Researchers have proposed SMPLer-X, a generalist foundation model for 3D/4D human motion capture from monocular inputs. The model shows impressive generalization capabilities and outperforms previous benchmark results. The research highlights the need for more diverse and extensive datasets for accurate human pose and shape estimation. The researchers also emphasize the value of utilizing multiple datasets…
This article introduces the Builder design pattern in Python and explains its importance in writing clean and reusable code. The Builder pattern is part of the creational design pattern class and simplifies the creation of objects by breaking it down into individual steps. The article provides a code example demonstrating how to implement the Builder…
The text discusses the challenges faced by the computer vision community and highlights the development of multimodal foundation models with vision and vision-language capabilities. It explores various instructional strategies and introduces important multimodal conceptual frameworks and models such as CLIP, BEiT, CoCa, UniCL, MVP, and BEiTv2. The text also discusses T2I production, spatial controllability in…
The author discusses using a Bayesian framework to choose between two restaurants based on reviews. Initially, with no reviews, all ratings are equally likely. The author then updates these beliefs based on observed data, using the Dirichlet distribution. The posterior ratings of the two restaurants are calculated, and the probability that restaurant A is better…
Fine-tuning commercial language models (LLMs) can bypass safety measures and lead to dangerous responses. Researchers found that fine-tuning GPT-3.5 with malicious examples deactivated its safety switch. This raises concerns about the safety and liability of fine-tuned models. Even proprietary models like GPT-3.5 can be compromised through fine-tuning, highlighting the need for robust safety mechanisms. Achieving…
Researchers from SLAC National Accelerator Laboratory, Stanford University, MIT, and Toyota Research Institute have developed a new approach using computer vision to analyze X-ray movies of lithium-ion batteries. By analyzing every pixel, they were able to uncover new physical and chemical details of battery cycling, including the impact of carbon coating thickness on lithium-ion flow.…
Large language models like ChatGPT have the potential to transform various fields but integrating them into real-world products poses challenges. A powerful strategy called retrieval-augmented generation (RAG) has emerged, allowing connection to external information sources for more accurate outputs. Several articles explore the intricacies and practical considerations of working with RAG, helpful for those in…
AI-driven apps are becoming popular for enhancing professional online images. Apps like Remini, Try It On AI, and AI Suit Up use artificial intelligence to create polished profile photos. While some users find these images to be genuine and professional, others believe they appear noticeably artificial. Cost is a driving factor, as professional photo sessions…
Researchers from Microsoft and ETH Zurich have released a dataset called “HoloAssist” to address the challenges of developing AI assistants for real-world tasks. The dataset contains extensive recordings of participants collaborating on physical manipulation tasks, capturing various sensor modalities and annotations. The dataset enables the development of anticipatory and proactive AI assistants for real-world scenarios,…
Predictive policing uses advanced analytics and machine learning to anticipate crimes before they happen. By analyzing historical crime data and other relevant information, algorithms can identify patterns and hotspots of criminal activity. However, recent investigations have revealed failures and ethical concerns, highlighting biases and the potential for inaccurate predictions. The efficacy of predictive policing software,…
MedARC has developed MindEye, an AI model that can analyze fMRI scans and retrieve the exact original image the person was looking at, even if the images are similar. The model can also identify similar images from a large image database. While impressive, the fMRI data collection process and limited training data are challenges. Nevertheless,…
Text-to-image diffusion models have dominated generative tasks by producing high-quality outcomes. Recently, image-to-image transformation tasks have been guided by diffusion models with external image conditions. However, the iterative and time-consuming nature of diffusion models limits their practical use. Recent research proposes distillation techniques to speed up sampling and condense the models. A single-stage distillation method…
Discover the quick and simple method for running Nougat using only a few lines of code.
Diffusion models have gained attention in the AI community for their ability to reverse the process of turning data into noise and understand complex data distributions. While they excel in some areas, they have limitations in tasks like picture translation. To address this, researchers have introduced Denoising Diffusion Bridge Models (DDBMs), which use diffusion bridges…
KOSMOS-G is an AI model developed by researchers at Microsoft Research, New York University, and the University of Waterloo. It can generate detailed images from text descriptions and multiple pictures. It uses a combination of pre-training and fine-tuning stages to align text and images and generate accurate pictures. KOSMOS-G has the capability to replace CLIP…
The article discusses the advancements in text-to-image generation using computer vision and generative modeling. It highlights the principles and features of a new model called Kandinsky, which combines latent diffusion techniques with image prior models. Kandinsky shows top-tier performance in image generation quality and achieves an impressive FID score. Future research directions are also mentioned.
Dutch scientists have developed a deep learning tool called Sturgeon, which aids brain surgeons in classifying tumor types and subtypes during surgery. By examining specific segments of a tumor’s DNA, the AI tool provides rapid insights that can guide surgeons in their approach. In initial tests, the tool achieved a diagnostic turnaround time of less…
Google’s Discord chat for its AI chatbot Bard is used by engineers, product managers, and designers to evaluate its performance. Internal discussions revealed skepticism about Bard’s effectiveness compared to other AI chatbots. Complaints have arisen about the generation of false information, leading to the introduction of a search button to validate AI-generated responses. Other controversies…
The Julia programming language implements a unique paradigm called Multiple Dispatch, which is particularly effective for data science. An important technique in Julia is abstraction, which allows for flexibility when working with different types of data. Abstraction is implemented using multiple dispatch, and it is crucial to understand how to use it effectively. Additionally, when…
This text explains the concept of Intersection over Union (IoU) in object detection models. IoU measures the accuracy of the object detector by evaluating the overlap between the detection box and the ground truth box. The text provides examples and Python code to compute and interpret IoU values.