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We introduce PokéChamp, a minimax agent powered by Large Language Models (LLMs) for Pokémon battles. Built on a general framework for two-player competitive games, PokéChamp leverages the generalist capabilities of LLMs to enhance minimax tree search. Specifically, LLMs replace three key modules: player action sampling, opponent modeling, and value function estimation, enabling the agent to effectively utilize gameplay history and human knowledge to reduce the search space and address partial observability. Notably, our framework requires no additional LLM training. We evaluate PokéChamp in the popular Gen 9 OU format. When powered by GPT-4o, it achieves a win rate of 76% against the best existing LLM-based bot and 84% against the strongest rule-based bot, demonstrating its superior performance. Even with an open-source 8-billion-parameter Llama 3.1 model, PokéChamp consistently outperforms the previous best LLM-based bot, Pokéllmon powered by GPT-4o, with a 64% win rate. PokéChamp attains a projected Elo of 1300–1500 on the Pokémon Showdown online ladder, placing it among the top 30%-10% of human players. In addition, this work compiles the largest real-player Pokémon battle dataset, featuring over 3 million games, including more than 500k high-Elo matches. Based on this dataset, we establish a series of battle benchmarks and puzzles to evaluate specific battling skills. We further provide key updates to the local game engine. We hope this work fosters further research that leverage Pokémon battle as benchmark to integrate LLM technologies with game-theoretic algorithms addressing general multiagent problems. Videos, code, and dataset available at this https URL.

Nowadays, if you have a microscope, you probably have a camera of some sort attached. [Applied Science] shows how you can add an array of tiny LEDs and some compute power to produce high-resolution images — higher than you can get with the microscope on its own. The idea is to illuminate each LED in the array individually and take a picture. Then, an algorithm constructs a higher-resolution image from the collected images. You can see the results and an explanation in the video below.

You’d think you could use this to enhance a cheap microscope, but the truth is you need a high-quality microscope to start with. In addition, color cameras may not be usable, so you may have to find or create a monochrome camera.

The code for the project is on GitHub. The LEDs need to be close to a point source, so smaller is better, and that determines what kind of LEDs are usable. Of course, the LEDs go through the sample, so this is suitable for transmissive microscopes, not metallurgical ones, at least in the current incarnation.

What is faster than the fastest hypersonic missile?, well a beam of light, microwaves or subatomic particles but they are impossibly small and have almost no mass compared to a projectile. However, if you have enough energy you can make a weapon that works at the speed of light and in theory can shoot down anything projectile weapon we have now.
So why don’t we have phasers like in Star Trek?, in this video we look at Directed Energy Weapons and what they can do now and in the future.

This video is sponsored by Brilliant.org :
https://brilliant.org/CuriousDroid.

Written, researched and presented by paul shillito.

Images and footage : Raytheon, Lockheed Martin, Google, US Navy, Marine Forces Reserve, IPG Photonics, EngineerguyFederico Dios, MicrowaveMeShow, PyroGadgets, laserpointersafety.com.
A big thank you also goes to all our Patreons smile

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Science fiction writer and historian HG Wells spoke of heat ray in war of the world’s.


The US-China rivalry has brought the future into today and weapons that were impossible to build before have become a reality — all in a bid to destroy each other. Laser weapons and hypersonic missiles — weapons only seen in sci-fi movies, are now fitting up to be the weapons of choice in a future conflict that could destroy the world as we know it. Which weapon will come out on top? In this video, we’ll find out — as it could be the single greatest indicator of which country would win in the race for world dominance between the US and China.

“I give you God’s view,” said Toby Cubitt, a physicist turned computer scientist at University College London and part of the vanguard of the current charge into the unknowable, and “you still can’t predict what it’s going to do.”

Eva Miranda, a mathematician at the Polytechnic University of Catalonia (UPC) in Spain, calls undecidability a “next-level chaotic thing.”

Undecidability means that certain questions simply cannot be answered. It’s an unfamiliar message for physicists, but it’s one that mathematicians and computer scientists know well. More than a century ago, they rigorously established that there are mathematical questions that can never be answered, true statements that can never be proved. Now physicists are connecting those unknowable mathematical systems with an increasing number of physical ones and thereby beginning to map out the hard boundary of knowability in their field as well.

What is technofeudalism? How does it affect us? And why is it important to talk about it?

Video: technofeudalism is here—and you’re already trapped inside it.

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