We Will All Write Like AI

Will our writing all converge to a generic AI style? 

Let's take a quick detour into LaTeX. Back in the late '80s, before LaTeX was the standard, there was TeX—a system with no default formatting, which meant everyone had their own unique style for papers. Then LaTeX arrived, and suddenly all our papers looked polished and professional. But the catch was, LaTeX only got you about 80% of the way there. The original manual even mentioned that you needed to add some extra TeX commands to really finish the job. Most of us didn’t bother, though, and soon all our papers had that same uniform look. It was efficient, and it was good enough. Microsoft Word ended up doing the same thing for everyone else—you could tweak it to be different, sure, but most people didn’t. It turns out most of us are just fine with "good enough."

I generally don't like to use large language models to write for me. But I do use them to refine my work, to catch errors or suggest improvements. The thing is, AI likes to take what I write and make it sound smoother, and I often think, "Wow, that really does sound better." But here’s the tricky part: it might be better, but it’s not mine. It’s the AI's voice. And still, if the stakes aren’t too high, sometimes I let the AI’s version slide. That’s the start of a slippery slope. Before you know it, we’re all letting AI make our writing a bit more generic, a bit more uniform. And eventually, we end up writing to match the AI’s preferred style.

For this blog post, I didn’t resist at all. Could you tell this is ChatGPT's style?

For what d is the following true: For all 2-colorings of \(R^d\) has a mono unit square (Answering(?) the Question)

 In my last post (see here) I invited you to work on the following question:

Find a \(d\) such that

--There is a 2-coloring of \(R^d\) with no mono unit square.

--For all 2-colorings of \(R^{d+1}\) there is a mono unit square. 

Actually I should have phrased my question as What do we know about d?  

Here is what we know

a) \(d \ge 2\).  There is a 2-coloring of  \(R^2\) with no mono unit square. This is easy and I leave to you. 

b) \(d\le 5\). For all 2-colorings of \(R^6\) there is a mono unit square. I will give pointers to the relevant papers and to my slides later in this post.

c) \(d\le 4\). For all 2-colorings of \(R^5\) there is a mono unit square. This is by an observation about the proof for \(R^6\). It will be in the slides about \(R^6\).

d) \(d\le 3\). This is in a paper that the reader Dom emailed me a pointer to. Dom is better at Google Search than I am. The link is here.

MY SLIDES:

\(K_6\) is the complete graph on 6 vertices. We will be looking at 2-colorings of its edges

\(C_4\) is the cycle on 4 vertices. A mono \(C_4\) has all four edges the same color.

We need a result by Chvtal and Harary in this paper here.

Lemma: For all 2-colorings of the edges of \(K_6\) there is a mono \(C_4\).

The proof appears both in their paper,  here, and on slides I wrote here. 

Stefan Burr used this to prove the following theorem.

Thm: For all 2-colorings of \(R^6\) there is a mono unit square. 

The proof was appears (with credit given to Stefan Burr) in a paper by Erdos, Graham, Montgomery, Rothchild, Spencer, Straus, here, and on slides I wrote here.

Random Points

1) It is open what happens in \(R^3\). 

2) The proof for \(R^6\) uses very little geometry. Dom had a proof for \(R^6\) in a comment on my last post that used geometry. The proof for \(R^4\) uses geometry. 

3) An ill-defined open question: Find a proof that every 2-coloring of \(R^4\) has a mono unit square that does not use that much geometry and so I can make slides about it more easily.

For what d is the following true: for all 2-colorings of \(R^d\) there is a mono unit square (Asking the Question)

 In this post I give a question for you to think about. 

My next post will have the answer and the proof. 

1) The following are known and I have a set of slides about it here

a) For all 2-colorings of \(R^2\) there exists two points an inch apart that are the same color. (You can do this one.)

b) For all 3-colorings of \(R^2\) there exists two points an inch apart that are the same color. (You can do this one.)

c) For all 4-colorings of  \(R^2\) there exists two points an inch apart that are the same color. (You cannot do this one.) 

