What is ChatGPT?
Chat Generative Pre-trained Transformer is a chatbot developed by OpenAI. ChatGPT is built on OpenAI’s GPT-3.5 of the Large Language Model, and is fine with both supervised and reinforcement learning techniques. ChatGPT and GPT 3.5 were trained on the Azure AI supercomputing infrastructure. Can chat, answer questions, create content, write and debug code, test, manipulate data, explain and tutor, and more !
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What is ChatGPT used for?
ChatGPT can provide information in clear, simple sentences rather than just a list of Internet links. It can explain concepts in ways that people can easily understand. It can even generate ideas from scratch including business strategies, Christmas gift suggestions, blog topics and holiday plans.
ChatGPT creator OpenAI has released Point-E, a new AI tool for generating 3D images in minutes. Point-E, unlike other 3D image generators, does not require a high-end computer to work and can generate a model in less than two minutes with a single Nvidia V100.
OpenAI, the company behind the AI-powered ChatGPT chatbot and Doll-e text-to-image generator, has released a new tool that can generate 3D objects based on simple text input.
Dubbed Point-e, its open source is available on Github, although it’s a bit complicated to try as users will need to be well-versed with command-line tools, and the system needs Python, unlike ChatGPT.
Where users can sign up to a website and test its capabilities.
The developers of Point-E have also published a research paper that explains how the platform works and what are its limitations.
They claim that the Point-E, unlike other 3D image generators, does not require a high-end computer to work and can generate a model in less than two minutes with a single Nvidia V100 GPU.
How does Point-e work?
Simply put, similar to OpenAI’s Dull-E, Point-E can generate 3D models with simple commands in English. The paper shows some bizarre examples such as “a corgi wearing a red Santa hat”, “a multicolored rainbow pumpkin”, “a pair of 3D glasses”, and “an avocado chair, a chair imitating an avocado.”
Although the tool does not produce a 3D model in the traditional sense, it produces a number of data points that represent a 3D shape.
The tool processes the final output after analyzing the input based on the “several million 3D models” it has already analyzed.
wrote in the paper titled “Point E: A system for generating 3D point clouds from complex signals”. To create a 3D object from a text prompt, we first sample and then sample an image using a text-to-image model.
A 3D object is optimized on the sample image. Both of these steps can be performed in several seconds, and do not require costly optimization procedures.
According to the research paper, Point-E is capable of efficiently producing diverse and complex 3D shapes conditioned on a text prompt.
Our approach can serve as a starting point for further work in the field of text-to-3D synthesis. Interestingly, the researchers at Point-E used OpenAI’s ChatGPT to write the paper.
The developers claim that the 3D objects generated by the Point-E can help a great deal in a wide range of applications such as virtual reality, gaming and industrial design.
Limitations of Point-E
Similar to the 2D image generator Dall-E, Point-E also fails to analyze the input, and its final output appears in low resolution.
Furthermore, the final output does not capture the “microscopic shape or texture”. But the Point-E technique can be improved as it analyzes more real-world images.
Once the system is improved, it can effectively challenge Google’s Dream Fusion, which produces more accurate results but requires powerful hardware.