28.5.2024
Did you know, in the AI world, only about 30% of researchers are women? And in higher positions, this number is even lower. This isn't just in research; less than 25% of AI specialists are women. I think it's time for a change. I'm Jeanette Hepp, CMO at Frontnow, and I see this imbalance every day. That's why I'm excited to introduce “AI-Conic Women”.
Jeanette Hepp
Chief Marketing Officer
From the start of Merantix, a venture like Merantix Momentum was always part of the hypothesis. To build up an impactful AI ecosystem, we would need to build up our expertise, learn the ins-and-outs of implementing AI solutions in a real world setting - we’d have to learn by doing and get our hands dirty. That idea really appealed to me, I like to make things happen, get things done, and create a real tangible impact.
As you said, I’m a tech optimist, so while my journey into the AI solutions space was influenced by a blend of my experiences in tech, investment, and a connection to the amazing founding team at Merantix - at the core it was driven by a deep-seated belief in the power of AI to solve complex problems. Recognizing the potential for AI to drive significant advancements across various sectors, we shaped Merantix Momentum with the mission to empower businesses and the public sector to harness this potential effectively. Our aim was to create an ecosystem where innovation is not only encouraged but meticulously developed and applied to tackle real-world challenges, ensuring that this remarkable technology is a catalyst for positive change here in Europe.
Identifying what makes a successful startup is never easy - even the best VCs are wrong on most of their bets. Developing and nurturing a successful AI startup, though, is a different story since you can continuously learn, iterate and innovate to find what fits, which is what makes Merantix’ venture building approach so engaging.
In general though, successful applied AI startups often hinge on the strong integration between deep AI expertise and industry knowledge, combined with an agile approach to learning and development and a strong support network. With AI in particular, it’s really important to try things and iterate because machine learning solutions are often really powerful in ways that don’t always line up with our initial intuitions. Keeping up in this rapidly evolving field won’t work if you rely too heavily on a shallow use case, but if your core business model is solid and you foster a learning, innovation-driven team that’s passionate about what they do, adapting to find the right fit should be a motivating challenge rather than a roadblock.
Any solution that tries to globalize is destined to fail if you take a one-size-fits-all approach, and AI is no different. Scientific advancements and the open source community can help to democratize a certain foundational layer for AI development globally, but actually applying those advancements on the ground tends to be much more local. Different markets have different industry focuses, clients, business cultures, regulatory regimes, tech stacks, and any number of other variables to adapt to. Generally speaking, the most important thing to do is pay attention; listen to and learn from the stakeholders in the market. From a startup ecosystem perspective, it helps to collaborate with local partners, businesses, talent, and academia to foster an environment that encourages innovation while addressing localized needs.
In our case it goes even beyond adaptation to a given market, we adapt our solutions to the individual needs of each client to ensure a tailored and bespoke fit for their case - so once again, it’s vital to prioritize agility and a culture of constantly seeking to learn, develop, and connect the dots. By leveraging global networks and insights, we aim to bridge the gap between international AI advancements and local applicability, ensuring that the solutions we develop are both cutting-edge and contextually relevant, no cookie cutters here.
The thing with such a fast-moving topic as AI is that you can’t afford to pick and choose a few topics to focus on - if you want to get in the game and play to win you have to embed curiosity about the field into your DNA. Our team is fascinated by the world of AI, so every day we share new use cases, models, news stories, research papers, and more. I don’t want to not answer your question, but in all honesty I wouldn’t say there are a select few trends we could really highlight and say that is our core focus. It’s part of our job to be up to date on all of the advancements in the space and serve as a guide to help our clients understand and navigate the landscape.
Zooming out, it’s important to consider trends affecting the economy, geopolitics, social perceptions, and many other factors in addition to the technological and scientific side of things. In that respect, our core mission is to help empower European businesses and society to be champions in the AI era, so we are laser focused on challenges and solutions relevant to ensuring Europe is not only able to compete, but also lead and set a positive example globally. One specific challenge we’re focused on is how to effectively pair regulatory efforts with efforts to invest in and support innovative businesses. It will be very interesting to see how the EU AI act is codified in various countries, and how we come together to collaboratively build a dynamic and impactful ecosystem.
