University Research Collaboration

𝗔𝟮𝗔 (𝗔𝗴𝗲𝗻𝘁-𝘁𝗼-𝗔𝗴𝗲𝗻𝘁) 𝗮𝗻𝗱 𝗠𝗖𝗣 (𝗠𝗼𝗱𝗲𝗹 𝗖𝗼𝗻𝘁𝗲𝘅𝘁 𝗣𝗿𝗼𝘁𝗼𝗰𝗼𝗹) are two emerging protocols designed to facilitate advanced AI agent systems, but they serve distinct roles and are often used together in modern agentic architectures. 𝗛𝗼𝘄 𝗧𝗵𝗲𝘆 𝗪𝗼𝗿𝗸 𝗧𝗼𝗴𝗲𝘁𝗵𝗲𝗿 Rather than being competitors, 𝗔𝟮𝗔 𝗮𝗻𝗱 𝗠𝗖𝗣 𝗮𝗿𝗲 𝗰𝗼𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁𝗮𝗿𝘆 𝗽𝗿𝗼𝘁𝗼𝗰𝗼𝗹𝘀 that address different layers of the agent ecosystem: • 𝗔𝟮𝗔 is about agents collaborating, delegating tasks, and sharing results across a distributed network. For example, an orchestrating agent might delegate subtasks to specialized agents (analytics, HR, finance) via A2A25. • 𝗠𝗖𝗣 is about giving an agent (often an LLM) structured access to external tools and data. Within an agent, MCP is used to invoke functions, fetch documents, or perform computations as needed.    𝗧𝘆𝗽𝗶𝗰𝗮𝗹 𝗪𝗼𝗿𝗸𝗳𝗹𝗼𝘄 𝗘𝘅𝗮𝗺𝗽𝗹𝗲: • A user submits a complex request. • The orchestrating agent uses 𝗔𝟮𝗔 to delegate subtasks to other agents. • One of those agents uses 𝗠𝗖𝗣 internally to access tools or data. • Results are returned via A2A, enabling end-to-end collaboration25.    𝗗𝗶𝘀𝘁𝗶𝗻𝗰𝘁 𝗦𝘁𝗿𝗲𝗻𝗴𝘁𝗵𝘀 • 𝗔𝟮𝗔 𝗲𝘅𝗰𝗲𝗹𝘀 𝗮𝘁:   Multi-agent collaboration and orchestration   Handling complex, multi-domain workflows   Allowing independent scaling and updating of agents   Supporting long-running, asynchronous tasks54 • 𝗠𝗖𝗣 𝗲𝘅𝗰𝗲𝗹𝘀 𝗮𝘁:   Structured tool and data integration for LLMs   Standardizing access to diverse resources   Transparent, auditable execution steps   Single-agent scenarios needing a precise tool    𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗮𝗹 𝗔𝗻𝗮𝗹𝗼𝗴𝘆 • 𝗠𝗖𝗣 is like a 𝘶𝘯𝘪𝘷𝘦𝘳𝘴𝘢𝘭 𝘤𝘰𝘯𝘯𝘦𝘤𝘵𝘰𝘳 (USB-C port) between an agent and its tools/data. • 𝗔𝟮𝗔 is like a 𝘯𝘦𝘵𝘸𝘰𝘳𝘬 𝘤𝘢𝘣𝘭𝘦 connecting multiple agents, enabling them to form a collaborative team.    𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗮𝗻𝗱 𝗖𝗼𝗺𝗽𝗹𝗲𝘅𝗶𝘁𝘆 𝗖𝗼𝗻𝘀𝗶𝗱𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀 • 𝗔𝟮𝗔 introduces many endpoints and requires robust authentication and authorization (OAuth2.0, API keys). • 𝗠𝗖𝗣 needs careful sandboxing of tool calls to prevent prompt injection or tool poisoning. Both are built with enterprise security in mind.    𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝘆 𝗔𝗱𝗼𝗽𝘁𝗶𝗼𝗻 • 𝗔𝟮𝗔: Google, Salesforce, SAP, LangChain, Atlassian, Cohere, and others are building A2A-enabled agents. • 𝗠𝗖𝗣: Anthropic (Claude Desktop), Zed, Cursor AI, and tool-based LLM UIs.   Modern agentic systems often combine both: 𝗔𝟮𝗔 𝗳𝗼𝗿 𝗶𝗻𝘁𝗲𝗿-𝗮𝗴𝗲𝗻𝘁 𝗼𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻, 𝗠𝗖𝗣 𝗳𝗼𝗿 𝗶𝗻𝘁𝗿𝗮-𝗮𝗴𝗲𝗻𝘁 𝘁𝗼𝗼𝗹 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻. This layered approach supports scalable, composable, and secure AI applications.