2) SO, lets look at other shapes

A unit square is  square with all sides of length 1.

Given a coloring of \(R^d\) a mono unit square is a unit square with all four corners the same color. 

a) There is a 2-coloring of \(R^2\) with no mono unit square. (You can do this one.)

b) What is the value of d such that 

-- There is a 2-coloring of  \(R^d\) with no mono unit square.

-- For all 2-colorings of \(R^{d+1}\) there is a mono unit square. 

My next post will tell you what is known about this problem.

Until then, you are invited to think about it and see what you can find out. Perhaps you will get a better result then what is known since you are untainted by conventional thinking. Perhaps not. 

Feel free to leave comments. However, if you don't want any hints then do not read the comments.

Favorite Theorems: Learning from Natural Proofs

October Edition

I had a tough choice for my final favorite theorem from the decade 2015-2024. Runners up include Pseudodeterministic Primes and Hardness of Partial MCSP.  But instead in memory of the recently departed Steven Rudich, this month's favorite theorem shows how to learn circuit classes that have a natural proof of hardness.

Learning Algorithms from Natural Proofs

Marco L. Carmosino, Russell Impagliazzo, Valentine Kabanets and Antonina Kolokolova

In 1993, Linial, Mansour and Nisan showed that any function f computed by a constant-depth polynomial-size AND-OR-NOT circuits (AC⁰), has a quasipolynomial-time PAC learning algorithm that, after seeing a quasipolynomial number of uniformly randomly chosen inputs x and their value f(x), can with high probability predict f on other randomly chosen inputs. Their proof works by looking a the Fourier basis of f, showing that learning the low-degree coefficients gives a good approximation to f. Their paper was one of the first to apply Fourier transformations to computational complexity. Adam Klivans did a guest post on this paper back in 2004.

Now, suppose we allow unbounded parity gates to the circuit. The Fourier argument falls apart and learning such circuits remained open for over a quarter century until the Carmosino et al. paper. Their paper uses a different technique, building on the proof of the Nisan-Wigderson pseudorandom generator function. They show that if a circuit class has a natural proof of hardness, the constructivity and largeness properties of the natural proof can break a pseudorandom generator for that class, which can then be used to create a learning algorithm. 

The authors then applied the Razborov and Rudich naturalization of Razborov and Smolensky's lower bounds for AC⁰ with parity gates to get a quasipolynomial learning algorithm for that circuit class.

Steven Rudich (1961-2024)

Complexity theorist Steven Rudich passed away on October 29 at the age of 63. His works on Natural Proofs and Program Obfuscation were both highly influential. Russell Impagliazzo had a great result with him on showing that one-way permutations alone isn't enough to get secret key-exchange.

I started graduate school in 1985 at Berkeley and Steven was the unofficial student leader of the theory group when I arrived and I got a taste of his optimistic style before I moved to MIT the following summer. I'd see Rudich at various conferences and during visits to each other's institutions. I first learned about natural proofs from a talk he gave at the University of  Chicago and we had many debates about its importance for years. Alas health issues took their toll and we lost one of the great researchers and personalities in our field.

Impagliazzo has been a friend and colleague of Steven's since they were both undergrads at Wesleyan and we asked him to write a guest post about Steven. Russell sent us a very honest and personal 7-page writeup. Too long for a blog post but I strongly recommend reading this powerful story. Also see Scott Aaronson's memories.

Higher Education Under Trump

It feels eerie as pretty much everyone seemingly avoided talking about the election. But Trump back in the White House will likely have a profound effect on US Colleges and Universities. Trump is no fan of universities and his vice-president once proclaimed "the professors are the enemy". 

While most US universities act outside of federal control, almost all of them take Federal funds in scholarships and grants and Trump could use that as a lever to push his policies.

