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Google's flagship model Gemini is natively multimodal with text capabilities matching GPT4 while also being able to operate on many other data sequences. It also trained Alpha Code 2, which is an 85th percentile coder on code forces. Alpha Code 2 will be available in Google’s API after December 13th.
Meta has launched 'Imagine,' a standalone image generator with its own website featuring generative AI that creates images from text prompts.
Microsoft is enhancing its Copilot service with new features, including OpenAI's latest GPT-4 Turbo model, an upgraded DALL-E 3 model, a new code interpreter feature, and a 'Deep Search' function in Bing.
This paper uses natural language to describe what is different between two collections of images. This is a novel problem and a challenging one. The solution involves captioning and reranking the individual images and summarizing them with a language model.
Researchers have developed Diffusion-SS3D, a new method to improve semi-supervised 3D object detection using diffusion models. This approach involves adding noise to object size and class label distributions in 3D space and then using the diffusion model to denoise and generate better bounding box outputs.
This project introduces BenchLMM, a benchmark designed to test the robustness of Large Multimodal Models like GPT-4V and LLaVA against various image styles.
Apple quietly released a cool Array framework that is accelerated on Mac devices because of unified memory. It is simple and clean and provides some GPU support as well.
Stable Fast is an inference engine for HuggingFace diffusion models.
Switch your project to open source in just a few lines of code.
This study introduces the use of the Oogiri humor generation game to explore the Leap-of-Thought capabilities in multimodal LLMs. This approach challenges LLMs to exhibit non-sequential thinking, a skill crucial for generating creative and humorous responses to various types of multimodal information.
Lightspeed shares insights from Google and TitanML about the ins and outs of optimizing LLMs whether via prompting or fine-tuning.
While automation will likely be the way of the future, today, it’s all about augmenting your existing processes/self without having to rip and replace everything. Don’t fall into the trap of just augmenting yourself to do your job better - thinking through what and how to automate things and viewing your role holistically will allow you to find the best use of AI for your needs.
Segment Anything is a great model, but it is slow to run. Efficient Segment Anything is a new model that uses a number of optimizations to run significantly faster.
Right before leaving the company, Elon Musk implored OpenAI to move faster, a departure from his typically more skeptical comments toward AI.
Build in-app AI chatbots and AI-powered Textareas into React web apps.