Dive Thinking Like an Annotator: Generation of Dataset Labeling Instructions

We are all amazed by the advancement we have seen in AI models recently. We’ve seen how generative models revolutionized themselves by going from a funky image generation algorithm to the point where it became challenging to differentiate the AI-generated content from real ones.  All these advancements are made possible thanks to two main points….

Meet LLaMaTab: An Open-Source Chrome Extension that Runs an LLM Entirely in the Browser

LLaMaTab – An Insightful Chrome Extension A Chrome add-on called LLaMaTab New Tab will display a different image of a llama every time a new tab starts. It’s a silly add-on, but it can keep one going when things become tough. LLaMaTab New Tab is a fantastic extension if one is using Chrome and wants…

Meet StyleAvatar3D: A New AI Method for Generating Stylized 3D Avatars Using Image-Text Diffusion Models and a GAN-based 3D Generation Network

Since the advent of large-scale image-text pairings and sophisticated generative model topologies like diffusion models, generative models have made tremendous progress in producing high-fidelity 2D pictures. These models eliminate manual involvement by allowing users to create realistic visuals from text cues. Due to the lack of diversity and accessibility of 3D learning models compared to…

Do You Really Need Reinforcement Learning (RL) in RLHF? A New Stanford Research Proposes DPO (Direct Preference Optimization): A Simple Training Paradigm For Training Language Models From Preferences Without RL

When trained on massive datasets, huge unsupervised LMs acquire powers that surprise even their creators. These models, however, are trained on information produced by people with a diverse range of motivations, objectives, and abilities. Not all of these ambitions and abilities may be emulated. It is important to carefully select the model’s desired responses and…

Meet CHARM: A New Artificial Intelligence AI Tool that can Decode Brain Cancer’s Genome during Surgery for Real-Time Tumor Profiling

In a groundbreaking development, Harvard researchers have unveiled an artificial intelligence (AI) tool capable of rapidly decoding a brain tumor’s DNA during surgery, providing critical information that can significantly impact patient outcomes. This innovative technology, known as CHARM (Cryosection Histopathology Assessment and Review Machine), has the potential to revolutionize the field of neurosurgery by enabling…

Researchers from UC Berkeley Introduce Gorilla: A Finetuned LLaMA-based Model that Surpasses GPT-4 on Writing API Calls

A recent breakthrough in the field of Artificial Intelligence is the introduction of Large Language Models (LLMs). These models enable us to understand language more concisely and, thus, make the best use of Natural Language Processing (NLP) and Natural Language Understanding (NLU). These models are performing well on every other task, including text summarization, question…

We know That LLMs Can Use Tools, But Did You Know They Can Also Make New Tools? Meet LLMs As Tool Makers (LATM): A Closed-Loop System Allowing LLMs To Make Their Own Reusable Tools

Large language models (LLMs) have excelled in a wide range of NLP tasks and have shown encouraging evidence of achieving some features of artificial general intelligence. Recent research has also revealed the possibility of supplementing LLMs with outside tools, considerably increasing their problem-solving powers and efficiency, similar to how human intelligence has evolved. However, the…

This AI Paper Proposes Retentive Networks (RetNet) as a Foundation Architecture for Large Language Models: Achieving Training Parallelism, Low-Cost Inference, and Good Performance

Transformer, which was first developed to address the sequential training problem with recurrent models, has since come to be accepted as the de facto architecture for big language models. Transformers’ O(N) complexity per step and memory-bound key-value cache make it unsuitable for deployment, trade-off training parallelism for poor inference. The sequence’s lengthening slows inference speed,…

Study finds ChatGPT boosts worker productivity for some writing tasks

Amid a huge amount of hype around generative AI, a new study from researchers at MIT sheds light on the technology’s impact on work, finding that it increased productivity for workers assigned tasks like writing cover letters, delicate emails, and cost-benefit analyses. The tasks in the study weren’t quite replicas of real work: They didn’t…

On-device diffusion plugins for conditioned text-to-image generation

Posted by Yang Zhao and Tingbo Hou, Software Engineers, Core ML In recent years, diffusion models have shown great success in text-to-image generation, achieving high image quality, improved inference performance, and expanding our creative inspiration. Nevertheless, it is still challenging to efficiently control the generation, especially with conditions that are difficult to describe with text….