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Homemade chess board moves its own pieces. And wins.
Technology AI Homemade chess board moves its own pieces. Maker Joshua Stanley Robotics used magnets and an open source chess platform to build this unique board. Breakthroughs, discoveries, and DIY tips sent six days a week. It's been nearly 30 years since chess champion Garry Kasparov lost to IBM's Deep Blue, marking the first time a reigning world champion was defeated by a computer in a match. Chess engines have since improved so dramatically that even a simple smartphone app can now make top grandmasters sweat .
Reawakening knowledge: Anticipatory recovery from catastrophic interference via structured training Y anlai Y ang 1, Matt Jones
The behavior emerges and becomes more robust as the architecture scales up its number of parameters.
UniBench: VisualReasoningRequiresRethinking Vision-LanguageBeyondScaling
Wefind that while scaling training data ormodel size can boost many vision-language model capabilities, scaling offers little benefit for reasoning or relations. Surprisingly, we also discover today's best VLMs struggle on simple digit recognition and counting tasks, e.g. MNIST, which much simpler networks can solve.
Adapting Fairness Interventions to Missing Values
Missing values in real-world data pose a significant and unique challenge to algorithmic fairness.
Re-Think and Re-Design Graph Neural Networks in Spaces of Continuous Graph Diffusion Functionals Tingting Dan
Since the PDE in Eq. 5 in the main manuscript is equivalent to the E-L equation of the quadratic
Generalizing CNNs to Graphs with Learnable Neighborhood Quantization
Many important real-world scenarios involve data structured as graphs.