MUHAI project
The outcome of MUHAI is twofold.
MUHAI is an EU-funded project (2020-2024) which aspires to introduce meaning and understanding in Artificial Intelligence by developing computational models of narrative construction. MUHAI project relies on many existing techniques of AI ranging from deep learning networks to knowledge graphs, but will push their boundaries and develop new techniques all operating in the service of giving AI syst
The widespread adoption of voice user interfaces (VUIs) highlighted the growing significance of speech interaction in our everyday activities.
However, researchers, designers, and developers lack a dedicated interaction model tailored to the intricacies of communication with speech agents.
MUHAI researchers Robert Porzel and Rainer Malaka propose a novel interaction model specifically crafted for speech interaction to better align with the evolving landscape of these systems. Learn more → https://bit.ly/4fUNLjF.
In Belgium, the Rector of the University of Gent announced that from next academic year, students will be allowed to use generative AI in their thesis. This sparked a debate within the academic community, questioning the purpose and methods of university evaluation in the age of AI.
Generative AI is supposed to be able to reshape every aspect of the research cycle, but is it so? MUHAI’s researchers can help you dive a bit deeper in the matter.
[Read more → https://bit.ly/4fewXni; picture credits: Shantanu Kumar via Pexels]
One reason that understanding language is so difficult for computers and AI systems is that words often have meanings based on context and even the appearance of the letters and words.
But, at the same time, people often find it difficult to understand specialized terms used in computer science. This is why, once a month, we propose you the explanation of a word. Enjoy our 32nd !
One reason that understanding language is so difficult for computers and AI systems is that words often have meanings based on context and even the appearance of the letters and words.
But, at the same time, people often find it difficult to understand specialized terms used in computer science. This is why, once a month, we propose you the explanation of a word. Enjoy our 32nd !
[Find out the previous words → https://bit.ly/45Qi3PJ]
📨You've got mail.
If not, you never know what you are missing. The eleventh issue of MUHAI newsletter has just been delivered!
Read it (https://bit.ly/3zVE3g2) and subscribe to be updated (https://bit.ly/435tBvs)!
What do MUHAI researchers see when they look into the future of AI development? brings you tarot readings of a sort. Find out what experts look forward to, with the beautiful Mantegna illustrations.
"I look forward to overcome educational limitations as well as education access inequalities, enhancing inclusivity. But less human interactions can have a cost." AI tarot reading by Carlo Santagiustina (Venice International University).
Frank van Harmelen, Professor in Knowledge Representation & Reasoning at Vrije Universiteit Amsterdam, gives a presentation “The K in 'neuro-symbolic' stands for 'knowledge'”.
The video is the first webinar in the NAI Webinar Series moderated by Pascal Hitzler, Editor-in-Chief of the Neurosymbolic Artificial Intelligence journal.
NAI Webinar Series #1: Frank van Harmelen: “The K in 'neuro-symbolic' stands for 'knowledge'” This is the first webinar in the NAI Webinar Series moderated by Pascal Hitzler, Editor-in-Chief of the Neurosymbolic Artificial Intelligence journal. Frank ...
Artificial intelligence is one of the world’s fastest growing tech sectors. However, the percentage of women working in AI today is approximately 30% (WEF, Global Gender Gap Report 2023).
Talent availability overall has surged, increasing six times between 2016 and 2022, yet female representation in AI is progressing very slowly.
The lack of women in data science creates feedback loops that cause gender bias in AI and machine learning systems (Unesco, The effects of AI on the working lives of women 2022).
Moreover, increasing the number and rate of women in AI-related entrepreneurship and innovation will be key to making AI development inclusive and potentially driven by a multiplicity of enterprises, rather than the current landscape of a small number of dominant actors.
In MUHAI, we forerun the trends: women represent 46% of the people working on the project. These are their voices.
One reason that understanding language is so difficult for computers and AI systems is that words often have meanings based on context and even the appearance of the letters and words.
But, at the same time, people often find it difficult to understand specialized terms used in computer science. This is why, once a month, we propose you the explanation of a word. Enjoy our 31st !
[Find out the previous words → https://bit.ly/45Qi3PJ]
📯Call for papers
🗓Deadline: 1/7/24
Lise Stork (VU) will be the co-chair of the 24th International Conference on Knowledge Engineering and Knowledge Management (EKAW-24), renowned event for anyone interested in advancing knowledge engineering and knowledge management practices. MUHAI will be present with a dedicated tutorial to present specific results as part of the final events of the project.
The conference will take place in Amsterdam, 26-28 November 2024 (in-person attendance). EKAW is renowned for its high-quality research presentations, stimulating discussions, and opportunities for networking.
[Learn more → https://muhai.org/what-s-new/news-events/273-nai-web-3]
Social media platforms such as Twitter allows people to voice their opinions by engaging in online discussions. The availability of such discussions has garnered interest amongst researchers in analyzing the dynamics on critical topics, such as inequality.
