1min.AI provides these AI features: - Chat with multiple AI models simultaneously, offering an option to mix contexts among AI models (powered by GPT-4, GPT-3.5 from OpenAI; ClaudeAI from Anthropic; Gemini, PaLM from GoogleAI). - Generate images with Midjourney, DALL-E (OpenAI), and Stable Diffusion (StabilityAI). - Upscale images with Stable Diffusion (StabilityAI). - Generate similar images with DALL-E (OpenAI) and Stable Diffusion (StabilityAI). - Edit images with DALL-E (OpenAI) and Stable Diffusion (StabilityAI). - Transcribe audio using Whisper (OpenAI). - Translate audio using Whisper (OpenAI). - Convert text to speech with TTS (OpenAI).
With this strong foundation, 1min.AI is extending its offerings to provide more AI features and integrate additional AI models, helping users maximize the potential of AI.
No features have been listed yet.
1min.AI's answer:
1min.AI is an all-in-one AI app that offers a variety of AI features powered by various AI models
1min.AI's answer:
Many features. Various AI models. Reasonable price.
1min.AI's answer:
People who want to utilize the power of various AI models
1min.AI's answer:
The AI revolution has recently been robust. we've noticed many AI products that provide a single feature or use just one AI model. However, we cannot fully utilize AI's power by sticking to only one option.
Therefore, we aim to build an all-in-one AI app that centralizes everything in one place, utilizes various AI models, and offers more cost savings.
1min.AI's answer:
ReactJS, NodeJS, MySQL, Kubernetes, AWS
1min.AI's answer:
1min.AI has recently launched, and we haven't yet acquired any major customers.
Based on our record, Neural Networks and Deep Learning seems to be more popular. It has been mentiond 44 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
For neural network theory, I'm very fond of http://neuralnetworksanddeeplearning.com, but you'll need calculus and some linear algebra to understand it. Source: 5 months ago
Alternatively, building them from scratch in numpy is definitely possible and an excellent way to learn the fundamentals. It will take some time though (debugging issues with a hand-rolled LSTM is very, very painful). There's a zillion tutorials/books out there (I think I started with http://neuralnetworksanddeeplearning.com). Source: 5 months ago
- http://neuralnetworksanddeeplearning.com/ The Watch the Caltech telecourse. - Source: Hacker News / 8 months ago
Neural Networks and Deep Learning, a free online book. http://neuralnetworksanddeeplearning.com/. - Source: Hacker News / 9 months ago
Many years ago I was studying deep learning using this resource: * http://neuralnetworksanddeeplearning.com/ I decided to try to implement everything from scratch in Elixir (after initially doing all the math with pen and paper on a trivial example to get the feel of it). Obviously pure elixir was extremely slow, so I started creating NIFs to pass over matrix multiplication to OpenBLAS. Then I was thinking more... - Source: Hacker News / 11 months ago
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