Über uns
Startup Grind is the largest independent startup community, actively educating, inspiring, and connecting entrepreneurs globally.
The cornerstone of our global community are monthly events featuring successful local founders, innovators, educators and investors who share lessons learned on the road to building great companies.
Founded in Silicon Valley, Startup Grind has helped millions of entrepreneurs build their businesses, connect with strategic partners, and secure funding.
- Start a Chapter in your city! - http://www.startupgrind.com/start
- Sponsor an event! - https://www.startupgrind.com/sponsor
- Have a Startup? your startup & meet investors at a regional conference through our Startup Program - http://bit.ly/sg_meetup_startup_first
Kommende Veranstaltungen
5
The Future of AI Infrastructure
535 5th Avenue, 535 5th Ave, New York, NY 10017, USA, New York, NY, USLet’s talk about what’s coming in the world of AI infra.
🚨 FREE RSVP HERE 👈
Anthony Erondu is a Principal Consultant focused on AI infrastructure, GPU compute and Physical AI. He partners with high growth companies across the space to build product and engineering teams, placing talent from VP level leaders through senior ICs across some of the most critical areas of the AI stack.
Akaanksha Sinha is an award-winning trailblazer in AI, cybersecurity & governance architecture. Over a decade in the enterprise stack. She founded AKAVAM, a governance-through-architecture company for enterprise AI. Its platform, AEVO, combines infrastructure as code, policy as code & compliance as code into deterministic execution, turning organizational context into operating capability. Ex-IBM, Deloitte, CUNY
Srinivas Venkatanarayanan is a Senior Systems Research Engineer in Nvidia, Working in Cosmos Search. He specializes in multimodal reasoning, search and Curation for Post-training Vision Language Action Models. He works in Autonomous Vehicle and Robotics domain.
Joshua Ness is a Senior AI Advisor & Consultant based in New York City. He spent 6 years at Verizon 5G Labs where he advised on enterprise adoption of 5G and edge computing technologies for clients, including the NFL, Disney, and MasterCard. He currently advises PE-backed global technology firms on AI implemention and organizational structure, including tech infrastructure modernization and regulatory compliance. Joshua holds a Fulbright Specialist appointment through which he works with the government of the Philippines on national AI readiness programs. He holds certifications from AWS, IBM, and IEEE in applied AI and cloud infrastructure.
🚨 FREE RSVP HERE 👈
2 Teilnehmer
Tech Happy Hour by Startup Grind
Time Out Market Union Square, 124 East 14th Street, New York, NY, USThis is the monthly Startup Grind tech mixer. It's a low-key way to connect with the NYC tech and startup community to discover shared interests, explore areas for collaboration, and find your next co-founder or key hire.
Join us for a casual happy hour to build real relationships and make friends, not just contacts. No pitches. No presentations. No agenda.
This happy hour is for:
- Startup Founders & Employees
- Technologists, Developers & Tech Workers
- Product Managers & Designers
- Investors, VCs, Advisors & Mentors
- Anyone curious about the NYC tech scene
Agenda:- 5:00 PM: Happy Hour starts. Come and go as you please.
We're at the new Time Out Market at Union Square. It features a selection of the city's best food and drink together under one roof, offering a wide variety of options to choose from throughout the event.Look for Startup Grind table signs toward the back near the outdoor terrace.
30 Teilnehmer
Prototyping in Public: Where Art and Science Get Tested on the Gallery Floor
The National Arts Club, 15 Gramercy Pk S, New York, NY 10003, USA, New York, NY, USWhat if a museum ran like a lab, with the experiment still in progress?
Ann Neumann is Director of Galleries and Exhibitions at the MIT Museum. Her question for the evening: can a museum serve as infrastructure for public experimentation, a place where visitors take part in the work rather than just walk through it?
If you build products, run pilots, or spend your days deciding what's ready to put in front of real people, this is a look at how one of the best-known science museums handles prototyping in public.
