Part of the answer lies in including users early on in the innovation process, striving for more agility, making innovation everyone’s job and, not least, creating technologies that inspire!
A fortnight ago I spent a day at the “4th Innovation and Technology Marketing Meeting”, co-organised by the French Commission for Alternative Energies and Atomic Energy (CEA), a big national player in research, development and innovation and the Grenoble Ecole de Management (GEM), a well ranked French business school with a focus on technology and innovation management. The conference was hosted at MINATEC, an innovation campus home to thousands of researchers and students but also to 600 business and technology transfer experts and next to the GIANT campus (Grenoble Innovation for Advanced New Technologies) – 250 hectares of fundamental research and technology, higher education and industry that foster technology breakthroughs.
The event was opened by Corinne Hueber Saintot, head of “valorization” at the CEA and Sylvie BLANCO head of innovation at GEM. Two women to welcome a rather masculine audience of 200 directors of SMEs and start-ups, innovation managers and marketing professionals.
Marc Giget, President of the European Institute for Creative Strategies & Innovation and member of the French Academy of Technologies kicked off the day. He spoke about: “How to optimise the relation between society and innovation?”
Although the content wasn’t new his talk was highly inspirational and engaging, packed with information, quotes and thought-provoking stories like the one where, well before the recent data breach crisis, Chamath Palihapitiya, former Facebook VP of user growth, had vehemently criticized his work on new tools and technology that were successfully in market, but which were ripping apart society: “The short-term, dopamine-driven feedback loops that we have created are destroying how society works. No civil discourse, no cooperation, misinformation, mistruth.” I think we all agree that the overall aim should be to market socially desirable technology, to make “our world a better place”. But it’s not that easy, great innovations are changed in applications… think of the enormous opportunities and responsibilities in areas like genetic engineering or the profound transformational impact AI may have on defence and security.
Marketing disruptive, agile, adaptable, economically beneficial technology needs to be above all consistent with our values, moral responsibilities and our integrity.
Marc Giget discussed the breath-taking progress in technology, science and knowledge and pointed out that, with more than a million new researchers and engineers in R&D worldwide every year, there would be 20 million by 2020 – that’s in just two years’ time. The resulting increasing in publications and patents, continuous higher education and expertise of these scientists means there will be new, innovative, efficient, intelligent and whatever you can think of technologies in the years to come.
So what?
According to Giget, society is increasingly unsatisfied with existing technologies because they need to be more user-centric. In our interconnected world, users want to actively collaborate with companies in product and process innovation and, if we want to be successful in the marketing of innovation we need to consider how to involve our customers.
At the end of his talk I was wondering why he insisted on keeping technology on one side and humans and ethics on the other with no link to a future with services combined with intelligent human machine interaction?
With no time for questions the second keynote speaker, Xavier Comtesse from the University of Geneva, came on stage. He’s head of the Geneva Office of Avenir Suisse, the leading Swiss Think Tank in charge of the development of economic and social issues. His talk was entitled “Why is storytelling as important as the product?” His address was appropriately absent of any slides whilst he shared the brand stories of Nespresso then of Zurich in becoming one of the most innovative and inspiring cities in the world. He concluded by captivating his local audience with the premise that Grenoble, with all its universities, innovative industry and start-ups could become a leading world tech hub – if only they could tell the right story.
Brand stories are extremely powerful but I was left with a doubt of whether storytelling is really the future of marketing and, in particular, marketing innovation. I was also curious to know of the choices to be made in the mix of content and channels in storytelling when investing in video, images, social media, print and influencers.
After the coffee break it was industry testimonial time with “Innovation marketing applied to projects”:
Jocelyne WASSELIN, director of the energy startup Enerbee claimed all good things come in threes and all within a short period to time: outstanding technology, ‘profound’ market validation and product development and deployment. Better get your head down then!
Julien VILLALONGUE head of operations & foresight at ‘Leonard Vinci’ (yes, that’s really its name) was up next. Leonard is actually part of VINCI, a multinational in construction (183,000 people in 100 countries). Leonard Vinci is what they call their ‘open laboratory’ for the future of cities and infrastructures because, as Villalongue put it, “We don’t know what will happen in the future but we need to be prepared”. The relation to innovation marketing was not strong apart from the conviction that you need to let your people explore and tell everyone you’re letting them do so.
Patrick Mazeau from our very own NAVER LABS Europe was the last speaker in this session. He spoke about the need for speed and agility as witnessed by the trials, success and failures of NAVER. “In a world where an app like TBH moves from 0 to millions of users in just a month and gets acquired by Facebook after 10 weeks of operation for $100 million … you have to behave differently – shoot and aim – as our leader often says.”
As the speed of change is so fast, benchmarks become blurred because there’s no time for test marketing and deep analysis and the stakes are even higher. That’s why companies, universities and society need to work together. The afternoon discussion on the importance of an active innovation ecosystem is beyond the scope of this blog but suffice to say that there was general agreement that innovation with peers and engaging more employees in the innovation process help make it faster.