The purpose of the Data Institute is to increase the value creation through data sharing and data reuse across domains and stakeholders in a responsible and compliant way. Data governance and ethics form the cornerstone of responsible AI development. My involvement with the Data Institute has reinforced my belief in establishing robust frameworks that ensure transparency, accountability, and fairness in AI systems. Effective data governance is pivotal in navigating the complexities of data privacy, bias mitigation, and ensuring that AI applications serve the broader interests of society. Our commitment is to a future where AI's potential is realized in a manner that respects ethical boundaries and promotes trust and inclusivity.
Thriving ecosystems require a multifaceted approach. Key to this is ensuring not just access, but consistent exposure to and collaboration with stakeholders that can provide capital, mentorship, talent, infrastructure, and networks. Beyond that, and this is something that is often overlooked, we need to ensure that clients for those startups - be they large corporates, government agencies, or otherwise - are behaving as good partners. When we subject startups to massive amounts of red-tape and paperwork, requiring them to jump through a thousand hoops just to qualify to potentially maybe be able to do business with us, we’re suffocating their ability to innovate. Fostering collaboration between startups, corporates, the public sector and academia can spur innovation and provide startups with the resources and expertise needed to scale.
When it comes to inclusion, this isn’t something with an easy fix. We need to actively work towards eliminating biases in funding and providing platforms that elevate diverse voices in tech. But that’s only one part of the issue - a vital part of a flourishing startup ecosystem is diverse talent and when we aren’t doing ourselves any favors when we complicate immigration or promote xenophobic ideologies and policies. An inclusive ecosystem is one where diverse perspectives are not only welcomed but recognized as a critical component of innovation and success. By supporting diversity and inclusion, we strengthen the ecosystem's capacity for creativity and resilience.
As an economist by training, I've always approached challenges with an eye on the broader impact, ensuring we don't lose sight of the forest for the trees. In both roles you mentioned I had the opportunity to work alongside very bright people who were pioneers in their fields. These experiences, especially during the economic turbulence triggered by Lehman Brothers' bankruptcy, were invaluable. They taught me how talented people drive innovation even in difficult times, and how to navigate through and beyond extreme economic cycles to appreciate the wider context.
All of my roles have had a strong focus on building bridges between technical and business stakeholders, which is a central throughline I’ve carried with me throughout my career leading to Merantix Momentum. We translate technical excellence into real-world business impact, helping stakeholders on all sides of that equation to collaborate towards a shared vision. Calling back to the economist in me, that shared vision can’t just be about achieving immediate results; it’s about crafting scalable solutions that pave the way for sustained economic growth and prosperity.
Looking ahead, I am particularly excited about AI's potential in all kinds of sectors from healthcare, to education, sustainable energy, intelligent manufacturing and more. However, when determining what can make a successful venture on the market we have to assess a lot of factors that might have less to do with what is possible for AI to accomplish, and more to do with how to build a sustainable business model around those capabilities.
In terms of what’s possible in different industries the sky is really the limit. In healthcare, AI can revolutionize personalized medicine, diagnostics, and patient care, making healthcare more accessible and effective. For energy, AI can optimize production and consumption, while intelligent manufacturing can enhance efficiency, reduce waste, and revolutionize supply chains - both of which could significantly benefit sustainability efforts. And those are just a few of the potential cases that we could see in the near to mid-term future. Long term? As I said, I’m optimistic. I don’t think anyone can accurately predict how things will transform, but the potential for positive impact is there and I’m excited our team is playing a part in shaping that future.
Nicole Büttner is fundamentally a tech optimist and operates as an entrepreneur, investor, and board member. She is the founder of the AI solutions company Merantix Momentum and a board member of Merantix, an AI venture studio based in Berlin. Nicole is a Digital Leader at the World Economic Forum and has been nominated as a Young Leader by the Aspen Institute. She has been selected twice as one of the "40 under 40" by Capital Magazine. Nicole serves on the supervisory board of Quinfos, a Dumont company, the Bauer Group, and Howspace. She was part of the founding commission of the Data Institute and is a member of the advisory board of the German Data Competence Toolbox. She is a member of the alumni board of the University of St. Gallen and the board of the German Startup Association. Previously, she worked as a hedge fund portfolio manager at OFI AM in Paris and led the global business development of Auctionomics, the auction design and technology company of Nobel laureate Paul Milgrom. She regularly lectures at the University of St. Gallen and other academic institutions. Nicole has trained as an economist and econometrician at the University of St. Gallen, the Stockholm School of Economics, and Stanford University, and holds an MA in Quantitative Economics and Finance.
