value function
Beyond Market Intelligence keeps value function in one place: 2 stories so far. The section currently leads with “Explore a Billion Chess Positions to Transform How You Analyze Data” and “Building smarter AI for puzzle games with previewed chance and stack constraints”. Analyzing a billion chess positions isn't just about winning games, it's a compelling experiment in data compression. Planning an AI around previewed chance events and long-horizon throughput is a sharp problem, and the trade-offs are framed clearly. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work… The list below is every value function story on Beyond Market Intelligence, newest first.
Explore a Billion Chess Positions to Transform How You Analyze Data
Analyzing a billion chess positions isn't just about winning games, it's a compelling experiment in data compression. One developer trained a vision transformer on Stockfish's evaluations, holding search depth constant to test if a neural net could approximate the tree beneath it. The vision transformer was slow, but a CNN offered geometric advantages. The real power came from combining them. For more on how models learn to copy context efficiently, see our piece on hash tables.
Building smarter AI for puzzle games with previewed chance and stack constraints
Planning an AI around previewed chance events and long-horizon throughput is a sharp problem, and the trade-offs are framed clearly. Separating deterministic afterstates from explicit chance nodes, paired with a policy/value network and PUCT, feels like the right structural instinct, especially given the preview-conditioned fourth action. Their honest reporting on what failed, like Q-head calibration and exhaustive leaf maximization, is more useful than most success stories.