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LLMs today suffer from inaccuracies at scale, but that doesn’t mean you should cede competitive ground by waiting to adopt generative AI. Building an AI-ready workforce with data.world OWLs, as imagined by OpenAI’s GPT-4Every enterprise technology has a purpose or it wouldn’t exist. Generative AI’s enterprise purpose is to produce human-usable output from technical, business,…
Adversarial attacks in image classification, a critical issue in AI security, involve subtle changes to images that mislead AI models into incorrect classifications. The research delves into the intricacies of these attacks, particularly focusing on multi-attacks, where a single alteration can simultaneously affect multiple images’ classifications. This phenomenon is not just a theoretical concern but…
Solving some of the major challenges of the 21st Century, such as producing clean electricity or developing high temperature superconductors, will require us to design new materials with specific properties. To do this on a computer requires the simulation of electrons, the subatomic particles that govern how atoms bond to form molecules and are also…
The work is done in a Google Colab Pro with a V100 GPU and High RAM setting for the steps involving LLM. The notebook is divided into self-contained sections, most of which can be executed independently, minimizing dependency on previous steps. Data is saved after each section, allowing continuation in a new session if needed.…
Artificial intelligence has always faced the issue of producing high-quality videos that smoothly integrate multimodal inputs like text and graphics. Text-to-video generation techniques now in use frequently concentrate on single-modal conditioning, using either text or images alone. The accuracy and control researchers can exert over the created films are limited by this unimodal technique, making…
Research
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Today, the world is abuzz with LLMs, short for Large Language models. Not a day passes without the announcement of a new language model, fueling the fear of missing out in the AI space. Yet, many still struggle with the basic concepts of LLMs, making it challenging to keep pace with the advancements. This article…
Diffusion models are a significant component in generative models, particularly for image generation, and these models are undergoing transformative advancements. These models, functioning by transforming noise into structured data, especially images, through a denoising process, have become increasingly important in computer vision and related fields. Their capability to convert pure noise into detailed images has…
In our recent paper we explore how multi-agent deep reinforcement learning can serve as a model of complex social interactions, like the formation of social norms. This new class of models could provide a path to create richer, more detailed simulations of the world. Humans are an ultra social species. Relative to other mammals we…