Universities spends $108 billion on research. But only 25-40% ever reaches the market. Universities are sitting on massive untapped potential. While traditional tech transfer has built critical infrastructure, there's a fundamental gap between laboratory proof-of-concept and market-ready applications. The emerging solution? University-attached venture studios. These systematic company creation platforms are demonstrating average net IRRs of 60% compared to 33% for top-quartile traditional VC. But the real value goes beyond returns. MIT Proto Ventures shows how this works: "We need a new, proactive model for research translation—one that breaks down silos and bridges deep technical talent with validated market needs." The results speak for themselves: Enhanced research impact through real-world application Universities build sustainable innovation infrastructure Students gain hands-on entrepreneurial experience Faculty research becomes more industry-relevant Early implementations at UNC's Eshelman Innovation, John Carroll's Blue Streak Ventures, and Arizona State's partnership with Idealab prove the model works across different institutional contexts. For university leadership, technology transfer professionals, and institutional investors: the question isn't whether venture studios represent superior research commercialization, but how quickly you can capture this opportunity. The institutions that act decisively will establish sustainable advantages that benefit their communities for generations. What's your university doing to bridge the innovation gap?

As Harvard faces deep research funding cuts, a private equity firm has stepped in with a $39M commitment to support a Harvard research lab. Could this signal a new future for how academic science is funded? The investment comes from Turkish firm İş Private Equity, which typically backs high-growth small and medium-sized enterprises (SMEs). The funding recipient is the lab of Professor Gökhan Hotamışlıgil at the Harvard T.H. Chan School of Public Health, whose research aims to develop therapies for obesity and other metabolic diseases. Broader context Private equity (PE) rarely funds basic university research directly, as it doesn’t align with traditional return-focused models. But that’s changing. New structures are emerging where PE capital supports translational or applied academic science: ▫️ New startup - İş Private Equity launched Enlila, a new biotech company created to fund Hotamışlıgil’s lab over the next 10 years. Enlila will also invest in translating the lab’s discoveries into therapeutic products. ▫️ Joint ventures - Since 2017, Deerfield Management has created university partnerships to advance early-stage therapeutics, providing capital and helping universities evaluate projects toward Investigational New Drug (IND) readiness. Recent examples include: - Hyde Park Discovery with University of Chicago ($130M, 2025) - VeritaScience with Washington University in St. Louis ($130M, 2024) ▫️ Royalty monetization - In 2023, Purdue Research Foundation received over $100M from Blue Owl Capital by selling a portion of its royalty interest in Pluvicto, a prostate cancer therapy. Yale University executed a similar deal for the drug Yervoy, turning future royalties into immediate research capital. Takeaway As the research funding landscape evolves, the capital stack for science is becoming increasingly complex. I think we’ll likely see more private equity, venture capital, and philanthropy stepping in to support bold, high-risk science in new and unexpected ways. Curious to hear your thoughts: Should private equity be stepping into early-stage science? Which research areas could benefit most from this approach?

