Ganesh Jagadeesan’s Post

Forget about LLMs Ranking Leaderboards🥇 , Welcome to the Era of Model Routing 🔀 ! The more I talk to AI practitioners, the more I realize about a clear shift in the market. Few months ago there was no discussion about which model to use. Today, things are very different. Talking to a customer last week, he said: I like Claude 3 for long summaries, GPT4 for coding tasks, Mistral 7B for simple user queries and the list continued….. Imagine choosing a foundation model like picking a car 🚗. You want something cost-effective, reliable, and versatile. But sometimes, you need the speed of a Ferrari 🏎. Easy choice, right? Not so fast. Traditional model selection has been static, tied to specific use cases. What if your journey includes a mountain track? Suddenly, you wish you had a Range Rover instead. Picture this in the world of generative AI. You've got a complex technical report for analysis and then need to send an email summarizing it moments later. You don't necessarily need the same model for both tasks—just the right one for each specific job. That's the beauty of model routing. It dynamically selects the most suitable model based on the task at hand. As companies expand their use cases, I foresee model routing becoming increasingly crucial, especially with the advent of state-of-the-art models and others fine-tuned for specific tasks. The future of model selection is flexible and task-specific, marking a significant shift from how we've approached it until now. 𝘋𝘰 𝘺𝘰𝘶 𝘸𝘢𝘯𝘵 𝘢 𝘳𝘦𝘢𝘭 𝘦𝘹𝘢𝘮𝘱𝘭𝘦 𝘰𝘧 𝘮𝘰𝘥𝘦𝘭 𝘳𝘰𝘶𝘵𝘪𝘯𝘨? 𝘛𝘩𝘪𝘴 𝘪𝘴 𝘩𝘰𝘸 Amazon 𝘘 𝘧𝘰𝘳 𝘉𝘶𝘴𝘪𝘯𝘦𝘴𝘴 𝘮𝘢𝘯𝘢𝘨𝘦𝘴 𝘢𝘯𝘺 𝘶𝘴𝘦𝘳 𝘲𝘶𝘦𝘳𝘺. 𝘐𝘵 𝘶𝘯𝘥𝘦𝘳𝘴𝘵𝘢𝘯𝘥𝘴 𝘪𝘵𝘴 𝘤𝘰𝘮𝘱𝘭𝘦𝘹𝘪𝘵𝘺 𝘢𝘯𝘥 𝘤𝘩𝘰𝘴𝘦 𝘵𝘩𝘦 𝘮𝘰𝘴𝘵 𝘴𝘶𝘪𝘵𝘢𝘣𝘭𝘦 𝘮𝘰𝘥𝘦𝘭 𝘪𝘯 𝘵𝘦𝘳𝘮𝘴 𝘰𝘧 𝘱𝘦𝘳𝘧𝘰𝘳𝘮𝘢𝘯𝘤𝘦 𝘢𝘯𝘥 𝘴𝘱𝘦𝘦𝘥, 𝘵𝘳𝘺𝘪𝘯𝘨 𝘵𝘰 𝘮𝘢𝘹𝘪𝘮𝘪𝘻𝘦 𝘵𝘩𝘦 𝘶𝘴𝘦𝘳 𝘦𝘹𝘱𝘦𝘳𝘪𝘦𝘯𝘤𝘦. #ai #genai #llm

Forget about LLMs Ranking Leaderboards🥇 , Welcome to the Era of Model Routing 🔀 ! The more I talk to AI practitioners, the more I realize about a clear shift in the market. Few months ago there was no discussion about which model to use. Today, things are very different. Talking to a customer last week, he said: I like Claude 3 for long summaries, GPT4 for coding tasks, Mistral 7B for simple user queries and the