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Large Language Models
Arcee.ai advances model merging innovations with launch of MergeKit hackathon
Arcee.ai, a leader in specialized language models for enterprise generative AI, invites developers to participate in a Model Merging Hackathon. With the opportunity to utilize MergeKit, an open-source tool for combining large language models, participants can showcase their creativity and expertise while competing for cash prizes. Read More
Holy Grail of Observability
Flip AI today announced that it has been named to the CB Insights AI 100 that showcases the 100 most promising private AI companies of 2024. The winners were chosen based on several factors, including CB Insights’ data on interviews with software buyers, deal activity and team strength: https://www.cbinsights.com/learn/ai-100-2024. Read More
Stardog Announces Voicebox General Release
Stardog, the enterprise data and AI company dedicated to providing workers with direct, easy, safe, and responsible access to critical business data, today announced the general release of Voicebox, its LLM Platform. Additionally, Stardog debuted Karaoke, a software-integrated appliance that enables highly-regulated businesses with data assets not cloud-resident to enjoy the benefits of Stardog Voicebox on-premises Read More
Quiq Selected for Enterprise Connect
Quiq, the next-generation conversational customer experience (CCX) platform, is proud to announce that we have been chosen for inclusion in this year’s Enterprise Connect’s 2024 Innovation Showcase (EC24). Each year the Innovation Showcase recognizes a handful of trailblazing companies aligned with a theme. In 2024, the theme is Customer Experience. Read More
Vero AI Emerges with Groundbreaking AI Driven.
Dedicated to empowering global enterprises in harnessing the full potential of AI technologies while minimizing risk, Vero AI announced the launch of its revolutionary AI-driven, science-based platform and scoreboard. Vero AI’s advanced analytical engine Iris and scoring framework, the VIOLET Impact Model, empower enterprises to evaluate their AI tools and optimize the value of their AI investments, while mitigating the many associated risks like bias, dehumanization, privacy invasions, and legal implications. Read More
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