Most of the current strategies are, however, limited with respect to conveying the fine-grained opinions of users, focusing on tasks such as sentiment analysis or topic modeling that extract coarse categorizations. In this work, MUHAI researchers address this challenge by integrating a Twitter corpus with the output of finer-grained semantic parsing for the analysis of social media discourse.
To do so, they first introduce the OBservatory Integrated Ontology (OBIO) that integrates social media metadata with various types of linguistic knowledge and then present the Observatory Knowledge Graph (OKG), a knowledge graph in terms of the ontology, populated with tweets on inequality.
[Read more → bit.ly/3fh2xTe; picture credits: Pixabay]
What do MUHAI researchers see when they look into the future of AI development? brings you tarot readings of a sort. Find out what experts look forward to, with the beautiful Mantegna illustrations.
"I look forward to innovation in human-centric AI in expert systems: offer solutions that reflect real-world complexities." (Óscar Vilarroya, Universitat Autònoma de Barcelona)
👏
🗣 Yesterday, a work from Venice International University was presented at the 'Science Communication in the age of AI' research conference at the University of Zurich (AISCICOMM24). The paper, "Promoting quality communication of Artificial Intelligence: insights from an AI research project" was written by Alessandra Fornetti (VIU), Folco Soffietti (IUAV PhD candidate and VIU), Ilda Mannino (VIU) and was presented by Folco at AISCICOMM24.
🤖 The presentation is based on insights from MUHAI project where VIU is leading the communication and dissemination activities.
Working with AI top-level scientists allowed a reflection on their understanding of public communication of AI, their role as researchers in supporting trustworthy communication and, in turn, the role of science communicators to effectively communicate AI to the wider public.
👉 Check out our VIU news to learn more:
https://lnkd.in/exMj-V_4
Follow the conference on X hashtag
Cooking is an act that we perform in our everyday lives to produce (delicious) dishes ready to eat. Many machines exist to help humans cook: slow cookers, multi-cookers, pressure cookers…
All these machines are really helpful, but they need the direct intervention of a human. Currently, It is not possible to give a recipe to a machine, place the machine in the kitchen, and ask it to cook the dish.
The reason for this is that recipes include a lot of background and implicit knowledge that humans gradually acquire by practicing and interacting with the world and that cannot be understood from the only lecture of the recipe.
[Learn more about Alexane Jouglar's latest blog → https://muhai.org/blog/11-understanding-everyday-activities/271-can-robots-cook]
Beginning of April, the I2B event "TZI Roadshow: AI Innovation made in Bremen" took place in the TAB building of the University of Bremen, where examples of work created at TZI were presented.
The event was a complete success with around 220 interested participants from local industry and science.
It was an important moment for the MUHAI project to present key results to the public and fellow researchers. The group from University of Bremen ensured a succesful outreach in this first final event of the MUHAI project.
Final events: i2b Bremen - MUHAI Meaning and Understanding in Human-centric AI
One reason that understanding language is so difficult for computers and AI systems is that words often have meanings based on context and even the appearance of the letters and words.
But, at the same time, people often find it difficult to understand specialized terms used in computer science. This is why, once a month, we propose you the explanation of a word. Enjoy our 30th !
[Find out the previous words → https://bit.ly/45Qi3PJ]
Generative AI (instantiated by ChatGPT, Dall-E, Claude, Copilot, Soundraw, etc.) has recently taken the world by storm, creating a wave of expectations and causing generative AI to be seen as the most transformative disruptive technology of today.
Although the power and utility of the deep learning/transformer methodology underlying generative AI is undeniable, there are also several by now well known serious issues. One of the most important ones is the tendency of generative AI to come up with facts that are untrue or devoid of common sense.
On the 9th of May 2024, Luc Steels (VIU) offered a talk at Fondazione ISI (Turin, Italy), reflecting on what are the research avenues we could explore to overcome these issues.
[learn more → https://muhai.org/what-s-new/news-events/269-gpt-now; picture credits: Growtika via Unsplash]
What do MUHAI researchers see when they look into the future of AI development? brings you tarot readings of a sort. Find out what experts look forward to, with the beautiful Mantegna illustrations.
"More effort shall improve education and research in AI, the money-driven current trend can make policies ineffective. Humans must be kept in decision loops." AI tarot reading by Luc Steels (VIU).
One reason that understanding language is so difficult for computers and AI systems is that words often have meanings based on context and even the appearance of the letters and words.
But, at the same time, people often find it difficult to understand specialized terms used in computer science. This is why, once a month, we propose you the explanation of a word. Enjoy our 29th !
