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AI-Generated Results

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Liquid Foundation Models (LFMs) are a new generation of generative AI models developed by Liquid AI, designed to deliver state-of-the-art performance across various scales while maintaining a smaller memory footprint and more efficient inference compared to traditional transformer-based architectures. Built from first principles, LFMs are versatile and capable of processing sequential data types, including text, audio, video, time series, and signals.

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Vind.ai's Scenario Modeling and Comparison tool empowers users to create, analyze, and compare multiple business scenarios, facilitating informed decision-making. By simulating various outcomes, organizations can anticipate potential challenges and opportunities, leading to strategic planning and risk mitigation.

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PolyModels Hub is a British software startup specializing in SaaS solutions for pharmaceutical process development. Their platform leverages artificial intelligence to assist scientists in modeling, simulating, and gaining insights across all protocols involved in transforming chemical compounds into safe drug products.

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Arima’s self-directed MMM is designed to understand how various ads impact sales. By analyzing past data, marketing mix modeling reveals which advertising channels—such as TV, print, radio, and online ads—influence customer behavior and correlate with sales, helping to determine a ROI curve.

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Evaluation of animal's health status (lameness) by gait analysis to predict disease (osteoarthritis, etc.).

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Companies use multiple media channels and promotions such as TV, radio, internet, mobile and print advertising as well as price discounts, coupons and bundled offerings. A complex mix of own actions, competitors’ actions, regulatory changes and market events affect a product’s performance. TransOrg offers Market Mix Modelling solution to evaluate the effectiveness of each campaign and each channel independently and also to determine what actually drives the sales.

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Evaluation of animal's health status (lameness) by gait analysis to predict disease (osteoarthritis, etc.).

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Akasia Infrastructure Modeler (AIM is a Software-as-a-Service (SaaS solution designed to facilitate the migration of on-premises infrastructure to cloud environments. By automatically discovering existing virtual machines (VMs and their configurations, AIM provides detailed cost analyses and right-sizing recommendations, enabling organizations to make informed decisions about transitioning to cloud platforms. The tool supports comparisons across major cloud providers, including AWS, Azure, Googl

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Macgence is a leading AI training data company at the forefront of providing exceptional human-in-the-loop solutions to make AI better. We specialize in offering fully managed AI/ML data solutions, catering to the evolving needs of businesses across industries. We leverage our expertise to curate high-quality ~ 95%+ accuracy datasets. These datasets fuel innovation and deliver tangible results. Partnering with Macgence means gaining a trusted ally in your journey towards leveraging the power of

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AI Jewelry Model helps jewelry brands and ecommerce teams turn product photos into polished on-model images without a traditional photoshoot. It supports rings, necklaces, earrings, and bracelets for product pages, ads, and social content.

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Accurate large strain Finite Element simulations of geological evolution.

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ADWARY is the click fraud solution that provides advertisers with complete visibility and protection. The specially developed methodology reliably identifies fraudulent clicks on the basis of a large number of indicators, consistently prevents fraud attempts and provides clear evidence.

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Supersimple is a business intelligence platform for B2B SaaS companies that lets anyone answer complex data questions in minutes. The real value in data doesn't come from static dashboards – it comes from answering specific, often ad-hoc questions. Supersimple was designed to enable anyone on the team to answer even the most complex questions, and to deeply explore data. This is possible thanks to a powerful semantic data modeling layer. The data model can be used to centralize definitions