25 + 1.67 + 2.5 + 5 ≈ 11.42

On average, you would need to buy approximately 11.42 boxes to collect a complete set of coupons numbered 1 to 5.

This answer is correct again.

A 1-meter stick is randomly broken into 4 pieces, what is the expected length of the shortest piece?

Let’s represent the break points on the stick as X1, X2, and X3, which are random variables uniformly distributed between 0 and 1. We can arrange these break points in ascending order, such that X1 <= X2 <= X3. Now, the stick is divided into 4 pieces with lengths Y1 = X1, Y2 = X2 – X1, Y3 = X3 – X2, and Y4 = 1 – X3.

We are interested in the expected value of the minimum length, which is given by min(Y1, Y2, Y3, Y4). To calculate the expected value of the shortest piece, we can find the expected value of each piece and then average them. Since the breaking points are uniformly distributed, the expected value of each piece is symmetric.

For the first piece, Y1 = X1, the expected value is:

E(Y1) = E(X1) = 1/4

For the second piece, Y2 = X2 – X1, the expected value is:

E(Y2) = E(X2) – E(X1) = 1/2 – 1/4 = 1/4

Similarly, for the third piece, Y3 = X3 – X2, the expected value is:

E(Y3) = E(X3) – E(X2) = 3/4 – 1/2 = 1/4

And for the fourth piece, Y4 = 1 – X3, the expected value is:

E(Y4) = 1 – E(X3) = 1 – 3/4 = 1/4

Now we can average the expected values of each piece to find the expected value of the shortest piece:

E(min(Y1, Y2, Y3, Y4)) = (E(Y1) + E(Y2) + E(Y3) + E(Y4)) / 4

E(min(Y1, Y2, Y3, Y4)) = (1/4 + 1/4 + 1/4 + 1/4) / 4

E(min(Y1, Y2, Y3, Y4)) = 1/4

So, the expected length of the shortest piece when a 1-meter stick is randomly broken into 4 pieces is 0.25 meters or 25 cm.

The answer is incorrect and I asked a similar question earlier and it is still wrong.

Quaternion explanation

A wonderful explanation of why $latex q p q^{-1}$ is rotation of $latex p$, where $latex q$ is most easily interpreted with the complex-number like structure of $latex \cos(\theta/2) + \sin(\theta/2)(a i + b j + c k)$ with $latex a i + bj +ck$ normalized (i.e., $latex a^2+b^2+c^2=1$). Note that $latex q^{-1}$ is then just $latex latex \cos(\theta/2) – \sin(\theta/2)(a i + b j + c k)$ (since $latex (a i + b j + c k)^2=-a^2 – b^2 -c^2 = -1$ just like the imaginary $latex i$ for complex number).

Basically quarternion is 4D stereographic projection back to 3D space. When multiply by a quarternion $latex \cos(\alpha) + \sin(\alpha) {\bf v}$ from the left, points parallel to $latex \bf v$ will be translate along $\bf v$ and points penpendicular to $latex \bf v$ will rotate around $latex \bf v$ (following the right hand rule). Similarly, when multiplying from the right by the same quarternion, points parallel to $latex \bf v$ will be translated in the same direction, but points perpendicular to $latex \bf v$ will be rotated in the opposite direction (following left hand rule). So if we multiple $latex q$ and $latex q^{-1}$ from both left and right hand sides, the translation effect will be exactly cancelled, and the the rotation will be doubled. That is why the angle in $latex q$ should be halved.

Copyright OU-Tulsa Lab of Image and Information Processing 2024
Tech Nerd theme designed by Siteturner