Large open-source pre-training datasets are important for the research community in exploring data engineering and developing transparent, open-source models. However, there’s a major shift from frontier labs to training large multimodal models (LMMs) that need large datasets containing both images and texts. The capabilities of these frontier models are advancing quickly, creating a large gap… →

Meta’s Fundamental AI Research (FAIR) team has announced several significant advancements in artificial intelligence research, models, and datasets. These contributions, grounded in openness, collaboration, excellence, and scale principles, aim to foster innovation and responsible AI development. Meta FAIR has released six major research artifacts, highlighting their commitment to advancing AI through openness and collaboration. These… →

Modern bioprocess development, driven by advanced analytical techniques, digitalization, and automation, generates extensive experimental data valuable for process optimization—ML methods to analyze these large datasets, enabling efficient exploration of design spaces in bioprocessing. Specifically, ML techniques have been applied in strain engineering, bioprocess optimization, scale-up, and real-time monitoring and control. Conventional sensors in chemical and… →

Machine learning methods, particularly deep neural networks (DNNs), are widely considered vulnerable to adversarial attacks. In image classification tasks, even tiny additive perturbations in the input images can drastically affect the classification accuracy of a pre-trained model. The impact of these perturbations in real-world scenarios has raised significant security concerns for critical applications of DNNs… →

Evaluating Large Language Models (LLMs) is a challenging problem in language modeling, as real-world problems are complex and variable. Conventional benchmarks frequently fail to fully represent LLMs’ all-encompassing performance. A recent LinkedIn post has emphasized a number of important measures that are essential to comprehend how well new models function, which are as follows. MixEval… →

Generative models are designed to replicate the patterns in the data they are trained on, typically mirroring human actions and outputs. Since these models learn to minimize the difference between their predictions and human-generated data, they aim to match the quality of human expertise in various tasks, such as answering questions or creating art. This… →

In a significant leap forward for AI, Together AI has introduced an innovative Mixture of Agents (MoA) approach, Together MoA. This new model harnesses the collective strengths of multiple large language models (LLMs) to enhance state-of-the-art quality and performance, setting new benchmarks in AI.  MoA employs a layered architecture, with each layer comprising several LLM… →

In the modern world, efficiency is key. Companies are constantly seeking ways to streamline their operations, reduce bottlenecks, and increase productivity.  Bitrix24 is comprehensive platform that offers a suite of tools designed to enhance collaboration, manage tasks, and automate workflows. In this article will delve into some of the new key features of Bitrix24 from… →