https://youtu.be/Eada9prCKKE
Google DeepMind has come up with an interesting idea: using language models as optimizers. They call this approach Optimization by PROmpting, or OPRO for short. Instead of relying on traditional optimization methods, DeepMind's models are trained to generate new solutions by understanding natural language descriptions of the problem at hand and using previous solutions as a basis. This concept has been tested on a range of problems, including linear regression, traveling salesman problems, and prompt optimization tasks. The results are pretty impressive. The prompts optimized by OPRO have outperformed prompts designed by humans by up to 8% on the GSM8K dataset, and up to a whopping 50% on the Big-Bench Hard tasks dataset. So why is this significant? Well, DeepMind's OPRO has the potential to revolutionize problem-solving in various fields. By improving task accuracy and surpassing human-designed approaches, it can provide end users with more efficient and effective solutions. Whether it's in operations research, logistics, or any other domain that involves complex problem-solving, OPRO could be a game-changer. It's exciting to see how language models can be leveraged in such innovative ways to tackle real-world challenges.
Video: https://youtu.be/Eada9prCKKE
Hey there! I have some exciting news to share with you today. NVIDIA has just released a groundbreaking software called TensorRT-LLM that can supercharge LLM inference on H100 GPUs. This is a game-changer, folks! So, what's so special about this software? Well, it comes packed with optimized kernels, pre- and post-processing steps, and even multi-GPU/multi-node communication primitives. All of this combined gives you an incredible performance boost. And the best part? You don't need to be a C++ or NVIDIA CUDA expert to use it! NVIDIA has made it super easy for developers to experiment with new LLMs. But wait, there's more! TensorRT-LLM also offers an open-source modular Python API, making customization and extensibility a breeze. You can even quantize your models to FP8 format for better memory utilization. And guess what? TensorRT-LLM is not just for H100 GPUs.
Full transcript at: https://enoumen.com/2023/09/02/emerging-ai-innovations-top-trends-shaping-the-landscape-in-september-2023/
Attention AI Unraveled Podcast Listeners!Are you eager to expand your understanding of artificial intelligence? Look no further than the essential book "AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence," now available at Apple, Google, or Amazon today!
This podcast is generated using the Wondercraft AI platform (https://www.wondercraft.ai/?via=etienne), a tool that makes it super easy to start your own podcast, by enabling you to use hyper-realistic AI voices as your host. Like mine!
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By Etienne Noumen
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https://youtu.be/Eada9prCKKE
Google DeepMind has come up with an interesting idea: using language models as optimizers. They call this approach Optimization by PROmpting, or OPRO for short. Instead of relying on traditional optimization methods, DeepMind's models are trained to generate new solutions by understanding natural language descriptions of the problem at hand and using previous solutions as a basis. This concept has been tested on a range of problems, including linear regression, traveling salesman problems, and prompt optimization tasks. The results are pretty impressive. The prompts optimized by OPRO have outperformed prompts designed by humans by up to 8% on the GSM8K dataset, and up to a whopping 50% on the Big-Bench Hard tasks dataset. So why is this significant? Well, DeepMind's OPRO has the potential to revolutionize problem-solving in various fields. By improving task accuracy and surpassing human-designed approaches, it can provide end users with more efficient and effective solutions. Whether it's in operations research, logistics, or any other domain that involves complex problem-solving, OPRO could be a game-changer. It's exciting to see how language models can be leveraged in such innovative ways to tackle real-world challenges.
Video: https://youtu.be/Eada9prCKKE
Hey there! I have some exciting news to share with you today. NVIDIA has just released a groundbreaking software called TensorRT-LLM that can supercharge LLM inference on H100 GPUs. This is a game-changer, folks! So, what's so special about this software? Well, it comes packed with optimized kernels, pre- and post-processing steps, and even multi-GPU/multi-node communication primitives. All of this combined gives you an incredible performance boost. And the best part? You don't need to be a C++ or NVIDIA CUDA expert to use it! NVIDIA has made it super easy for developers to experiment with new LLMs. But wait, there's more! TensorRT-LLM also offers an open-source modular Python API, making customization and extensibility a breeze. You can even quantize your models to FP8 format for better memory utilization. And guess what? TensorRT-LLM is not just for H100 GPUs.
Full transcript at: https://enoumen.com/2023/09/02/emerging-ai-innovations-top-trends-shaping-the-landscape-in-september-2023/
Attention AI Unraveled Podcast Listeners!Are you eager to expand your understanding of artificial intelligence? Look no further than the essential book "AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence," now available at Apple, Google, or Amazon today!
This podcast is generated using the Wondercraft AI platform (https://www.wondercraft.ai/?via=etienne), a tool that makes it super easy to start your own podcast, by enabling you to use hyper-realistic AI voices as your host. Like mine!
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