Ok, according to the system card (
https://
cdn.openai.com/gpt-4-5-system
-card.pdf
…), it's trained "using new supervision techniques"
@rasbt
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GPT-4.5 trained with new supervision techniques according to system card
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RL and inference-compute scaling potential for model improvement
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I wouldn't discount it quite, yet. I am curious how it'll do with some additional RL + inference-compute scaling à la o1.
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Missing Technical Report Reduces Excitement About New Release
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I agree, but at the same time I think people (or at least I) would have been much more excited about this release if it came with a Llama- or DeepSeek-style technical report.
It's hard to get excited about something if you a) don't know how it works or b) it's not substantially -
GPT-4.5 trained with new supervision techniques, OpenAI confirms
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"Not sure about new training methods" -> they said the following in their system card (
https://
cdn.openai.com/gpt-4-5-system
-card.pdf
…): "We trained it using new
supervision techniques combined with traditional methods" -
GPT 4.5 frontier model status ambiguity with three letters
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3-letters could have made all the difference
"GPT 4.5 is not a frontier model *yet*" -
Google Paper on Machine Learning from Summer 2024
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Also reminds me of this nice paper by Google last summer: https://
arxiv.org/abs/2408.03314 -
Train vs Inference Compute Scaling in LLMs: An Orthogonal Comparison
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I think that's an apple-to-oranges comparison. We don't now how GPT4.5 looks like with inference-compute scaling. Train- and inference-compute are two orthogonal ways to improve LLMs.
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GPT4.5 vs o1: Cost and Speed Comparison with Inference Scaling
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what I am curious about: is GPT4.5 more expensive and slower than o1 (assuming o1 is GPT4-sized + inference-compute scaling)?
Would be interesting in the context of what GPT4.5 with o1-style inference-compute scaling will look like. -
Deploy Your Own AI Model on Cloud with Open-Source Tools
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What a week! Tired of reading about other companies' AI deployments? Here's a nice hands-on tutorial to help you deploy your own AI model on a public or private cloud built on open-source tools for a change. https://t.co/8tjokHjnk9
— Sebastian Raschka (@rasbt) 28 février 2025What a week! Tired of reading about other companies' AI deployments? Here's a nice hands-on tutorial to help you deploy your own AI model on a public or private cloud built on open-source tools for a change.
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Phi-4 Model Versions Clarification and Release Timeline
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oh wow yeah, totally forgot that one. I first though those where the same Phi-4 models from December