25Jan / 2022

Optimized Wordle solver

In case you’re not so good with the words, but feel the social pressure to play Wordle bearing down on you, Jonathan Olson made an optimized solver:

The game Wordle has a lot of speculation online about what is the “best” first word. If we are exploring optimal strategies to solve the original game in the least number of guesses, most of it is wrong.

For humans, almost all of these words are great! However for optimal strategies, we need to examine all of the guesses, not just the first word. It turns out, it’s possible to solve 99% of all puzzles in only 4 guesses or with an average of ~3.42 guesses per win, but not with most of the “best” words found online.

I don’t play because I am a not-so-good-with-words person, but also there can only be one true Wordle.

Tags: game, Jonathan Olson, optimization, Wordle

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12Nov / 2021

Optimizing retail spaces

Patrick Sisson for The New York Times reports on the growing popularity of tracking customer movement in stores:

Complicating efforts to address privacy concerns is a lack of regulatory clarity. Without an overarching federal privacy law or even a shared definition of personal data, retailers must sort through layers of state and municipal rules, such as California’s Consumer Privacy Act, said Gary Kibel, a partner at the law firm Davis+Gilbert who specializes in retail privacy.

Technology companies counter the pushback by noting that their systems are designed to limit what they collect and anonymize the rest. For instance, Standard AI’s system does not capture faces, so they cannot be analyzed with facial recognition technology.

Uh huh.

Tags: New York Times, optimization, privacy, retail, shopping

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30Aug / 2021

Repulsive curves

Chris Yu, Henrik Schumacher, and Keenan Crane from Carnegie Mellon University are working on repulsive curves, which is a method to efficiently unravel curves so that they don’t overlap:

Curves play a fundamental role across computer graphics, physical simulation, and mathematical visualization, yet most tools for curve design do nothing to prevent crossings or self-intersections. This paper develops efficient algorithms for (self-)repulsion of plane and space curves that are well-suited to problems in computational design. Our starting point is the so-called tangent-point energy, which provides an infinite barrier to self-intersection. In contrast to local collision detection strategies used in, e.g., physical simulation, this energy considers interactions between all pairs of points, and is hence useful for global shape optimization: local minima tend to be aesthetically pleasing, physically valid, and nicely distributed in space.

Be sure to watch the video demo.

Tags: curves, optimization, research

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25Aug / 2020

Optimizing a peanut butter and banana sandwich

How do you assemble a banana and peanut butter sandwich that maximizes the number of bites with the perfect ratio of bread, peanut butter, and banana? Ethan Rosenthal, in a quest to work on something truly meaningless, solved the problem over several months with a truly roundabout solution:

So, how do we make optimal peanut butter and banana sandwiches? It’s really quite simple. You take a picture of your banana and bread, pass the image through a deep learning model to locate said items, do some nonlinear curve fitting to the banana, transform to polar coordinates and “slice” the banana along the fitted curve, turn those slices into elliptical polygons, and feed the polygons and bread “box” into a 2D nesting algorithm.

Best.

Tags: deep learning, optimization, sandwich

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Category Archives: optimization

Optimized Wordle solver

Optimizing retail spaces

Repulsive curves

Optimizing a peanut butter and banana sandwich

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