From the start of Merantix, a venture like Merantix Momentum was always part of the hypothesis. To build up an impactful AI ecosystem, we would need to build up our expertise, learn the ins-and-outs of implementing AI solutions in a real world setting - we’d have to learn by doing and get our hands dirty. That idea really appealed to me, I like to make things happen, get things done, and create a real tangible impact.
As you said, I’m a tech optimist, so while my journey into the AI solutions space was influenced by a blend of my experiences in tech, investment, and a connection to the amazing founding team at Merantix - at the core it was driven by a deep-seated belief in the power of AI to solve complex problems. Recognizing the potential for AI to drive significant advancements across various sectors, we shaped Merantix Momentum with the mission to empower businesses and the public sector to harness this potential effectively. Our aim was to create an ecosystem where innovation is not only encouraged but meticulously developed and applied to tackle real-world challenges, ensuring that this remarkable technology is a catalyst for positive change here in Europe.
Identifying what makes a successful startup is never easy - even the best VCs are wrong on most of their bets. Developing and nurturing a successful AI startup, though, is a different story since you can continuously learn, iterate and innovate to find what fits, which is what makes Merantix’ venture building approach so engaging.
In general though, successful applied AI startups often hinge on the strong integration between deep AI expertise and industry knowledge, combined with an agile approach to learning and development and a strong support network. With AI in particular, it’s really important to try things and iterate because machine learning solutions are often really powerful in ways that don’t always line up with our initial intuitions. Keeping up in this rapidly evolving field won’t work if you rely too heavily on a shallow use case, but if your core business model is solid and you foster a learning, innovation-driven team that’s passionate about what they do, adapting to find the right fit should be a motivating challenge rather than a roadblock.
Any solution that tries to globalize is destined to fail if you take a one-size-fits-all approach, and AI is no different. Scientific advancements and the open source community can help to democratize a certain foundational layer for AI development globally, but actually applying those advancements on the ground tends to be much more local. Different markets have different industry focuses, clients, business cultures, regulatory regimes, tech stacks, and any number of other variables to adapt to. Generally speaking, the most important thing to do is pay attention; listen to and learn from the stakeholders in the market. From a startup ecosystem perspective, it helps to collaborate with local partners, businesses, talent, and academia to foster an environment that encourages innovation while addressing localized needs.
In our case it goes even beyond adaptation to a given market, we adapt our solutions to the individual needs of each client to ensure a tailored and bespoke fit for their case - so once again, it’s vital to prioritize agility and a culture of constantly seeking to learn, develop, and connect the dots. By leveraging global networks and insights, we aim to bridge the gap between international AI advancements and local applicability, ensuring that the solutions we develop are both cutting-edge and contextually relevant, no cookie cutters here.
The thing with such a fast-moving topic as AI is that you can’t afford to pick and choose a few topics to focus on - if you want to get in the game and play to win you have to embed curiosity about the field into your DNA. Our team is fascinated by the world of AI, so every day we share new use cases, models, news stories, research papers, and more. I don’t want to not answer your question, but in all honesty I wouldn’t say there are a select few trends we could really highlight and say that is our core focus. It’s part of our job to be up to date on all of the advancements in the space and serve as a guide to help our clients understand and navigate the landscape.
Zooming out, it’s important to consider trends affecting the economy, geopolitics, social perceptions, and many other factors in addition to the technological and scientific side of things. In that respect, our core mission is to help empower European businesses and society to be champions in the AI era, so we are laser focused on challenges and solutions relevant to ensuring Europe is not only able to compete, but also lead and set a positive example globally. One specific challenge we’re focused on is how to effectively pair regulatory efforts with efforts to invest in and support innovative businesses. It will be very interesting to see how the EU AI act is codified in various countries, and how we come together to collaboratively build a dynamic and impactful ecosystem.
The purpose of the Data Institute is to increase the value creation through data sharing and data reuse across domains and stakeholders in a responsible and compliant way. Data governance and ethics form the cornerstone of responsible AI development. My involvement with the Data Institute has reinforced my belief in establishing robust frameworks that ensure transparency, accountability, and fairness in AI systems. Effective data governance is pivotal in navigating the complexities of data privacy, bias mitigation, and ensuring that AI applications serve the broader interests of society. Our commitment is to a future where AI's potential is realized in a manner that respects ethical boundaries and promotes trust and inclusivity.