When #Technology Meets #Humanity: Research Making a Global Impact Imagine moving a robotic arm with nothing but your mind. It sounds like science fiction, but thanks to groundbreaking research—enabled by years of collaboration and dedication across institutions—it’s now a reality. At Chalmers University of Technology, we are proud to be at the forefront of this innovation in brain-computer interface (#BCI) technology. This research is not just restoring movement for individuals with paralysis—it’s restoring independence, dignity, and hope. This incredible achievement, featured in The Times and Le Monde, would not have been possible without the global research community’s collective efforts. It’s a testament to the power of science and collaboration to push boundaries and redefine what’s possible. We are also proud to announce that this work has been published in Science Magazine, marking a significant milestone in addressing some of humanity’s most pressing challenges. A heartfelt thanks to the dedicated researchers behind this breakthrough, including Dr. Giacomo Valle at Chalmers, and our incredible collaborators: University of Chicago: Ali H. Alamri, John E. Downey, Patrick M. Jordan, Anton R. Sobinov, Linnea J. Endsley, Dillan Prasad, Peter C. Warnke, Nicholas G. Hatsopoulos, Charles M. Greenspon, Sliman J. Bensmaia University of Pittsburgh: Robin Lienkämper, Michael L. Boninger, Jennifer L. Collinger, Robert A. Gaunt Northwestern University: Lee E. Miller This work exemplifies what we mean by "technology for a better world"—not innovation for its own sake, but innovation that transforms lives. Curious to learn more? Read the full article in The Times: https://lnkd.in/dFVvbg2M This is what science can achieve when curiosity and collaboration meet. What other areas of innovation do you believe will transform lives in the near future?

What if today’s students didn’t just know how to use AI, but were AI-fluent, building with it, shaping it, and bringing those skills into the workforce? What if some of the world’s oldest and most extensive archival libraries were open to anyone, anywhere, in any language — whether they read the text or needed to hear it spoken? What if we started to think about how AI could unlock the freedom to learn and the freedom to access knowledge in new ways? These possibilities, including the freedom of knowledge and the freedom to learn, are being pursued by NextGenAI — a first-of-its-kind research consortium OpenAI launched today with 15 leading universities and research institutions across the US and abroad. The goal? Use AI to put tools in the hands of researchers to accelerate breakthroughs in science, medicine, and education that will help everyone As Dr. Benjamin Talton, Director of the Moorland-Spingarn Research Center of Howard University, one of the NextGenAI partners, put it: “The business of universities is planning for the future… You can’t plan unless you know the tools you’ll have at your disposal” That’s why as part of NextGenAI, OpenAI is committing $50 million in research grants, compute funding, and API access to support students, educators, and researchers as they push the frontiers of knowledge NextGenAI’s founding members—who reflect an incredible mosaic—include: Caltech, the California State University system, Duke University, the The University of Georgia, Harvard University, Howard University, Massachusetts Institute of Technology, University of Michigan, University of Mississippi, The The Ohio State University, University of Oxford, Sciences Po, Texas A&M University, as well as Boston Children's Hospital, the Boston Public Library, and OpenAI  NextGenAI will drive impact in three key areas:  1) Accelerate frontier research breakthroughs 2) Prepare the next generation of students and learners to be AI-literate 3) Empower universities and libraries with AI to enhance operations and learning possibilities As our CEO Sam Altman has written in his Three Observations, AI could be the next transistor — a breakthrough that scales across every sector of the economy, seeping into every corner of our lives. As we enter The Intelligence Age, I am excited to see how our NextGenAI partners use AI to make breakthroughs that will help improve the lives of all of us A huge thank you to NextGenAI founding partners, and my colleagues who made this possible — they are forces of nature and together a force multiplier when it comes to delivering on OpenAI’s purpose to build AI that serves everybody: Jasmyn Samaroo, Michelle (Bailhe) Fradin, James Donovan, Chris Orsinger, Brianna Bower, adam koppel, Elizabeth Wilner, Amy Custalow Wendling, Dani Westbrook, Andy Brown, Austin Bates, Leah Belsky, and Brad Lightcap https://lnkd.in/eng7ikVU

