Zachary Bratun-Glennon’s Post

I am thrilled to share that ELSA has been named a World Economic Forum Technology Pioneer 2024! This recognition highlights our dedication to utilizing AI to revolutionize lives and organizations through effective spoken English. Additionally, I am honored to be speaking at two WEF panels on Wednesday during the WEF Annual Meeting of the New Champions in Dalian, China, from June 25-27, 2024: - Unlocking ASEAN's Digital Prosperity | 08:30–09:30 CST (GMT+8) - AI Breaking New Ground: What's Next for Industry? | 13:00–14:00 CST (GMT+8) https://lnkd.in/gY4p-FyV Excited to exchange ideas and contribute to shaping the future of AI and digital growth in the region. #WorldEconomicForum #TechPioneer #ELSA #AI #DigitalEconomy #Innovation #ASEAN #ProudELSAN

Last week we hosted hundreds of founders, investors, and friends at the Gradient Ventures Founder Summit in NYC! I want to thank our speakers, team, and community for all the engagement and support. In addition, it was fascinating to hear from a number of incredible founders including: - Ivan Zhao, Founder of Notion, who painted an incredible vision for the future of work with AI - Cristóbal Valenzuela, Founder of Runway, who shared how his team operates with a "just figure it out" mentality - Stephen Balaban, Founder of Lambda, who explained how every round he has ever raised yielded only one term sheet and how difficult it is to raise money regardless of how well your company is performing What a day and looking forward to doing our best to raise the bar next year! 🚀 Zachary Bratun-Glennon Eylul Kayin Andrew Brackin Denise T. Siri Srinivas Vig Sachidananda, PhD Clayton Petty Jackie Eicholz Kyle Duffy Carmella Vong Alessandra Cigna

Excited to announce Gradient Ventures's investment in Bernardo Aceituno and Antoni Rosinol, building StackAI. They've already helped 40,000 users bring AI into their workplace to automate email summarization & drafting, build search engines on unstructured data, and automate so much more. CC: Zachary Bratun-Glennon, Jackie Eicholz https://lnkd.in/g9Df_7qg

What are the emerging use cases for responsible AI (RAI)? 🤔 Making AI responsible has been an ongoing topic for a while, but I had some confusion when I first heard about it - how to define responsible AI? Is it only referring to safety? and what use cases in the AI stack that actually makes AI more responsible? After looking into hundreds of solutions in the market, here are some takeaways: 1️⃣ RAI use cases across the AI stack can be divided into two dimensions: AI engineering workflow and the “value” of responsible AI.  AI engineering workflow includes 4 stages, apply to both traditional MLOps and GenAI Ops:  - Data preprocessing - Model adaptation - Serving - Inference RAI value includes 5 categories: - Explainability - Bias & Fairness - System Robustness - Privacy & Protection - System Security 2️⃣ Many existing solutions focus on model explainability, performance eval/monitoring, output verification, and red-teaming to address the non-deterministic nature of GenAI, and issues of bias, hallucination. More and more solutions center around security and privacy, including prompt protection, PII protection, and decentralized training. ⭐3️⃣ Lastly, there are 9 emerging RAI use cases that we’re excited about: - Constitutional AI - Feature Interpretability - Optimization With User Feedback - Data Accreditation - Tiered Agent Permissioning - RAG Security - AI Compliance Explainability and Reporting - Visual Data Understanding - Proprietary Data Pruning Check out the full piece here for details on the use cases we're seeing in Responsible AI: https://lnkd.in/gcbGDUPr And If you're working on solutions in this space, feel free to reach out to our team at Gradient Ventures!