So, you know, after the US and Iran had a little family fallout following those joint Israeli strikes, the markets got all jittery. Oil prices did a jitterbug, and the risk-takers straightened up like a pigeon dropping its confetti at a funeral.
Disc Creatures World is a game where you collect over 300 unique creatures, store them on special Discs, and then battle with teams of three. It’s a revamped version of the original Disc Creatures game, previously released by Picorinne and Dangen on Steam in 2019, but with updated graphics and gameplay.
Kalshi, that titan of regulated prediction markets, has set its sights beyond the familiar, embarking on a voyage of international expansion. One might say it has grown weary of the comforts of home and seeks the thrill of foreign shores.
Cygames announced on Steam that you’ll need a new account to play Granblue Fantasy on Steam – your existing Granblue Fantasy account won’t work. However, it will work with your Cygames ID. Check out the special artwork created to celebrate the Steam release below!
Falcom Acoustics 3, featuring 12 songs, is now available to stream and buy digitally! You can listen on platforms like Spotify and Apple Music (which supports high-quality lossless audio), and you can find links to all the services here.
A new study dissects the unique challenges of building reliable, self-directed AI systems, identifying patterns of failure distinct from traditional software.
The studio released a launch trailer for the game on YouTube to mark the occasion. The trailer is available in English, Japanese, Korean, and Simplified Chinese.
Throughout the first season of One Piece, Monkey D. Luffy gathered his crew, the Straw Hat Pirates, as he set out to find the legendary treasure and achieve his dream of becoming the Pirate King.
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![Symbolic forecasting architectures-specifically, a differentiable neural network (SyNF) and an evolutionary-search-based tree constructor (SyTF)-demonstrate the capacity to distill complex time-series data into interpretable equations, such as [latex] \hat{y}\_{t}=0.1110+0.9421y\_{t-1}+0.0001\left(y\_{t-1}\right)^{2} [/latex] for SyNF and [latex] \hat{y}\_{t,\text{SyTF}}=0.9613y\_{t-1} [/latex] for SyTF, effectively reverse-engineering predictive dynamics from a simulated dataset using only lagged observations.](https://arxiv.org/html/2603.07261v1/Symbolic_Forecasting_Model_Architecturre.png)
New research demonstrates how symbolic machine learning can unlock interpretable models from complex, chaotic time series data.