[Find out the previous words → https://bit.ly/45Qi3PJ]
What do MUHAI researchers see when they look into the future of AI development? brings you tarot readings of a sort. Find out what experts look forward to, with the beautiful Mantegna illustrations.
"The innovations I look forward to in human-centric AI span three areas: expert systems, education, and social robots. Firstly, I hope expert systems will evolve to emulate human decision-making in specialized fields, integrating advanced algorithms with vast databases to offer solutions that reflect real-world complexities. In education, I am eager to see how AI fosters personalized learning, tailoring content to individual needs, providing real-time feedback, and adapting curricula. Finally, in the area of social robots, I am excited to see how they become adept at understanding human emotions and social cues, offering companionship and support in healthcare, education, and personal assistance. These human-centric innovations should signify a future where technology enhances human capabilities and enriches experiences, focusing on intuitive, effective, and empathetic human-machine interactions." (Óscar Vilarroya, Universitat Autònoma de Barcelona)
Artificial intelligence is one of the world’s fastest growing tech sectors. However, the percentage of women working in AI today is approximately 30% (WEF, Global Gender Gap Report 2023).
Talent availability overall has surged, increasing six times between 2016 and 2022, yet female representation in AI is progressing very slowly.
The lack of women in data science creates feedback loops that cause gender bias in AI and machine learning systems (Unesco, The effects of AI on the working lives of women 2022).
Moreover, increasing the number and rate of women in AI-related entrepreneurship and innovation will be key to making AI development inclusive and potentially driven by a multiplicity of enterprises, rather than the current landscape of a small number of dominant actors.
In MUHAI, we forerun the trends: women represent 46% of the people working on the project. And these are their voices.
What do MUHAI researchers see when they look into the future of AI development? brings you tarot readings of a sort. Find out what experts look forward to, with the beautiful Mantegna illustrations.
"I look most forward to the use of AI in my scientific work. The speed of science is now so high that it is almost impossible to keep up with new developments. I look forward to AI systems that can read the literature, that can give me good high level summaries of the latest developments, that can answer my questions about technical details, and with whom I can maybe even brainstorm about new ideas. And I don’t think these systems will be very far away in the future." (Frank van Harmelen, VUA)
📨You've got mail.
If not, you never know what you are missing. The tenth issue of MUHAI has just been delivered!
Read it (https://bit.ly/3VCUU0a) and subscribe to be updated (https://bit.ly/435tBvs)!
In the dazzling realm where cutting-edge technology meets the world of culinary arts, precision is not just a preference – it's the secret sauce to success.
Imagine a futuristic kitchen where robotic chefs whip up gourmet delights with a mere tap on a touchscreen. Now, in this technologically driven culinary landscape, the unsung hero emerges: accurate tracking of coreference.
Like a culinary GPS, it navigates all complex recipe transformations undergone by ingredients, ensuring that every "it" and "they" (as in "put it in the fridge" or "they are ready when a fork slides in easily") points to the right flavour-packed entity.
Anna Morbiato's latest blog explores why this seemingly subtle linguistic skill is the backbone of a seamless, tech-infused gastronomic experience.
[Learn more → https://bit.ly/3vcTuPg; picture credits: Toa Heftiba via Unsplash]
One reason that understanding language is so difficult for computers and AI systems is that words often have meanings based on context and even the appearance of the letters and words.
But, at the same time, people often find it difficult to understand specialized terms used in computer science. This is why, once a month, we propose you the explanation of a word. Enjoy our 28th !
[Find out the previous words → https://bit.ly/45Qi3PJ]
One major motivation of explainable artificial intelligence (XAI) is the desire to make the predictions of black-box machine learning models more transparent. To foster a human-centered approach to XAI, individuals and their preferences should be considered by appropriate user models.
If users ask for explanations because they expected different AI behaviour, there must be some disagreement between users and AI in their respective beliefs and knowledge, which is what we call their uncommon ground.
[Learn more about Robert Porzel's latest blog → https://bit.ly/3V7z2d4]
In the 1980s and 1990s a new wind was blowing in many sciences, based on the realization that various complex phenomena in Nature can be understood by viewing them as self-organizing dynamical systems.
A new science of complex systems was born coinciding with profound mathematical developments in fractal geometry, chaos theory and the study of large-scale networks. But how to archive, register and share this revolutionary moment?
Luc Steels curated a pop up exhibition at the Royal Library (KBR) in Brussel to collect the experiences of the scientists who developed these original ideas and carried out some of the key experiments.
[Learn more → https://bit.ly/3V7aDV4]
One reason that understanding language is so difficult for computers and AI systems is that words often have meanings based on context and even the appearance of the letters and words.
But, at the same time, people often find it difficult to understand specialized terms used in computer science. This is why, once a month, we propose you the explanation of a word. Enjoy our 27th !
[Find out the previous words → https://bit.ly/45Qi3PJ]
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