Compilation··3:30·Theoretical computer science
Unique Games Conjecture, Bin Packing and 8 More in Theoretical Computer Science
Watch on YouTubeAbout the problem →
About this video
10 results from OpenAI's public mathematics catalogue, one per chapter. Each chapter names the problem, shows the real objects, and states what OpenAI claims; none of it is peer reviewed yet.
Chapters:
0:00 Unique Games Conjecture
0:21 2-to-1 Games Conjecture
0:42 Coloring 3-Colorable Graphs
1:04 Permanent vs Determinant
1:25 Randomized k-Server Problem Solved
1:47 Matroid Prophet Inequality
2:07 Noncommutative Identity Testing
2:28 Bin Packing
2:49 Maximum Matching in Almost Linear Time, Any Graph
3:09 Edit Distance
Unique Games Conjecture: Max-Cut asks you to split a network's dots into two teams so that as many lines as possible join opposite teams.
Explained: gradientdamage.com/p/102
Paper: github.com/openai/math/blob/main/preprints/The-Unique-Games-T…
2-to-1 Games Conjecture: In a 2-to-1 game every dot gets a label, and each link has a rule that sends two labels on one side to one label on the other.
Explained: gradientdamage.com/p/105
Paper: github.com/openai/math/blob/main/preprints/Perfect-completene…
Coloring 3-Colorable Graphs: A graph is 3-colorable if its dots can be given three colors so that no link joins two dots of the same color.
Explained: gradientdamage.com/p/106
Paper: github.com/openai/math/blob/main/preprints/Hardness-of-findin…
Permanent vs Determinant: The determinant of a matrix is fast to compute; the permanent (the same sum with every sign a plus) is believed to be hard.
Explained: gradientdamage.com/p/108
Paper: github.com/openai/math/blob/main/preprints/A-cubic-lower-boun…
Randomized k-Server Problem Solved: k taxis, calls arriving one at a time, and no view of the future: how close can you get to the best plan in hindsight? The randomized k-server conjecture guessed a factor of log k.
Explained: gradientdamage.com/p/110
Paper: github.com/openai/math/blob/main/preprints/Squared-logarithmi…
Matroid Prophet Inequality: Values arrive one at a time and you must keep or discard each on the spot, while a prophet who sees everything picks the best set.
Explained: gradientdamage.com/p/111
Paper: github.com/openai/math/blob/main/preprints/One-Sample-Suffice…
Noncommutative Identity Testing: With numbers, (x+y)(x−y) always equals x² − y², but with matrices, where xy ≠ yx, it does not.
Explained: gradientdamage.com/p/116
Paper: github.com/openai/math/blob/main/preprints/Uniform-Matrix-Hit…
Bin Packing: Bin packing asks how few boxes of size 1 can hold a list of items.
Explained: gradientdamage.com/p/118
Paper: github.com/openai/math/blob/main/preprints/Additive-hardness-…
Maximum Matching in Almost Linear Time, Any Graph: A matching pairs up dots along edges so that no dot is used twice.
Explained: gradientdamage.com/p/120
Paper: github.com/openai/math/blob/main/preprints/Almost-Linear-Time…
Edit Distance: The edit distance between two strings is the fewest inserts, deletes and swaps that turn one into the other.
Explained: gradientdamage.com/p/121
Paper: github.com/openai/math/blob/main/preprints/An-Almost-Linear-A…
The animations illustrate the results; they are not proofs.
Gradient Damage: mathematics you can see, equations you can hear.
youtube.com/@gradientdamage
Chapters
One problem per chapter. Each name links to the result's own page, each time to that moment on YouTube.
