The use of digital imagery and computer vision is increasingly prevalent in various branches of biology, such as ecology and evolutionary biology, aiding in species delineation, adaptation mechanisms understanding, and biodiversity conservation. Researchers are addressing challenges and developing models, such as TreeOfLife-10M, a biology picture dataset, and BIOCLIP, to enhance computer vision in biological tasks.…
ICL, a multinational corporation based in Israel, faced challenges monitoring industrial equipment at their mining sites due to harsh conditions and costly manual monitoring. They partnered with AWS to develop in-house capabilities using machine learning for computer vision, leading to a successful prototype for monitoring mining screeners. This collaboration enabled ICL to build and deploy…
Amazon Comprehend is a natural-language processing (NLP) service offering pre-trained and custom APIs for deriving insights from textual data. It allows training custom named entity recognition (NER) models to extract business-specific entities from documents. The pre-labeling tool automates document annotation using existing tabular entity data, reducing manual effort. The tool accelerates custom entity recognition model…
Text-to-image generation is a fast-growing field in AI, finding applications in media, gaming, e-commerce, advertising, design, art, and medical imaging. Stable Diffusion and Retrieval Augmented Generation (RAG) are innovative models that simplify and enhance prompt creation for text-to-image generation, increasing efficiency and creativity across various industries. AWS provides diverse LLM options, facilitating the construction of…
Talent.com, founded in 2011, offers a unified job search platform covering 75+ countries, 30M+ job listings, and various languages and industries. It collaborates with AWS to develop a job recommendation engine using deep learning. The large-scale data processing pipeline handles JSON Lines from S3, extracting and refining features for the recommendation engine. The pipeline significantly…
Google DeepMind’s new tool, FunSearch, utilizes a large language model to solve a previously unsolved mathematics problem. This approach marks a breakthrough by harnessing large language models for factual discovery in scientific puzzles. FunSearch’s unique methodology of code suggestion and refinement offers potential for diverse problem-solving applications, including the recent success in addressing the bin…
The article discusses the rise of the Productized Services model, which is transforming the services industry and posing a threat to freelancers and employees. It explains the concept, advantages over traditional models, and provides steps to implement the model effectively. The Productized Services model is seen as a game-changer in the services industry.
Pope Francis calls for a legally binding international treaty to regulate artificial intelligence, emphasizing the need for a coordinated global approach to AI regulation. He highlights ethical concerns, specifically in AI weapon systems, stating that autonomous weapon systems cannot be considered morally responsible. The Pope’s message was delivered for the Roman Catholic Church’s World Day…
The research delves into the challenge of extending the forecast horizon in autoregressive neural operators. It highlights instability issues that limit the effectiveness of existing methods, proposing a novel solution that includes dynamic filters generated through a frequency-adaptive MLP. Experimental results demonstrate significant stability improvements. The work showcases a groundbreaking stride in tackling forecast horizon…
Deci has introduced DeciLM-7B, a 7-billion-parameter class language model with high precision and speed, bringing revolutionary changes to various industries. It significantly outperforms its predecessors in accuracy and speed, with potential applications in cost-effective high-volume user interactions. DeciLM-7B, powered by AutoNAC and Infery, exemplifies the future of versatile and efficient AI solutions.
A new open-source system called Dobb-E can train robots for domestic tasks using real home data, addressing the lack of training data in robotics. Utilizing an iPhone and reacher-grabber stick to collect data, the system achieved an 81% success rate in executing household tasks over 30 days. The team aims to expand Dobb-E’s capabilities.
Indiana University researchers have developed Brainoware, a groundbreaking artificial intelligence system that combines lab-grown brain cells with computational circuits to achieve speech recognition and mathematical problem-solving. This innovative technology showcases potential in advancing AI capabilities and poses ethical considerations. While challenges exist, Brainoware offers hope for future applications in neuroscience and computing paradigms.
Image-text alignment models aim to connect visual content and textual information, but aligning them accurately is challenging. Researchers from Tel Aviv University and others developed a new approach to detect and explain misalignments. They introduced ConGen-Feedback, a method to generate contradictions in captions with textual and visual explanations, showing potential to improve NLP and computer…
Google AR & VR and University of Central Florida collaborated on a study to validate VALID, a virtual avatar library comprising 210 fully rigged avatars representing seven races. The study, which involved a global participant pool, revealed consistent recognition for some races and own-race bias effects. The team highlighted implications for virtual avatar applications and…
The study introduces “Vary,” a method to expand the vision vocabulary in Large Vision-Language Models (LVLMs) for enhanced perception tasks. This method aims to improve fine-grained perception, particularly in document-level OCR and chart understanding. Experimental results demonstrate Vary’s effectiveness, outperforming other LVLMs in certain tasks. For more information, visit the Paper and Project.
Meta’s introduction of Emu as a generative AI for movies signifies a pivotal moment where technology and culture merge. Emu promises to revolutionize access to information and entertainment, offering unprecedented personalization. However, the potential drawbacks of oversimplification and reinforcement of biases call for a vigilant and balanced approach to utilizing this powerful tool.
LLM360 is a groundbreaking initiative promoting comprehensive open-sourcing of Large Language Models. It releases two 7B parameter LLMs, AMBER and CRYSTALCODER, with full training code, data, model checkpoints, and analyses. The project aims to enhance transparency and reproducibility in the field by making the entire LLM training process openly available to the community.
Numerical simulations used for climate policy face limitations in accurately representing cloud physics and heavy precipitation due to computational constraints. Integrating machine learning (ML) can potentially enhance climate simulations by effectively modeling small-scale physics. Challenges include obtaining sufficient training data and addressing code complexity. ClimSim, a comprehensive dataset, aims to bridge this gap by facilitating…
The MIT-Pillar AI Collective has selected three fellows for fall 2023. They are pursuing research in AI, machine learning, and data science, with the goal of commercializing their innovations. The Fellows include Alexander Andonian, Daniel Magley, and Madhumitha Ravichandra, each working on innovative projects in their respective fields as part of the program’s mission to…
LLMLingua is a novel compression technique launched by Microsoft AI to address challenges in processing lengthy prompts for Large Language Models (LLMs). It leverages strategies like dynamic budget control, token-level iterative compression, and instruction tuning-based approach to significantly reduce prompt sizes, proving to be both effective and affordable for LLM applications. For more details, refer…