In collaboration with the National Arts Club and its Art and Technology Committee, Ann will walk through the interactive projects she's shepherded at the MIT Museum. Each one works as a prototype for engaging the public with technologies like CRISPR, machine learning, and sensory neuroscience.
Reserve your spot and arrive early. Space is limited.
Founded in 1898, the National Arts Club is a 501(c)(3) nonprofit with a mission to stimulate, foster, and promote public interest in the arts and to educate the American people in the fine arts.
Annually, the Club offers more than 150 free programs—both in-person and virtually—to the public, including exhibitions, theatrical and musical performances, lectures, and readings, attracting an audience of over 30,000 in-person visitors and thousands more online.
1 Teilnehmer
The AI Briefing by Startup Grind: Who Owns the Data Layer Behind Enterprise AI
Civic Hall, 124 East 14th Street, New York, NY, US👉 CLICK HERE TO RSVP FOR FREE 👈
The AI Briefing is a recurring AI deep-dive for decision-makers.
Each month, we select one high-signal industry report, circulate it in advance, and meet to cut through the noise.📜 This month's source: The Formula for Agentic AI Value: Applied AI Index 2026 (Boston Consulting Group – Sep 2026)
Secondary sources:
- 5 Emerging Trends in Enterprise Data & AI (The Modern Data Company – Aug 2026)
- Agentic context layers (VentureBeat Intelligence – Oct 2026)
Most of the money behind enterprise AI no longer runs through IT.
BCG surveyed 1,330 CxOs and senior executives. AI spending has more than tripled, to 3.3% of revenue, and 2.8 points of it sit outside the enterprise IT budget. Business units generate about two-thirds of the value AI creates.
So who owns the data their agents run on?
BCG says the gap between leaders and everyone else has moved up the stack, to whether a company's data is current, consistently defined, trustworthy, and managed with clear ownership. It tells companies to keep their definitions, business rules and decision logic in a layer they control and could move to another vendor.
VentureBeat's August survey points the other way. 98% of companies running retrieval in production use at least one system someone else built, and 2% name building and owning their context layer as their likely direction. 64% have already caught an AI agent giving a confidently wrong answer because of their own company's data.
👉 CLICK HERE TO RSVP FOR FREE 👈
🏔️ The Mission: Deciding who owns the definitions, rules and context your AI runs on
- This series has spent the year on readiness: how fast enterprises adopted, where leadership's confidence outran results, how governance fell behind agents, and whether the workforce was ready. October's discussion turned to a question none of those sessions answered: who owns the data layer?
- We'll test BCG's advice against what data teams report from the inside. 61% call a reliable context layer critical for AI agents, and 16% engineer one on purpose.
📊 The Format:
- The numbers: BCG's spending and ownership data, and where a self-reported executive survey stops being evidence.
- Cross-pollinated debate: Who owns it in your org? IT, the data team, the business unit paying for the agent, or the model vendor whose stack holds the context.
- The semantic layer problem: In VentureBeat's survey, companies running or building a semantic layer were about twice as likely to report a confidently wrong agent answer (78% vs. 37%). We'll work through why, and what it means for anyone about to fund one.
🤝 Who Should Attend:
- Enterprise Executives: See where AI budgets and accountability sit at the 7.5% of companies BCG calls future-built (all of them have clear ownership of the AI agenda), and decide whose name goes on the data layer before a vendor's does.
- Founders & Builders: Hear what buyers mean when they ask about lock-in. 37% of VentureBeat's respondents plan to keep standalone tools alongside the model, and 22% expect to consolidate onto one model provider's stack.
- Product, Data, and Operations Leads: Compare notes on the work underneath. 46% of respondents say their teams spend more than a quarter of their time maintaining and integrating tools, and 8.4% say the data feeding their AI is trustworthy enough for production.
📬 The Prep: This is a working session, not a lecture. Read the report here. Bring one wrong answer your AI gave and where the bad data came from.
👉 CLICK HERE TO RSVP FOR FREE 👈
2 Teilnehmer
Vergangene Veranstaltungen
255
