Listen "Multimodal Reka Core 🌟 // OpenAI Batch API 💻 // COCONut Segmentation Dataset 🥥"
Episode Synopsis
Reka Core, a comprehensive multimodal solution, is one of only two commercially available models that can handle input from text, images, videos, and audio.
OpenAI's Batch API promises to save costs and increase rate limits on certain async tasks like summarization, translation, and image classification.
COCONut is the largest and most comprehensive segmentation dataset to date, with high-quality annotations and harmonized segmentation types.
DR-PO algorithm directly resets the policy optimizer to the states in the offline dataset, leading to better generative models that are fine-tuned to human preferences.
Contact: [email protected]
Timestamps:
00:34 Introduction
01:52 Reka Core: Our Frontier Class Multimodal Language Model
03:43 OpenAI Batch API
05:14 OpenAI fires two researchers for leaking info
06:42 Fake sponsor
08:54 COCONut: Modernizing COCO Segmentation
10:27 Dataset Reset Policy Optimization for RLHF
12:22 Probing the 3D Awareness of Visual Foundation Models
13:58 Outro
OpenAI's Batch API promises to save costs and increase rate limits on certain async tasks like summarization, translation, and image classification.
COCONut is the largest and most comprehensive segmentation dataset to date, with high-quality annotations and harmonized segmentation types.
DR-PO algorithm directly resets the policy optimizer to the states in the offline dataset, leading to better generative models that are fine-tuned to human preferences.
Contact: [email protected]
Timestamps:
00:34 Introduction
01:52 Reka Core: Our Frontier Class Multimodal Language Model
03:43 OpenAI Batch API
05:14 OpenAI fires two researchers for leaking info
06:42 Fake sponsor
08:54 COCONut: Modernizing COCO Segmentation
10:27 Dataset Reset Policy Optimization for RLHF
12:22 Probing the 3D Awareness of Visual Foundation Models
13:58 Outro
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