OpenAI just made a big move. #GPT4o, the Desktop app, audio, video… All that was cool in the demo but what does it give in practice? I test absolutely EVERYTHING in my video here →
https://youtu.be/RG5itd9ktW8 Share without moderation.
MACHINE LEARNING
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Practical Test of GPT-4o: Desktop, Audio, and Video
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Automatic Speech Recognition with OpenAI GPT-4o and Whisper Models
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🚀 Blog-tastic Tuesdays 🚀https://t.co/l4ersJaHam
— Satya Mallick (@LearnOpenCV) 14 mai 2024
Gone are the days when talking to our gadgets felt like a scene from a sci-fi movie. Today, it's our reality, thanks to advanced AI tools like OpenAI's GPT-4-o (omni) and Whisper models. These open-source innovations are making… pic.twitter.com/mFPm4kAn5PBlog-tastic Tuesdays https://
learnopencv.com/automatic-spee
ch-recognition/
… Gone are the days when talking to our gadgets felt like a scene from a sci-fi movie. Today, it's our reality, thanks to advanced AI tools like OpenAI's GPT-4-o (omni) and Whisper models. These open-source innovations are making -
Daily Content Sharing on Python Data Science and MLOps Topics
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That's a wrap! If you are interested in any of these below topics: – Python – Data Science – Machine Learning – Data Analysis – LLMs – MLOps Find me → @Sumanth_077 I'm sharing daily content over here.
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Upload PDF Research Paper Data to Clarifai Vector Database
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Step 3: Upload the data, Here we are uploading the pdf file of a research paper. Once you upload the data, it will embed and index the data into your Clarifai app. Clarifai Apps acts as your vector database.
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Benchmarking GPT-4o for Contextual Emotion Recognition in HRI
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In my HRI lab, the main issue that we have been trying to tackle is precision over many categories and contextual emotion recognition. Gpt-4o needs to be benchmarked properly to compare it to current research (paper forthcoming).
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Embodiment and Acoustic Context in Human-Robot Interaction Systems
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I would need to try it out also to know more, to see how it handles other examples. They only demo'd a smile. And HRI thinks a lot about embodiment. For example we should take into account acoustic context eg. https://
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Multimodal Emotion Analysis: Early Fusion Techniques and Historical Context
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I agree that the integration is impressive, esp. early fusion of 3 modalities at scale. But multimodal emotion analysis and other kinds of fusion have been well studied, check out work by @lpmorency I also worked on this ~10 years ago using late fusion
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Prompt technique: hiding chain-of-thought in code comments
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Teaching ChatGPT to “think silently” by hiding planning, chain-of-thought, or other intermediate writing in interpreted Python code blocks as comments or strings. Text remains visible to the model (and the user, by clicking to view code) without cluttering the chat dialog.
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Voice data training settings and privacy defaults
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Not really, voice data training will be a separate option and off by default
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Tensor Algebra: Scaling AI Architectures Efficiently with TensorLy
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Tensor algebra is the way to scale AI architectures in an efficient way. We have been working on it for more than a decade. Check out http://
tensorly.org led by @JeanKossaifi with @PyTorch framework