list continued….. Imagine choosing a foundation model like picking a car 🚗. You want something cost-effective, reliable, and versatile. But sometimes, you need the speed of a Ferrari 🏎. Easy choice, right? Not so fast. Traditional model selection has been static, tied to specific use cases. What if your journey includes a mountain track? Suddenly, you wish you had a Range Rover instead. Picture this in the world of generative AI. You've got a complex technical report for analysis and then need to send an email summarizing it moments later. You don't necessarily need the same model for both tasks—just the right one for each specific job. That's the beauty of model routing. It dynamically selects the most suitable model based on the task at hand. As companies expand their use cases, I foresee model routing becoming increasingly crucial, especially with the advent of state-of-the-art models and others fine-tuned for specific tasks. The future of model selection is flexible and task-specific, marking a significant shift from how we've approached it until now. 𝘋𝘰 𝘺𝘰𝘶 𝘸𝘢𝘯𝘵 𝘢 𝘳𝘦𝘢𝘭 𝘦𝘹𝘢𝘮𝘱𝘭𝘦 𝘰𝘧 𝘮𝘰𝘥𝘦𝘭 𝘳𝘰𝘶𝘵𝘪𝘯𝘨? 𝘛𝘩𝘪𝘴 𝘪𝘴 𝘩𝘰𝘸 Amazon 𝘘 𝘧𝘰𝘳 𝘉𝘶𝘴𝘪𝘯𝘦𝘴𝘴 𝘮𝘢𝘯𝘢𝘨𝘦𝘴 𝘢𝘯𝘺 𝘶𝘴𝘦𝘳 𝘲𝘶𝘦𝘳𝘺. 𝘐𝘵 𝘶𝘯𝘥𝘦𝘳𝘴𝘵𝘢𝘯𝘥𝘴 𝘪𝘵𝘴 𝘤𝘰𝘮𝘱𝘭𝘦𝘹𝘪𝘵𝘺 𝘢𝘯𝘥 𝘤𝘩𝘰𝘴𝘦 𝘵𝘩𝘦 𝘮𝘰𝘴𝘵 𝘴𝘶𝘪𝘵𝘢𝘣𝘭𝘦 𝘮𝘰𝘥𝘦𝘭 𝘪𝘯 𝘵𝘦𝘳𝘮𝘴 𝘰𝘧 𝘱𝘦𝘳𝘧𝘰𝘳𝘮𝘢𝘯𝘤𝘦 𝘢𝘯𝘥 𝘴𝘱𝘦𝘦𝘥, 𝘵𝘳𝘺𝘪𝘯𝘨 𝘵𝘰 𝘮𝘢𝘹𝘪𝘮𝘪𝘻𝘦 𝘵𝘩𝘦 𝘶𝘴𝘦𝘳 𝘦𝘹𝘱𝘦𝘳𝘪𝘦𝘯𝘤𝘦. #ai #genai #llm

Forget about LLMs Ranking Leaderboards🥇 , Welcome to the Era of Model Routing 🔀 ! The more I talk to AI practitioners, the more I realize about a clear shift in the market. Few months ago there was no discussion about which model to use. Today, things are very different. Talking to a customer last week, he said: I like Claude 3 for long summaries, GPT4 for coding tasks, Mistral 7B for simple user queries and the list continued….. Imagine choosing a foundation model like picking a car 🚗. You want something cost-effective, reliable, and versatile. But sometimes, you need the speed of a Ferrari 🏎. Easy choice, right? Not so fast. Traditional model selection has been static, tied to specific use cases. What if your journey includes a mountain track? Suddenly, you wish you had a Range Rover instead. Picture this in the world of generative AI. You've got