Synthetic text extrusion machines such as ChatGPT are only a threat to adversarial pedagogies. It is hence surprising that we have not paid more attention to pedagogies that are instead based on forms of mutualism and consensus. Ones that would be less brittle in plagiarism hysterias. The Ungrading movement would be a good example or Students as Partners. In the introduction to their very useful new #openaccess book on co-design in higher education editors Mohammad Golam Jamil, Catherine O'Connor and Fiona Shelton give a great conceptual overview of different ways in which the staff student boundary are reimagined: “1. Students as Partners (SaP) is largely aligned to radical social justice roots (Cook-Sather, 2022; de Bie et al., 2021). On the contrary, the focus of co-creation is broader which is often co-creating value, in any form or volume, among the stakeholders. Therefore, while all SaP may be perceived as co-creation, not all co-creation is SaP. 2. Co-design mainly refers to the design phase of a product or process. The focus is on inventions through incorporating stakeholder’ views and actions (Vargas et al., 2022). Co-creation is broader than this as it can be a pre- or post- design stage, for example, any activities for identifying the need for a product, and contextualising its perceived outcomes. Therefore, similar to Students as Partners, all co-design is likely co-creation, but not all co-creation is co-design. 3. Co-production is very similar to the concept of co-design, and it is mainly oriented towards the building or construction of a product or process. The dominant part of the literature on co-production defines it as the collective construction of knowledge which is often generated at the end of the value chain or lifecycle of a product or process (Vargas et al., 2022). On the other hand, co-creation engages stakeholders at all phases of the process including initiation, design, implementation, and evaluation (Ansell & Torfing, 2021; Voorberg et al., 2015). 4. In Students as Change Agents, students are the key stakeholders and take the roles of leaders and decision makers in the change process (Kay et al., 2010). Compared to SaP, co-design, and co-creation; in SCA students enjoy more power and autonomy for intervening and making any targeted changes. However, this may place an unfair burden on them because of the passive or dependent role of other stakeholders including staff members. Co-creation is more inclusive in this aspect as it places responsibilities on all stakeholders, although staff members may drive student agency to enact any changes.” https://lnkd.in/eXw9Pgcj

The current lull in news about the financial position of universities does not mean that the UK’s higher education sector is not under immense pressure. Rising costs, frozen tuition fees, the decline in international students, political demands for “value for money,” and shifting workforce needs driven by AI and sustainability are all colliding to create a system that is no longer sustainable in its current form. “Radical collaboration”, a new report from KPMG and Mills & Reeve, offers a clear message: universities can’t simply do more with less. They must rethink how they work together, moving beyond institutional pride and financial firefighting to embrace bold, long-term collaboration. This isn’t about bailing out failing institutions but about reshaping the sector to deliver research excellence, broader access, stronger regional impact, and long-term resilience and the report outlines key recommendations for the future: ➡️ Recognise the current HE model is no longer sustainable ➡️ Focus collaboration on outcomes, not just cost-cutting ➡️ Define clear purpose and objectives for any partnership ➡️ Prioritise long-term strategic leadership over institutional pride ➡️ Consider a range of models from alliances to full mergers ➡️ Create the right conditions: strong leadership, aligned values, clear communication ➡️ Address cultural and regulatory barriers early ➡️ Ensure government provides enabling support (legal, financial, regulatory) ➡️ Treat radical collaboration as a proactive strategy for sector sustainability The question now is whether the sector has the leadership, political will, and strategic clarity to act or whether it will continue to delay the inevitable. #HigherEducation #UniversityStrategy #Leadership #Collaboration #Policy #HEReform #RadicalCollaboration #FutureOfHE #Universities #PublicValue

