@SavannahFeder If a goal of such videos is to trigger some emotions and intentions and all such videos will be everywhere - how will it influence the process? Maybe making something outstanding and impressive will still take another scale of effort and budget?
@JinaAI_ Can you describe from practice how well it can encode visual information? What depth of details is reasonable to assume? For example in more technical images like floor plans?
@kimmonismus I had an interesting discussion with o3 about open deep topics. After some exchanges suggested that there are limits in language capacity to cover how world works. There is clear truth in that. It's easy to see it comparing how different languages are able to cover the same info.
@Hesamation@HeyNina101 Very cool. On viable suggestion I would have is to open it more to different LLM platformts so instead of particular clients files add a routhing file with platform parameters and function calls. In the end one would like to test/route 10+ different platforms.
@1romanprodan Basic RAG solution will not work for most of professional commercial cases. Reliance on comparing information based on embeddings will not work in documents dense in information and meaning. Graph RAG seems to be a direction. Problem still to be solved.
The new Chat GPT 4.5 is:
750 x more expensive than the Google Gemini Flash 2.0 model.
277 x more expensive than DeepSeek V3.
30 x more expensive than ChatGPT 4o.
25 x more expensive than ChatGPT Claude Sonnet 3.7.
In many aspects, these models are comparable.
Bill Gates, przeszedł ostatnio glow up i zaczął podchodzić z większą fantazją do ubioru. To oczywiście nieprawda, tak jak coraz więcej treści wideo.
Nowe Kling AI Virtual Try On: daj mi osobę i zdjęcie ubioru, a pokażę Ci, jak ta prezentuje się w tej kreacji.