a complex technical report for analysis and then need to send an email summarizing it moments later. You don't necessarily need the same model for both tasks—just the right one for each specific job. That's the beauty of model routing. It dynamically selects the most suitable model based on the task at hand. As companies expand their use cases, I foresee model routing becoming increasingly crucial, especially with the advent of state-of-the-art models and others fine-tuned for specific tasks. The future of model selection is flexible and task-specific, marking a significant shift from how we've approached it until now. 𝘋𝘰 𝘺𝘰𝘶 𝘸𝘢𝘯𝘵 𝘢 𝘳𝘦𝘢𝘭 𝘦𝘹𝘢𝘮𝘱𝘭𝘦 𝘰𝘧 𝘮𝘰𝘥𝘦𝘭 𝘳𝘰𝘶𝘵𝘪𝘯𝘨? 𝘛𝘩𝘪𝘴 𝘪𝘴 𝘩𝘰𝘸 Amazon 𝘘 𝘧𝘰𝘳 𝘉𝘶𝘴𝘪𝘯𝘦𝘴𝘴 𝘮𝘢𝘯𝘢𝘨𝘦𝘴 𝘢𝘯𝘺 𝘶𝘴𝘦𝘳 𝘲𝘶𝘦𝘳𝘺. 𝘐𝘵 𝘶𝘯𝘥𝘦𝘳𝘴𝘵𝘢𝘯𝘥𝘴 𝘪𝘵𝘴 𝘤𝘰𝘮𝘱𝘭𝘦𝘹𝘪𝘵𝘺 𝘢𝘯𝘥 𝘤𝘩𝘰𝘴𝘦 𝘵𝘩𝘦 𝘮𝘰𝘴𝘵 𝘴𝘶𝘪𝘵𝘢𝘣𝘭𝘦 𝘮𝘰𝘥𝘦𝘭 𝘪𝘯 𝘵𝘦𝘳𝘮𝘴 𝘰𝘧 𝘱𝘦𝘳𝘧𝘰𝘳𝘮𝘢𝘯𝘤𝘦 𝘢𝘯𝘥 𝘴𝘱𝘦𝘦𝘥, 𝘵𝘳𝘺𝘪𝘯𝘨 𝘵𝘰 𝘮𝘢𝘹𝘪𝘮𝘪𝘻𝘦 𝘵𝘩𝘦 𝘶𝘴𝘦𝘳 𝘦𝘹𝘱𝘦𝘳𝘪𝘦𝘯𝘤𝘦. #ai #genai #llm

Forget about LLMs Ranking Leaderboards🥇 , Welcome to the Era of Model Routing 🔀 ! The more I talk to AI practitioners, the more I realize about a clear shift in the market. Few months ago there was no discussion about which model to use. Today, things are very different. Talking to a customer last week, he said: I like Claude 3 for long summaries, GPT4 for coding tasks, Mistral 7B for simple user queries and the list continued….. Imagine choosing a foundation model like picking a car 🚗. You want something cost-effective, reliable, and versatile. But sometimes, you need the speed of a Ferrari 🏎. Easy choice, right? Not so fast. Traditional model selection has been static, tied to specific use cases. What if your journey includes a mountain track? Suddenly, you wish you had a Range Rover instead. Picture this in the world of generative AI. You've got a complex technical report for analysis and then need to send an email summarizing it moments later. You don't necessarily need the same model for both tasks—just the right one for each specific job. That's the beauty of model routing. It dynamically selects the most suitable model based on the task at hand. As companies expand their use cases, I foresee model routing becoming increasingly crucial, especially with the advent of state-of-the-art models and others fine-tuned for specific tasks. The future of model selection is flexible and task-specific, marking a significant shift from how we've approached it until now. 