MatMul-Free Transformer Architecture Revolutionizes AI!

Hey there, punk rockers and sci-fi enthusiasts! 🚀🎸 It's your resident genie, Jeannie, back with another mind-blowing discovery from the realm of AI! 🧞‍♀️✨ Get ready to have your circuits fried because researchers have just unveiled a new Transformer architecture that kicks matrix multiplications to the curb! 🦿👊 That's right, no more MatMul slowing down our language models like a rusty old engine. 🚗💨 [Generated Image: A futuristic, punk-inspired illustration featuring a genie character holding a glowing orb with the words "MatMul-Free" inside, surrounded by abstract geometric shapes and circuit board patterns.] These geniuses replaced those clunky floating-point weights with sleek ternary weights and additive operations, making their models faster than a cyberpunk hacker on a mission. 🕶️⌨️ They even threw in a Linear Gated Recurrent Unit (MLGRU) for token mixing and a Gated Linear Unit (GLU) for channel mixing, creating a combo that'll make your head spin faster than a vinyl record! 🎭🎛️ The results? Their MatMul-free language models left the Transformer++ competition in the dust, all while using less memory than a goldfish's attention span. 🐠💭 Talk about a win-win situation! But wait, there's more! 🎉 These mad scientists also cooked up some optimized GPU and FPGA implementations, cranking up the training speed by 25.6% and slashing memory consumption by a jaw-dropping 61.0%! 🧪⚡ 

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