Thriving ecosystems require a multifaceted approach. Key to this is ensuring not just access, but consistent exposure to and collaboration with stakeholders that can provide capital, mentorship, talent, infrastructure, and networks. Beyond that, and this is something that is often overlooked, we need to ensure that clients for those startups - be they large corporates, government agencies, or otherwise - are behaving as good partners. When we subject startups to massive amounts of red-tape and paperwork, requiring them to jump through a thousand hoops just to qualify to potentially maybe be able to do business with us, we’re suffocating their ability to innovate. Fostering collaboration between startups, corporates, the public sector and academia can spur innovation and provide startups with the resources and expertise needed to scale.
When it comes to inclusion, this isn’t something with an easy fix. We need to actively work towards eliminating biases in funding and providing platforms that elevate diverse voices in tech. But that’s only one part of the issue - a vital part of a flourishing startup ecosystem is diverse talent and when we aren’t doing ourselves any favors when we complicate immigration or promote xenophobic ideologies and policies. An inclusive ecosystem is one where diverse perspectives are not only welcomed but recognized as a critical component of innovation and success. By supporting diversity and inclusion, we strengthen the ecosystem's capacity for creativity and resilience.
As an economist by training, I've always approached challenges with an eye on the broader impact, ensuring we don't lose sight of the forest for the trees. In both roles you mentioned I had the opportunity to work alongside very bright people who were pioneers in their fields. These experiences, especially during the economic turbulence triggered by Lehman Brothers' bankruptcy, were invaluable. They taught me how talented people drive innovation even in difficult times, and how to navigate through and beyond extreme economic cycles to appreciate the wider context.
All of my roles have had a strong focus on building bridges between technical and business stakeholders, which is a central throughline I’ve carried with me throughout my career leading to Merantix Momentum. We translate technical excellence into real-world business impact, helping stakeholders on all sides of that equation to collaborate towards a shared vision. Calling back to the economist in me, that shared vision can’t just be about achieving immediate results; it’s about crafting scalable solutions that pave the way for sustained economic growth and prosperity.
Looking ahead, I am particularly excited about AI's potential in all kinds of sectors from healthcare, to education, sustainable energy, intelligent manufacturing and more. However, when determining what can make a successful venture on the market we have to assess a lot of factors that might have less to do with what is possible for AI to accomplish, and more to do with how to build a sustainable business model around those capabilities.
In terms of what’s possible in different industries the sky is really the limit. In healthcare, AI can revolutionize personalized medicine, diagnostics, and patient care, making healthcare more accessible and effective. For energy, AI can optimize production and consumption, while intelligent manufacturing can enhance efficiency, reduce waste, and revolutionize supply chains - both of which could significantly benefit sustainability efforts. And those are just a few of the potential cases that we could see in the near to mid-term future. Long term? As I said, I’m optimistic. I don’t think anyone can accurately predict how things will transform, but the potential for positive impact is there and I’m excited our team is playing a part in shaping that future.
Nicole Büttner is fundamentally a tech optimist and operates as an entrepreneur, investor, and board member. She is the founder of the AI solutions company Merantix Momentum and a board member of Merantix, an AI venture studio based in Berlin. Nicole is a Digital Leader at the World Economic Forum and has been nominated as a Young Leader by the Aspen Institute. She has been selected twice as one of the "40 under 40" by Capital Magazine. Nicole serves on the supervisory board of Quinfos, a Dumont company, the Bauer Group, and Howspace. She was part of the founding commission of the Data Institute and is a member of the advisory board of the German Data Competence Toolbox. She is a member of the alumni board of the University of St. Gallen and the board of the German Startup Association. Previously, she worked as a hedge fund portfolio manager at OFI AM in Paris and led the global business development of Auctionomics, the auction design and technology company of Nobel laureate Paul Milgrom. She regularly lectures at the University of St. Gallen and other academic institutions. Nicole has trained as an economist and econometrician at the University of St. Gallen, the Stockholm School of Economics, and Stanford University, and holds an MA in Quantitative Economics and Finance.
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