- Unique Games Conjecture Theoretical computer science
- 2-to-1 Games Conjecture Theoretical computer science
- Coloring 3-Colorable Graphs Theoretical computer science
- Permanent vs Determinant Theoretical computer science
- Randomized k-Server Problem Solved Theoretical computer science
- Matroid Prophet Inequality Theoretical computer science
- Noncommutative Identity Testing Theoretical computer science
- Bin Packing Theoretical computer science
- Maximum Matching in Almost Linear Time, Any Graph Theoretical computer science
- Edit Distance Theoretical computer science
Chapter 1: about the problem
Theoretical computer science·OpenAI Math·Result 102
The Unique Games Conjecture and optimal approximation thresholds
Proves Khot's Unique Games Conjecture. Independent direct reductions also establish NP-hardness, on unweighted graphs, of approximation beyond the Goemans–Williamson ratio for Max-Cut, below factor two for Vertex Cover, and within any fixed constant factor for Min-UnCut and directed feedback vertex set. These direct proofs use established PCP and Label Cover hardness results. (Lean)
Chapter 2: about the problem
Theoretical computer science·OpenAI Math·Result 105·from 0:21
Perfect completeness for 2-to-1 games
Proves Khot's 2-to-1 Games Conjecture with perfect completeness: for every fixed rational δ ∈ (0,1), it is NP-hard to distinguish satisfiable games from games whose optimum is at most δ, on explicit unweighted instances. The alphabet depends only on δ, and every right-hand label has exactly two preimages under each constraint map. (Lean)
Chapter 3: about the problem
Theoretical computer science·OpenAI Math·Result 106·from 0:42
Hardness of coloring three-colorable graphs
It is NP-hard to color a three-colorable graph using any fixed number c ≥ 3 of colors. More strongly, for every fixed 0 < δ < 1/3, a deterministic polynomial-time reduction from 3SAT produces simple unweighted graphs that are three-colorable in the satisfiable case and have no independent set of size δ n otherwise, where n is the number of vertices. (Lean)
Chapter 4: about the problem
Theoretical computer science·OpenAI Math·Result 108·from 1:04
A cubic permanent–determinant lower bound
Proves an Ω(n3) lower bound for the border determinantal complexity of the n× n permanent over ℂ. Even coefficientwise limits of determinants of affine-linear matrices require matrix size at least cn3, for an absolute c > 0 and all sufficiently large n; the same bound therefore holds for exact representations. (Lean)
Chapter 5: about the problem
Theoretical computer science·OpenAI Math·Result 110·from 1:25
Optimal-order randomized k-server on arbitrary metrics
Establishes a randomized competitive ratio O(log2(k+1)) for k-server on every metric space, matching the worst-case lower-bound order. One policy serves every finite oblivious request sequence, including on infinite unbounded metrics. On finite rational metrics, a uniform implementation has polynomial preprocessing and per-request bit cost in the input length and log(t+1) at request t, with a finite instance-dependent additive movement constant. (Lean)
Chapter 6: about the problem
Theoretical computer science·OpenAI Math·Result 111·from 1:47
One-sample matroid prophet inequalities against an almighty adversary
For every finite matroid known in advance, gives a distribution-independent online rule using one independent sample per element and earning a universal constant fraction of the expected offline optimum. Values are independent and nonnegative, with finite expected optimum. The guarantee holds even when the arrival-order adversary sees all samples, values, and the rule's entire random seed; no polynomial-time implementation is asserted. (Lean)
Chapter 7: about the problem
Theoretical computer science·OpenAI Math·Result 116·from 2:07
Uniform black-box noncommutative identity testing across characteristics
For each characteristic, constructs in deterministic polynomial bit time a polynomial-dimensional matrix tuple detecting every nonzero division-free noncommutative formula of bounded size over any field of that characteristic. Rational formulas over ℚ also admit polynomial-size hitting lists whenever they have a defined rational-matrix evaluation. (Lean)
Chapter 8: about the problem
Theoretical computer science·OpenAI Math·Result 118·from 2:28
Bin packing and unbounded configuration-LP gaps
Disproves the modified integer round-up conjecture of Scheithauer and Terno: the integral bin-packing optimum can exceed its configuration linear-programming value by an arbitrarily large additive constant. Approximating the optimum within any fixed additive constant is also NP-hard, even when every item exceeds 1/6 and each bin holds at most five items. (Lean)
Chapter 9: about the problem
Theoretical computer science·OpenAI Math·Result 120·from 2:49
Almost-linear-time exact matching and prescribed-degree factors in general graphs
Gives a randomized algorithm finding an exact maximum-cardinality matching in any simple undirected graph in (n+m)1+o(1) word time, with success probability at least 2/3. The time bound holds on every computation path. The same guarantees apply to finding a spanning subgraph with prescribed admissible vertex degrees, or deciding that none exists.
Chapter 10: about the problem
Theoretical computer science·OpenAI Math·Result 121·from 3:09
Almost-linear approximation of edit distance
For every fixed rational ε ∈ (0,1), gives a randomized (1+ε) approximation to unit-cost edit distance in worst-case expected time N1+o(1), with success probability at least 2/3. The strings have total length N and polynomially bounded integer symbols. This is an asymptotic guarantee at fixed accuracy. (Lean)
Topics
unique games conjecture2-to-1 games conjecturegraph coloringpermanent vs determinantk-server problemprophet inequalitypolynomial identity testingbin packingmaximum matchingedit distanceTheoretical computer scienceOpenAI mathAI proofAI mathematicsmathsGradient Damage