Overall an interesting event with the takeaway that speed is the essence in marketing innovations and that innovations must be user centric, ideally should serve an ethically moral purpose and should not be either detrimental to our lives or unnecessarily clutter them up. Plus, Grenoble is a hotbed of innovation with a great ecosystem.
On that note I cannot but end with our LABS Europe vision which I think you’ll find reflects at least some of the takeaway:
… a world of Ambient Intelligence where people intuitively interact with ubiquitous, helpful, personalized services they trust.
Time to keep working at making that vision reality.
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NAVER LABS Europe 6-8 chemin de Maupertuis 38240 Meylan France Contact
To make robots autonomous in real-world everyday spaces, they should be able to learn from their interactions within these spaces, how to best execute tasks specified by non-expert users in a safe and reliable way. To do so requires sequential decision-making skills that combine machine learning, adaptive planning and control in uncertain environments as well as solving hard combinatorial optimization problems. Our research combines expertise in reinforcement learning, computer vision, robotic control, sim2real transfer, large multimodal foundation models and neural combinatorial optimization to build AI-based architectures and algorithms to improve robot autonomy and robustness when completing everyday complex tasks in constantly changing environments. More details on our research can be found in the Explore section below.
For a robot to be useful it must be able to represent its knowledge of the world, share what it learns and interact with other agents, in particular humans. Our research combines expertise in human-robot interaction, natural language processing, speech, information retrieval, data management and low code/no code programming to build AI components that will help next-generation robots perform complex real-world tasks. These components will help robots interact safely with humans and their physical environment, other robots and systems, represent and update their world knowledge and share it with the rest of the fleet. More details on our research can be found in the Explore section below.
Visual perception is a necessary part of any intelligent system that is meant to interact with the world. Robots need to perceive the structure, the objects, and people in their environment to better understand the world and perform the tasks they are assigned. Our research combines expertise in visual representation learning, self-supervised learning and human behaviour understanding to build AI components that help robots understand and navigate in their 3D environment, detect and interact with surrounding objects and people and continuously adapt themselves when deployed in new environments. More details on our research can be found in the Explore section below.
Details on the gender equality index score 2024 (related to year 2023) for NAVER France of 87/100.
The NAVER France targets set in 2022 (Indicator n°1: +2 points in 2024 and Indicator n°4: +5 points in 2025) have been achieved.
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Index NAVER France de l’égalité professionnelle entre les femmes et les hommes pour l’année 2024 au titre des données 2023 : 87/100
Détail des indicateurs :
Les objectifs de progression de l’Index définis en 2022 (Indicateur n°1 : +2 points en 2024 et Indicateur n°4 : +5 points en 2025) ont été atteints.
Details on the gender equality index score 2024 (related to year 2023) for NAVER France of 87/100.
1. Difference in female/male salary: 34/40 points
2. Difference in salary increases female/male: 35/35 points
3. Salary increases upon return from maternity leave: Non calculable
4. Number of employees in under-represented gender in 10 highest salaries: 5/10 points
The NAVER France targets set in 2022 (Indicator n°1: +2 points in 2024 and Indicator n°4: +5 points in 2025) have been achieved.
——————-
Index NAVER France de l’égalité professionnelle entre les femmes et les hommes pour l’année 2024 au titre des données 2023 : 87/100
Détail des indicateurs :
1. Les écarts de salaire entre les femmes et les hommes: 34 sur 40 points
2. Les écarts des augmentations individuelles entre les femmes et les hommes : 35 sur 35 points
3. Toutes les salariées augmentées revenant de congé maternité : Incalculable
4. Le nombre de salarié du sexe sous-représenté parmi les 10 plus hautes rémunérations : 5 sur 10 points
Les objectifs de progression de l’Index définis en 2022 (Indicateur n°1 : +2 points en 2024 et Indicateur n°4 : +5 points en 2025) ont été atteints.
To make robots autonomous in real-world everyday spaces, they should be able to learn from their interactions within these spaces, how to best execute tasks specified by non-expert users in a safe and reliable way. To do so requires sequential decision-making skills that combine machine learning, adaptive planning and control in uncertain environments as well as solving hard combinatorial optimisation problems. Our research combines expertise in reinforcement learning, computer vision, robotic control, sim2real transfer, large multimodal foundation models and neural combinatorial optimisation to build AI-based architectures and algorithms to improve robot autonomy and robustness when completing everyday complex tasks in constantly changing environments.
The research we conduct on expressive visual representations is applicable to visual search, object detection, image classification and the automatic extraction of 3D human poses and shapes that can be used for human behavior understanding and prediction, human-robot interaction or even avatar animation. We also extract 3D information from images that can be used for intelligent robot navigation, augmented reality and the 3D reconstruction of objects, buildings or even entire cities.
Our work covers the spectrum from unsupervised to supervised approaches, and from very deep architectures to very compact ones. We’re excited about the promise of big data to bring big performance gains to our algorithms but also passionate about the challenge of working in data-scarce and low-power scenarios.
Furthermore, we believe that a modern computer vision system needs to be able to continuously adapt itself to its environment and to improve itself via lifelong learning. Our driving goal is to use our research to deliver embodied intelligence to our users in robotics, autonomous driving, via phone cameras and any other visual means to reach people wherever they may be.
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