Qloo
Qloo, the "Cultural AI", is capable of decoding and forecasting consumer tastes around the world. Privacy-first API that predicts global consumer preferences, catalogs hundreds of million of cultural entities, and is privacy-first. Our API provides contextualized personalization and insight based on deep understanding of consumer behavior. We have access to more than 575,000,000 people, places, and things. Our technology allows you to see beyond trends and discover the connections that underlie people's tastes in their world. Our vast library includes entities such as brands, music, film and fashion. We also have information about notable people. Results are delivered in milliseconds. They can be weighted with factors like regionalization and real time popularity. Companies who want to use best-in-class data to enhance their customer experiences. Our flagship recommendation API provides results based on demographics and preferences, cultural entities, metadata, geolocational factors, and metadata.
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Vehicle Acquisition Network (VAN)
Vehicle Acquisition Network (VAN) is an automotive software platform built to help car dealerships acquire high-quality used vehicles directly from private sellers—without relying on auctions. As wholesale prices rise and vehicle availability tightens, VAN empowers dealers with tools to source inventory faster, more profitably, and with greater control.
VAN aggregates local FSBO (for-sale-by-owner) listings, applies real-time market data to assess profitability, and automates communication with sellers at scale. Buyers can manage leads, track seller conversations, and streamline acquisition workflows through an intuitive CRM-style dashboard designed specifically for dealership teams.
For dealers who don’t have dedicated acquisition staff, VAN offers a Managed Buyer program, pairing stores with expert buyers who actively source, engage, and negotiate with private sellers on their behalf—saving time and boosting acquisition volume without internal hiring.
VAN is trusted by hundreds of dealerships across North America—from independent rooftops to franchise groups—looking to beat Carvana and CarMax at their own game. It's the smarter way to buy cars.
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Uni-1
UNI-1, a groundbreaking multimodal artificial intelligence model from Luma AI, combines visual generation and reasoning within a singular framework, marking progress towards achieving multimodal general intelligence. This innovative design addresses the challenges faced by conventional AI systems, where various components like language models and image generators function in isolation, lacking cohesive reasoning. By merging these features, UNI-1 enables seamless interaction between language comprehension, visual analysis, and image creation, allowing the model to logically interpret scenes, follow instructions, and produce visual outputs that adhere to both logical and spatial parameters. Central to its architecture is a decoder-only autoregressive transformer that processes both text and images as a unified sequence of tokens, facilitating a coherent interaction between linguistic and visual data. This integration not only enhances the efficiency of the AI but also broadens the scope of its applications across various domains.
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CodeT5
CodeT5 is an innovative pre-trained encoder-decoder model specifically designed for understanding and generating code. This model is identifier-aware and serves as a unified framework for various coding tasks. The official PyTorch implementation originates from a research paper presented at EMNLP 2021 by Salesforce Research. A notable variant, CodeT5-large-ntp-py, has been fine-tuned to excel in Python code generation, forming the core of our CodeRL approach and achieving groundbreaking results in the APPS Python competition-level program synthesis benchmark. This repository includes the necessary code for replicating the experiments conducted with CodeT5. Pre-trained on an extensive dataset of 8.35 million functions across eight programming languages—namely Python, Java, JavaScript, PHP, Ruby, Go, C, and C#—CodeT5 has demonstrated exceptional performance, attaining state-of-the-art results across 14 different sub-tasks in the code intelligence benchmark known as CodeXGLUE. Furthermore, it is capable of generating code directly from natural language descriptions, showcasing its versatility and effectiveness in coding applications.
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