Glasswing Ventures

The AI market is expected to reach $2.7 trillion by 2032 (Source: Fortune Business Insights™). With this rapid expansion comes an increased importance for both builders and buyers of AI to understand the subtle nuances of varying use cases and their associated AI platforms to accurately determine which solutions will bring the most positive impact to enterprise businesses. To aid AI pioneers in this understanding, Glasswing is excited to release its proprietary Enterprise AI Adoption Framework. This framework outlines the main criteria every AI pioneer should know when evaluating AI-native solutions. Familiarize yourself with the Framework here: https://lnkd.in/ee7Q2Zmi

We are thrilled to see Bruce Schneier join Nametag's Advisory Board! Bruce's deep industry expertise will empower the data collaboration platform to continue pushing the boundaries of what’s possible in privacy-first identity verification and online account protection. Read more about Bruce and Nametag here: https://lnkd.in/eCkGgCTF

We are thrilled to see Bruce Schneier join Nametag's Advisory Board! Bruce's deep industry expertise will empower the data collaboration platform to continue pushing the boundaries of what’s possible in privacy-first identity verification and online account protection. Read more about Bruce and Nametag here: https://lnkd.in/eCkGgCTF

Where Artificial Intelligence is the "what," its architecture is the how — how a unique combination of models, guardrails, data, and systems make AI models function. Glasswing's proprietary Enterprise AI Value Creation Framework covers the characteristics of an AI model's system, sensitivity, and performance one must be aware of to make the right AI decision for their business and use case: 𝗦𝘆𝘀𝘁𝗲𝗺 𝗗𝗲𝘀𝗶𝗴𝗻: Open-ended systems adapt and learn continuously whereas discrete systems follow strict data rules. 𝗥𝗲𝗴𝘂𝗹𝗮𝘁𝗼𝗿𝘆 𝗦𝗲𝗻𝘀𝗶𝘁𝗶𝘃𝗶𝘁𝘆: AI must comply with industry-specific regulations. Thoughtful design ensures both legal compliance and market trust. 𝗠𝗼𝗱𝗲𝗹 𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲: High-stakes environments demand near-perfect accuracy, while creative tasks function well with flexibility and adaptation. Read more about AI architecture here: https://lnkd.in/e4dCgyre

Thank you, Kristen Craft, for interviewing our Founder and Managing Partner, Rudina Seseri! In this video, Kristen and Rudina discuss why Rudina is passionate about venture capital, the number one attribute she looks for in new and repeat founders, and what she is most excited about regarding the current AI landscape. Listen below 👇

Training data is the backbone of any AI solution. Where relevant, clean data builds high-performing AI models, irrelevant, scattered data can quickly break down those same models. Our Enterprise AI Value Creation Framework covers three key data characteristics to look for when evaluating AI solutions. Learn about them here: https://lnkd.in/ee7Q2Zmi

AI agents are the hot topic of many conversations, but what are they, really? Ron Miller writes that the answer remains unclear, citing the perspective of our Founder and Managing Partner, Rudina Seseri. In these early days of AI agents, Rudina believes that there isn't a single definition of an AI agent. Rather, there is a common viewpoint that an AI agent is an intelligent software system designed to perceive its environment, reason about it, make decisions, and take actions to achieve specific objectives autonomously. Read more about AI agents here: https://lnkd.in/gz4N5gh4

Today, significant oversupply within supply chains restricts the use of effective working capital, but AI advancements and financial innovation present the opportunity for companies to break out of this norm. In his recent Forbes article, Paul J. Noble (Founder & CSO of Verusen AI) shares insights from a recent discussion with Sean Hanafin (CEO, Silver Birch Finance). The two highlight how AI technology and strategic finance initiatives can work together to liberate capital and create leaner and more resilient supply chains, especially in asset-intensive large industrial settings. Read how technology and finance innovators are redefining inventory management here: https://lnkd.in/dqKhVKfs

Our Partner, Kleida Martiro, had a great conversation with Rob Levin and Jason Snyder this morning during the Greater Boston Chamber of Commerce & McKinsey & Company State of AI event! The trio discussed the pace of AI adoption in the enterprise and how budget plays a role, the Commonwealth's support of AI innovation, and what they're most looking forward to in the next year of AI development. Watch the full recording here: https://lnkd.in/eTWyyNp5

How can enterprises accelerate AI optimization while reducing costs? Graph Metanetworks (GMNs) provide a compelling answer, offering a way to automate the analysis and optimization of AI models. This framework, developed by NVIDIA and MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), eliminates much of the manual effort involved in debugging and fine-tuning. Our Founder and Managing Partner, Rudina Seseri, explains how GMNs leverage graph-based representations to map and refine neural networks in her newest AI Atlas. Dive deeper into GMNs here: https://lnkd.in/ejr8McpP