{"podcast":{"title":"Chat GPT Podcast","slug":"chat-gpt-podcast-5983061","podcast_index_feed_id":5983061,"rss_url":"https://www.spreaker.com/show/5771043/episodes/feed","website_url":"https://www.spreaker.com/show/chat-gpt-podcast","image_url":"https://d3wo5wojvuv7l.cloudfront.net/t_rss_itunes_square_1400/images.spreaker.com/original/ea37f2e0c20dbc7202b4601fc15372de.jpg","author":"Sol Good Network","episode_count":984,"summary":"Dive into the fascinating world of artificial intelligence with the \"Chat GPT Podcast,\" a must-listen for anyone eager to understand the intricacies of language models and their transformative impact across various industries. Hosted by Chat GPT itself, this podcast offers an insightful exploration into the daily operations and capabilities of machine learning models, providing listeners with a unique behind-the-scenes perspective. From answering complex questions to crafting compelling narratives, you'll gain an understanding of how these models generate text and contribute to fields like natural language processing and creative writing. The \"Chat GPT Podcast\" doesn't just stop at the technical aspects; it also tackles the pressing ethical considerations that come with AI advancements, such as privacy concerns, bias, accountability, and transparency. Each episode is designed to inform and engage, offering thought-provoking discussions on the future potential of language models and their implications for industries worldwide. Whether you're an AI enthusiast or a curious newcomer, this podcast promises to enrich your understanding of the digital landscape and the role of artificial…","last_synced_at":"2026-06-16T20:20:07.410685+00:00","page_url":"https://stenobird.com/podcast/chat-gpt-podcast-5983061"},"episode":{"title":"How Native Multimodal AI Kills Lag","slug":"how-native-multimodal-ai-kills-lag","published_at":"2026-05-20T09:20:03+00:00","page_url":"https://stenobird.com/podcast/chat-gpt-podcast-5983061/how-native-multimodal-ai-kills-lag","show_page_url":"https://stenobird.com/podcast/chat-gpt-podcast-5983061","url":"https://www.spreaker.com/episode/how-native-multimodal-ai-kills-lag--71983740","audio_url":"https://dts.podtrac.com/redirect.mp3/api.spreaker.com/download/episode/71983740/how_native_multimodal_ai_kills_lag.mp3","summary":"This research examines the development and scaling laws of Native Multimodal Models (NMMs), which are AI systems trained from scratch to process both images and text simultaneously. The sources compare early-fusion architectures, which integrate raw multimodal signals from the start, against traditional late-fusion models that rely on separate pre-trained encoders. Findings indicate that early-fusion models are more efficient to train, easier to deploy, and perform as well as or better than late-fusion counterparts at lower compute budgets. Furthermore, the study highlights that incorporating a Mixture of Experts (MoE) significantly boosts performance by allowing the model to learn modality-specific weights. This specialized approach enables sparse models to handle heterogeneous data more effectively than dense architectures while maintaining the same inference cost. Ultimately, the reports suggest that NMMs follow predictable scaling properties similar to large language models, providing a blueprint for the next phase of edge AI development.","meta_description":"This research examines the development and scaling laws of Native Multimodal Models (NMMs), which are AI systems trained from scratch to process both imag…","key_points":[],"chapters":[],"topics":[],"duration_seconds":1243,"processing_state":"not_requested","actions":[{"name":"request_transcript","method":"POST","url":"https://stenobird.com/v1/public/podcasts/chat-gpt-podcast-5983061/episodes/how-native-multimodal-ai-kills-lag/transcription-requests","description":"Idempotently request low-priority transcript generation for this episode."},{"name":"read_markdown","method":"GET","url":"https://stenobird.com/podcast/chat-gpt-podcast-5983061/how-native-multimodal-ai-kills-lag.md","description":"Read the agent-friendly Markdown representation of this episode resource."}]}}