Director of Analytics. Runner and Comrades finisher (56 miles/89kms). Two teen boys. Mediocre but passionate chess player (USCF 1594 and counting) #chesspunks
Let me explain exactly why every new subdivision in America looks like the top photo, because the math is wild.
A mature tree increases a home's value by 7 to 19 percent. On a $400,000 house, that's $28,000 to $76,000. A single shade tree produces the cooling equivalent of ten room-size air conditioners running 20 hours a day. One tree on the west side of a house cuts energy bills by 12 percent within 15 years. The bottom photo is worth more, costs less to live in, and sells faster. This has been documented by the University of Washington, Clemson, Michigan State, and the USDA. The data is not in dispute.
Removing those trees saves the builder roughly $5,000 per lot. Concrete trucks need twice the dripline radius of every standing tree. Utility trenches need flat ground. A bulldozer flattens 200 lots in an afternoon. Preserving trees adds weeks and thousands per home.
So the developer pockets $5,000 in savings and the buyer eats $50,000 in lost value for the next two decades. The person making the decision and the person paying for it have never been in the same room.
The Woodlands, Texas is the proof of what happens when they are. George Mitchell bought 28,000 acres of Houston timberland in 1974 and preserved 28% as permanent green space. He forced McDonald's to build behind the tree canopy. That McDonald's became one of the highest-volume locations in Texas. The first office building, designed to reflect the surrounding forest so you couldn't see it from the street, leased completely.
The Woodlands median home price today: $615,000. Katy, a comparable Houston suburb that clear-cut: $375,000. Named #1 community to live in America two years running.
Fifty years of data. The trees are worth more than removing them saves. Developers clear-cut anyway because they sell the house once and leave. You live in it for 30 years.
I am excited to share a work we did in the Discovery team at @GoogleDeepMind using RL and generative models to discover creative chess puzzles 🔊♟️♟️ #neurips2025
🎨While strong chess players intuitively recognize the beauty of a position, articulating the precise elements that constitute creativity remains elusive. To address this, we pre-trained generative models on public datasets and then applied reinforcement learning, using novel rewards designed for uniqueness, counter-intuitiveness, realism, and novelty. This approach doubled the number of novel chess puzzles compared to the original training data, while successfully maintaining aesthetic diversity.
Three distinguished experts—International Master of chess compositions Amatzia Avni (author of "Creative Chess"), Grandmaster Jonathan Levitt @JonathanLevitt7 (author of "Secrets of Spectacular Chess"), and Grandmaster Matthew Sadler @gmmds (author of "Game Changer")—evaluated and selected the puzzles they found most compelling. Their preference was for puzzles exhibiting original, paradoxical, surprising, and naturally occurring positions, with particular emphasis on those that integrated aesthetic themes in innovative ways and demonstrated exceptional over-the-board vision.
🧩Try to solve the puzzles @chesscom: https://t.co/qHxXiWC427
@thechessnerd The first time I played a tournament in Atlanta, in the middle of a round, a women started screaming at her son at the top of her lungs out in the lobby. The guy next to me shrugged and went: “O no, not again.” Apparently this mom just got really angry when her kid lost. Insane.
Hey everyone - I’m teaching at an adult chess camp before the ALTO tournament in Charlotte. I encourage you all to join the camp and play in ALTO (adults only). Info on the camp here: https://t.co/4kG2xCPO1V
@ImShahinyan I love this! So many of these are so interesting and so true. I am wondering - how easy is it to find references for these? Would love to quote some of these!