This study addresses the problem of text-to-image generative models’ inability to consistently generate images. They propose a novel approach to generating consistent portrayals of characters in different circumstances based on a text prompt. The researchers use a clustering technique to extract a representation that captures common traits among images and repeatedly refine the generated model…
NVIDIA has introduced the HELPSTEER dataset, a collection of annotated responses that influence helpfulness in language models. The dataset covers qualities such as accuracy, coherence, complexity, verbosity, and overall helpfulness. Researchers used the dataset to train the Llama 2 70B model, which outperformed other models on the MT Bench with a score of 7.54. The…
OpenAI, initially a non-profit, shifted to a for-profit structure in 2019, straying from its effective altruism mission. Effective altruism seeks to maximize positive impacts while long-termism focuses on reducing existential risks. OpenAI’s commercial expansion created a conflict between altruistic goals and practical business needs, leading to a clash of ideologies within the company. The recent…
Spanish agency The Clueless has created an AI-generated model named Aitana, who has over 125,000 followers on Instagram. With the aim of reducing costs and avoiding the challenges of working with human influencers, The Clueless has found success in using AI models. The use of AI in the modeling and influencer industries raises ethical and…
Summary: Surveys are often used incorrectly in the design cycle due to the assumption that they are quick and easy. However, different types of surveys can be effective at various stages of the cycle. User research should be conducted at different stages, with surveys commonly associated with the Listen phase.
Summary: An article about AI-chatbot interactions highlights the key components found in most prompts, such as requests, framing context, format specification, and references to previous answers or sources. The absence of these components can result in inefficient conversations. Designers can enhance user experience by incorporating AI-interface elements that facilitate the inclusion of prompt components. A…
This article discusses a novel method for generating 3D human avatars from 2D image collections. The proposed method aims to produce high-quality images and accurate geometry, particularly when modeling loose clothing. The research team introduces a monolithic design that models both the human body and clothing together, along with multiple discriminators to enhance geometric detail.…
Amazon Bedrock is a generative AI service that simplifies the creation of product descriptions for e-retailers. It offers high-performing foundation models from leading AI companies and allows retailers to tailor the descriptions to their target audience. Bedrock also enables faster approvals, improved product listing velocity, future-proofing, and fosters a culture of innovation. With additional capabilities…
Formula 1 is set to trial an AI Computer Vision system at the Abu Dhabi Grand Prix to analyze track limit incidents. Currently, human stewards review video feeds during races to identify infringements, but the new AI system will do the bulk of the work. The technology aims to save time and improve accuracy in…
The text highlights the transformative impact of generative artificial intelligence (AI) on the internet landscape. Major platforms are undergoing significant changes, with AI-driven content on the rise. Challenges include Google’s search overhaul, Twitter’s bot and verification issues, Amazon and TikTok’s content quality concerns, layoffs in online media companies, and the demand for “AI editors” in…
The text discusses various optimization algorithms that can be used to improve the training of neural networks beyond the traditional gradient descent algorithm. These algorithms include momentum, Nesterov accelerated gradient, AdaGrad, RMSProp, and Adam. The author provides explanations, equations, and implementation examples for each algorithm. The performance of these algorithms is compared using a simple…
This article discusses the challenges of analyzing data that follows a Power Law distribution and presents a technique called the “Log-Log approach” to detect Power Laws in real-world data. It also introduces the Maximum Likelihood method as a more mathematically sound approach to estimating the parameters of a Power Law distribution. The article provides example…
Summary: The text discusses the key elements that power advanced recommendation engines, focusing on two-tower neural networks and the use of negative sampling. It explores the efficiency and effectiveness of two-tower networks in ranking, the impact of loss functions and negative sampling on model accuracy, and the role of negative sampling in recommendation systems. The…
Researchers have developed an active learning workflow to create a machine learning (ML) model for efficient prediction of hydrogen combustion. The workflow expands the dataset and utilizes negative design data acquisition and metadynamics simulations. The ML model accurately predicts transition states and reaction mechanisms, providing insights into potential energy surfaces. The approach shows promise for…
LLMs are powerful linguistic agents used for programming tasks, but there is a gap between their capabilities in controlled settings and real-world programming scenarios. Existing benchmarks focus on code generation, but real-world programming often involves using existing libraries. A new study introduces ML-BENCH, a dataset to evaluate LLMs’ ability to interpret user instructions and generate…
This article discusses four different methods of passing arguments to Python scripts. For more information, please read the full article on Towards Data Science.
The article discusses how to use Pandas and the YouTube Data API to obtain statistical insights. For more details, please visit Towards Data Science.
Artificial Intelligence and deep learning have made significant advancements in technology, enabling robots to perform tasks previously limited to human intelligence. Symbolic Regression in AI plays an important role in scientific research, focusing on algorithms that interpret complex patterns in datasets. The Φ-SO framework, a Physical Symbolic Optimization method, automates the process of finding analytic…
This article discusses the use of network analytics to analyze international trade data provided by UN Comtrade. The author highlights the importance of this approach in gaining insights into global trade patterns. For more information, read the full article on the Towards Data Science website.
OpenAI made headlines this week with a dramatic series of CEO appointments and firings. Sam Altman was initially removed as CEO, leading to a backlash from OpenAI staff. However, it seems that Altman will be reinstated as CEO under a new board. In other news, Microsoft expressed interest in attracting disgruntled OpenAI staff and released…