𝘋𝘰 𝘺𝘰𝘶 𝘸𝘢𝘯𝘵 𝘢 𝘳𝘦𝘢𝘭 𝘦𝘹𝘢𝘮𝘱𝘭𝘦 𝘰𝘧 𝘮𝘰𝘥𝘦𝘭 𝘳𝘰𝘶𝘵𝘪𝘯𝘨? 𝘛𝘩𝘪𝘴 𝘪𝘴 𝘩𝘰𝘸 Amazon 𝘘 𝘧𝘰𝘳 𝘉𝘶𝘴𝘪𝘯𝘦𝘴𝘴 𝘮𝘢𝘯𝘢𝘨𝘦𝘴 𝘢𝘯𝘺 𝘶𝘴𝘦𝘳 𝘲𝘶𝘦𝘳𝘺. 𝘐𝘵 𝘶𝘯𝘥𝘦𝘳𝘴𝘵𝘢𝘯𝘥𝘴 𝘪𝘵𝘴 𝘤𝘰𝘮𝘱𝘭𝘦𝘹𝘪𝘵𝘺 𝘢𝘯𝘥 𝘤𝘩𝘰𝘴𝘦 𝘵𝘩𝘦 𝘮𝘰𝘴𝘵 𝘴𝘶𝘪𝘵𝘢𝘣𝘭𝘦 𝘮𝘰𝘥𝘦𝘭 𝘪𝘯 𝘵𝘦𝘳𝘮𝘴 𝘰𝘧 𝘱𝘦𝘳𝘧𝘰𝘳𝘮𝘢𝘯𝘤𝘦 𝘢𝘯𝘥 𝘴𝘱𝘦𝘦𝘥, 𝘵𝘳𝘺𝘪𝘯𝘨 𝘵𝘰 𝘮𝘢𝘹𝘪𝘮𝘪𝘻𝘦 𝘵𝘩𝘦 𝘶𝘴𝘦𝘳 𝘦𝘹𝘱𝘦𝘳𝘪𝘦𝘯𝘤𝘦. #ai #genai #llm

Forget about LLMs Ranking Leaderboards🥇 , Welcome to the Era of Model Routing 🔀 ! The more I talk to AI practitioners, the more I realize about a clear shift in the market. Few months ago there was no discussion about which model to use. Today, things are very different. Talking to a customer last week, he said: I like Claude 3 for long summaries, GPT4 for coding tasks, Mistral 7B for simple user queries and the list continued….. Imagine choosing a foundation model like picking a car 🚗. You want something cost-effective, reliable, and versatile. But sometimes, you need the speed of a Ferrari 🏎. Easy choice, right? Not so fast. Traditional model selection has been static, tied to specific use cases. What if your journey includes a mountain track? Suddenly, you wish you had a Range Rover instead. Picture this in the world of generative AI. You've got a complex technical report for analysis and then need to send an email summarizing it moments later. You don't necessarily need the same model for both tasks—just the right one for each specific job. That's the beauty of model routing. It dynamically selects the most suitable model based on the task at hand. As companies expand their use cases, I foresee model routing becoming increasingly crucial, especially with the advent of state-of-the-art models and others fine-tuned for specific tasks. The future of model selection is flexible and task-specific, marking a significant shift from how we've approached it until now. 𝘋𝘰 𝘺𝘰𝘶 𝘸𝘢𝘯𝘵 𝘢 𝘳𝘦𝘢𝘭 𝘦𝘹𝘢𝘮𝘱𝘭𝘦 𝘰𝘧 𝘮𝘰𝘥𝘦𝘭 𝘳𝘰𝘶𝘵𝘪𝘯𝘨? 𝘛𝘩𝘪𝘴 𝘪𝘴 𝘩𝘰𝘸 Amazon 𝘘 𝘧𝘰𝘳 𝘉𝘶𝘴𝘪𝘯𝘦𝘴𝘴 𝘮𝘢𝘯𝘢𝘨𝘦𝘴 𝘢𝘯𝘺 𝘶𝘴𝘦𝘳 𝘲𝘶𝘦𝘳𝘺. 𝘐𝘵 𝘶𝘯𝘥𝘦𝘳𝘴𝘵𝘢𝘯𝘥𝘴 𝘪𝘵𝘴 𝘤𝘰𝘮𝘱𝘭𝘦𝘹𝘪𝘵𝘺 𝘢𝘯𝘥 𝘤𝘩𝘰𝘴𝘦 𝘵𝘩𝘦 𝘮𝘰𝘴𝘵 𝘴𝘶𝘪𝘵𝘢𝘣𝘭𝘦 𝘮𝘰𝘥𝘦𝘭 𝘪𝘯 𝘵𝘦𝘳𝘮𝘴 𝘰𝘧 𝘱𝘦𝘳𝘧𝘰𝘳𝘮𝘢𝘯𝘤𝘦 𝘢𝘯𝘥 𝘴𝘱𝘦𝘦𝘥, 𝘵𝘳𝘺𝘪𝘯𝘨 𝘵𝘰 𝘮𝘢𝘹𝘪𝘮𝘪𝘻𝘦 𝘵𝘩𝘦 𝘶𝘴𝘦𝘳 𝘦𝘹𝘱𝘦𝘳𝘪𝘦𝘯𝘤𝘦. #ai #genai #llm