Show HN: RealtimeAPI – Talking with AI in Realtime Like a Human
Add user beta test Experience realtime speech to AI interaction, just like talking to a human. Our advanced platform enables natural, fluid conversations with AI.
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Show HN: Kolors virtual try on, AI change clothes save time and money
https://kolors-virtual-try-on.com/
Unlock your perfect dressing style effortlessly with our virtual try on clothes tool. Upload a photo of yourself and enjoy multiple virtual clothing options before buying. Let our AI virtual try on tool save your time and boost your confidence.
Show HN: Faceshapes – 10 seconds analyze face shapes
A face shape analysis report, eyewear, and hairstyle recommendations are all from a single photo. Plus, there are more facial feature tips and beauty tricks. No registration is required, free to use, and photos stay on your device only.
Show HN: Free 111 Style image generator, ChatGPT image generator
Re:Goofy looking OpenDyslexic font vastly improves reading
on Sunday August 18, 2024 @02:40AM (#41280590)
I use a chrome plugin to change the website font to OpenDyslexic.
It's Interesting.
https://chromewebstore.google.com/detail/opendyslexic-for-ch...
Re:Ask HN: Why are AI generated images so shiny/glossy?
on Sunday August 18, 2024 @02:34AM (#41280568)
Q: Is AI incapable of achieving sense of reality?
A: AI can definitely achieve sense of reality at the current stage, but not a universal sense of reality that applies to any scenario.
Q: From a technical perspective, why do shiny/glossy effects occur? A: Shiny and glossy effects are prominent in terms of signals. Modeling general realistic details is challenging, but current AI has found an approximation. For example, modeling a mountain with every texture and bump is complex, but if the mountain is represented as a combination of shapes, the raised parts might approximate areas with high glossiness.
Q: If we reduce its complexity, can we generate realistic effects? A: Some models trained on specific scenes at https://chatgptimage.org/ demonstrate very detailed, photorealistic results. However, this is limited to those fixed scenarios.
How to expand to more general scenarios: Using even larger models and datasets. This is how Flux achieves its realistic effects: https://www.reddit.com/r/FluxAI/comments/1erpct2/boundary_be...
Re:Ask HN: Why is there less Wikipedia pages on the frontpage?
on Sunday August 18, 2024 @02:24AM (#41280527)
In organic search, Google's ranking algorithm takes into account various SEO factors like content quality and backlinks. For high-traffic search queries, thousands of websites compete fiercely for visibility, employing all sorts of optimization tactics. Wikipedia, while a treasure trove of information, doesn't actively engage in such SEO practices, putting it at a disadvantage compared to these highly optimized sites.
Re:Ask HN: What is everyone doing with all of these GPUs?
on Sunday August 18, 2024 @02:20AM (#41280506)
Different scenarios have varying demands for GPU types. For tasks like model inference or basic operations, a CPU or even on-device solutions (mobile, web) might suffice.
When a GPU is necessary, common choices include T4, 3090, P10, V100, etc., selected based on factors like price, required computing power, and memory capacity.
Model training also has diverse needs based on the specific task. For basic, general-purpose vision tasks, 1 to 50 cards like the 3090 might be enough. However, cutting-edge areas like visual generation and LLMs often require A100s or A800s, scaling from 1 to even thousands of cards.