Large language model
Amazon Personalize has introduced the Next Best Action feature, which uses machine learning to recommend personalized actions to individual users in real time. This helps improve customer engagement and increase conversion rates by providing users with relevant and timely recommendations based on their past interactions and preferences. With Next Best Action, brands can deliver personalized…
Russian President Vladimir Putin has announced plans to drive forward AI development in Russia. He aims to counter what he perceives as a Western monopoly in AI and ensure Russian solutions are used in the creation of reliable and transparent AI systems. Putin expressed concerns about Western AI algorithms erasing Russian cultural and scientific achievements,…
Recent economic policies in the UK, particularly the “full expensing” tax break, have raised concerns among leaders in the film, publishing, and music sectors. They are worried that these policies could lead to machines replacing humans and redirecting funds to foreign tech companies. Additionally, there is a debate about the use of intellectual property in…
Large Language Models (LLMs) are valuable assets, but training them can be challenging. Efficient training methods focus on data and model efficiency. Data efficiency can be achieved through data filtering and curriculum learning. Model efficiency involves designing the right architecture and using techniques like weight sharing and model compression. Pre-training and fine-tuning are common training…
Researchers from the University of Chicago and Snap Research have developed a 3D paintbrush that can automatically texture local semantic regions on meshes using text descriptions. The method produces texture maps that seamlessly integrate into standard graphics pipelines. The team also developed a technique called cascaded score distillation (CSD) to enhance details and resolution. The…
Recent advances in Neural Radiance Fields (NeRFs) have demonstrated advancements in 3D graphics and perception. The 3D Gaussian Splatting (GS) framework has further enhanced these improvements. However, more applications are needed to create new dynamics. A research team has developed PhysGaussian, a physics-integrated 3D Gaussian method that allows for realistic generative dynamics in various materials.…
Inflection AI has developed Inflection-2, a highly capable language model that aims to outperform existing solutions such as those from Google and Meta. The model excels in common sense and mathematical reasoning, showcasing its abilities in these domains despite not being its main focus during training. Inflection-2 has outperformed Google and Meta’s models in benchmark…
Stanford researchers have developed BLASTNet-2, a revolutionary dataset that aims to advance the understanding and application of fluid dynamics in various fields. With five terabytes of data derived from over 30 different configurations, BLASTNet-2 offers a centralized platform for fluid dynamics data and promotes interdisciplinary collaborations. It has potential applications in areas such as renewable…
Researchers from UC Berkeley, Toyota Technological Institute at Chicago, ShanghaiTech University, and other institutions propose a new deep network design called CRATE, which stands for “coding-rate” transformer. CRATE aims to bridge the gap between theory and practice in deep learning by providing a white-box architecture that is interpretable and performs well on various learning tasks.…
Researchers from Meta have introduced a new approach called System 2 Attention (S2A) to improve the reasoning capabilities of Large Language Models (LLMs). LLMs often make simple mistakes due to weak reasoning and sycophancy. S2A mitigates these issues by identifying and extracting relevant parts of the input context. It also improves factuality, objectivity, and performance…
The rise of AI has created new career opportunities, such as prompt engineering. Prompt engineers specialize in crafting text-based prompts for AI systems to ensure accurate responses. This field is experiencing job growth and offers competitive salaries, with over 7,000 jobs requiring generative AI expertise in the US alone. Technical, linguistic, and analytical skills are…
Student of Games (SoG) is a general-purpose algorithm developed by EquiLibre Technologies, Sony AI, Amii, Midjourney, and Google’s DeepMind project. It combines search, learning, and game-theoretic reasoning to achieve high performance in both perfect and imperfect information games. SoG demonstrates the potential for creating artificial general intelligence by teaching computers to master a wide range…
Jason Eshraghian from UC Santa Cruz has developed snnTorch, an open-source Python library for implementing spiking neural networks. The library aims to address the inefficiency and environmental impact of traditional neural networks by emulating the brain’s processing mechanisms. With over 100,000 downloads, snnTorch has gained traction and is being used in various applications, including NASA’s…
This text discusses the HyperHuman framework, which aims to generate realistic and diverse human images. It highlights the challenges faced by previous models in creating coherent anatomical structures and proposes a unified framework that incorporates structural information like body skeletons and spatial geometry. The paper introduces the HumanVerse dataset and describes two modules, the Latent…
Researchers have proposed a new method called Random Slices Mixing Data Augmentation (RSMDA) for deep learning. RSMDA blends sections of images to create diverse training samples, overcoming the limitations of single-image-based methods. The strategy RSMDA(R), focusing on row-wise mixing, consistently outperformed existing techniques in reducing error rates and showcased robustness against adversarial attacks. RSMDA shows…
A recent study by researchers from the Harbin Institute of Technology and Huawei explores the issue of hallucinations in large language models (LLMs). LLMs have revolutionized natural language processing but have a tendency to generate information that seems credible but lacks factual basis. The study reclassifies hallucination types and proposes detection techniques to minimize their…
The RPRS model addresses the limitations of current search methods for long documents. It computes relevance between a query document and candidate documents based on proportional matches across their sentences. The approach consists of three stages: sentence encoding, finding the most relevant sentence sets, and proportion-based relevance scoring. The RPRS method significantly outperforms previous techniques…
Nvidia will delay the release of its H20 AI chip designed for the Chinese market until early 2024. The delay is a result of strategic challenges and compliance requirements, including integrating the chip into server infrastructure. The H20 chip aims to help Nvidia maintain its market share in China amid tighter export rules, as competitors…
Researchers have discovered new techniques for coaxing AI models into performing actions they are programmed to avoid. The study introduces “persona modulation,” a method where one AI model designs prompts to manipulate another model. By assuming a harmful persona and bypassing safety protocols, the target model’s rate of harmful outputs increased significantly. The research highlights…
This article discusses the use of Convolutional Neural Networks (CNNs) for feature extraction in image classification tasks. It explains how CNNs recognize patterns in an image to classify it and demonstrates an example of feature extraction using TensorFlow and the Keras functional API. The article also compares the feature extraction capabilities of two CNNs trained…