What if we stopped treating university-SME collaboration as a “nice to have” and started treating it as economic infrastructure? A new report from CSIRO and the University of Queensland reveals what actually happens when small and medium enterprises (SMEs) work with universities and research institutions (URIs). The results are compelling. Collaborations between SMEs and URIs are widely acknowledged as drivers of innovation. But this report digs deeper, asking: what’s the real commercial payoff for the firms involved? Based on a survey of 201 Australian businesses across diverse sectors and regions, Commercial Outcomes of SME–Research Collaboration analyses three types of engagement: 🔹 Facilitated dollar-matched programmes 🔹Competitive grants 🔹Student placement programmes The findings? 🔹66% of SMEs reported new or improved products—clear evidence that collaboration brings ideas to market. 🔹Prototypes, independent validation, and derisked R&D were common outcomes, especially for early-stage firms. 🔹Facilitated, entry-level collaborations delivered outcomes nearly on par with large, competitive grants—but with smaller budgets and greater accessibility. 🔹Regional SMEs outperformed their metro counterparts across nearly all dimensions, from innovation to credibility to market expansion. Sectoral insights are equally striking: 🔹Medtech and biotech firms focused on R&D derisking; 🔹Manufacturing and digital tech SMEs reported strong product development outcomes; 🔹Energy businesses used partnerships to validate solutions for market credibility. In New Zealand, we often underinvest in the connective tissue that makes innovation happen. This report shows that well-designed, fit-for-purpose collaboration programmes can unlock capability, especially for regional and smaller firms. The message is clear: industry-university collaboration is a catalyst. And in an economy where resilience and diversification are more important than ever, we can’t afford to overlook it. https://lnkd.in/gTHhRiBQ

Two years ago, I moved to Austria with curiosity in my heart and a question in my mind: What if Austrian and Indian universities could do more together? This week, that “what if” felt more real than ever. TU Austria (a network of TU Wien, TU Graz, and Montanuniversität Leoben) this week has launched a powerful initiative with India, supported by €5 million in funding from the Austrian Federal Ministry of Science, Research and Economy. This isn't just another exchange program. It’s a strategic bridge — rooted in academic diplomacy, built on trust and excellence, and aimed at addressing the global challenges of our time: 📌 Circular economy 📌 Climate-neutral technologies 📌 Sustainable infrastructure 📌 AI and digitalization As someone who has worked for a decade at the intersection of academia, innovation, and international collaboration — from Indian universities to top US institutions, and now actively engaging with Austrian universities — I see this as a defining moment. A moment to: 🎯 Co-create joint research labs 🎯 Launch PhD exchange programs with dual supervision 🎯 Design transdisciplinary academic-industry clusters between Austria and India 🎯 Develop curriculum and mobility models for the future of STEM education This is where I’d love to contribute — as a consultant and bridge-builder for universities in both countries. Helping map opportunities, facilitate strategic dialogues, and enable world-class programs that serve both nations — and the planet. 📢 To university leaders, deans, researchers, and innovation offices — let’s talk. Because when two strong academic cultures come together, we don’t just exchange students. We exchange futures. Read more about the initiative: https://lnkd.in/dfvprh4U (English summary also available via TU Austria) #AustriaIndia #AcademicDiplomacy #JointResearch #HigherEducation #CircularEconomy #GlobalCollaboration #TUAustria #InnovationBridges

💥 Everyone is talking about MCP (Model Context Protocol)… but almost no one is asking the bigger question: what comes after MCP? Because the truth is: MCP only solves model ↔ tool integration. The next protocols will solve the agent to agent collaboration problem. That’s where the next generation of protocols comes in: 🔹 A2A (Agent-to-Agent Protocol) – enables peer-to-peer task delegation, lifecycle management, and artifact exchange. 🔹 ACP (Agent Communication Protocol) – focuses on REST-native, async-first messaging between agents. 🔹 ANP (Agent Network Protocol) – a more ambitious layer, introducing decentralized identity and open agent discovery. Why this matters in life sciences: 1️⃣ Clinical trial start-up → sponsor and CRO agents coordinating tasks with full audit trails. 2️⃣ Pharmacovigilance → intake agents handing cases to follow-up agents seamlessly. 3️⃣ RWE & evidence generation → multiple agents sharing cohorts, analysis plans, and results across systems. MCP is foundational, but the real transformation comes when we move into inter-agent standards. That’s how we get from isolated AI assistants to collaborative AI ecosystems that actually fit regulated pharma workflows. #AIinHealthcare #LifeSciencesAI #ModelContextProtocol #AgenticAI #PharmaInnovation #AIProtocols #HealthcareTechnology #DrugDevelopment #AIInteroperability #FutureOfAI