Now Trump is always unpredictable and the courts could step in but here is what could happen.

International Students

I still remember Trump's ban on Iranians in the US and what it meant to our students and faculty at Georgia Tech. While that thankfully got blocked by the courts, who knows what will happen in this next administration.

International students at all levels in higher ed play a major role in increasing both the intellectual and financial strengths of universities. International Students, especially from some countries like China, may have a harder time coming to or staying in the US under a Trump administration or may have less desire to do so.

On the other hand last June Trump said "What I want to do and what I will do is, you graduate from a college, I think you should get automatically, as part of your diploma, a Green Card to be able to stay in this country." If that's true that will greatly increase interest among foreign students but I doubt he will carry it out.

Student Loan Forgiveness

Not going to happen

Title IX

University Title IX offices get whiplash with each change of administration. Expect Title IX (sex discrimination) protections to be watered down and eliminated for transgender individuals. 

Look at Republican States

Trump may try to apply Republican policies at state universities to all universities as a whole: Dismantling DEI efforts, weakening tenure protection, allowing campus carry of guns on campus, and "free speech" policies while limiting what can be taught and cracking down on protests.

Accreditation

Trump and republicans are no fan of accreditation, and Trump has threatened that he will replace accreditors to enforce certain points of view.

A new Mersenne Prime Has Been Found. When will we find the next one?

(Lance posted on the search for Mersenne primes in 2006 after a new one was discovered. I will comment on his post later. ADDED LATER- You Tube Video by Matt Parker on the new prime, here)

A Mersenne Prime is a prime of the form \(2^n-1\) where n is a natural number. One can show that n must be a prime. There is a list of all known Mersenne primes here. A more complete list of large primes going back to 1456 (which is not prime) when they discovered that 8191 is prime, is here.

New Mersenne primes were found in 

1985

1992 (so a 7 year gap)

1994

1996

1997

1998

1999

2001

2003

2004

2005

2005 (wow, two in one year!)

2006

2008

2008 (wow, two in one  year!)2009

2013 (so a 5 year gap)

2016

2017

2018

2024 (so a 6 year gap)

When will the next one be? Possibilities:

a) The techniques that got us to the one in 2024 are NEW and will be USED to get us some new ones soon. 

b) The techniques that got us to the one in 2024 were the old techniques on their last legs. A new idea is needed either from number theory, algorithms, or hardware. So we may not find one for a while.

I do not know which of (a) or (b) is closer to the truth. It may be hard to tell. 

There are two obstacles for making progress on numbers like this.

a) Technology, math, etc.

b) Sociology. Do enough people care about finding these numbers? 

AND these two obstacles can interact to give you either

a)  a death spiral: the problem is to hard so people don't want to work on it, and people don't want to work on it because the problem is to hard or

b) a live spiral: a breakthrough was made so lets all now really go for it!

I do not know how Mersenne primes do in this context. 

In 2006 Lance's post raised the question Why Do We Care About Finding Large Primes? 

a) We don't. Not that many people are working on this.  

b) The actual primes aren't that interesting, but the techniques used to find them might be. 

c) Why do people climb mountains?

Because they like getting frostbite!

Better off finding primes which you can do without risking life and limb. 

d) As someone who has worked on proving primes infinite using Ramsey Theory I am reluctant to tell someone else that there work is not worthwhile. I blogged on using Ramsey Theory to Proof the number of primes is infinite  here.

e) I leave the following as an open problem: Compare and contrast value and interest in finding the following:

Large Merseene Prime

Largest non-Mersenne Prime. Mersenne primes are easier to find, so most known large primes are Mersenne. Finding large non-Mersenne primes has been looked at, see here, but not much.

The Busy Beaver Function . Scott did a post on the new breakthrough here.

Small Universal Turing Machines. I did a blog post on that here. There is a cash prize for it!

Ramsey Numbers, in particular R(5). I did a blog post on the new breakthrough here.