By Melissa Anchisi and Florian Meyer
In July, EPFL, ETH Zurich, and the Swiss National Supercomputing Centre (CSCS) announced their joint initiative to build a large language model (LLM). Now, this model is available and serves as a building block for developers and organisations for future applications such as chatbots, translation systems, or educational tools.
The model is named Apertus – Latin for “open” – highlighting its distinctive feature: the entire development process, including its architecture, model weights, and training data and recipes, is openly accessible and fully documented.
AI researchers, professionals, and experienced enthusiasts can either access the model through the strategic partner Swisscom or download it from Hugging Face – a platform for AI models and applications – and deploy it for their own projects. Apertus is freely available in two sizes – featuring 8 billion and 70 billion parameters, the smaller model being more appropriate for individual usage. Both models are released under a permissive open-source license, allowing use in education and research as well as broad societal and commercial applications.
As a fully open language model, Apertus allows researchers, professionals and enthusiasts to build upon the model and adapt it to their specific needs, as well as to inspect any part of the training process. This distinguishes Apertus from models that make only selected components accessible.
“With this release, we aim to provide a blueprint for how a trustworthy, sovereign, and inclusive AI model can be developed,” says Martin Jaggi, Professor of Machine Learning at EPFL and member of the Steering Committee of the Swiss AI Initiative. The model will be regularly updated by the development team which includes specialized engineers and a large number of researchers from CSCS, ETH Zurich and EPFL.
With its open approach, EPFL, ETH Zurich and CSCS are venturing into new territory. “Apertus is not a conventional case of technology transfer from research to product. Instead, we see it as a driver of innovation and a means of strengthening AI expertise across research, society and industry,” says Thomas Schulthess, Director of CSCS and Professor at ETH Zurich. In line with their tradition, EPFL, ETH Zurich and CSCS are providing both foundational technology and infrastructure to foster innovation across the economy.
Trained on 15 trillion tokens across more than 1,000 languages – 40% of the data is non-English – Apertus includes many languages that have so far been underrepresented in LLMs, such as Swiss German, Romansh, and many others.
“Apertus is built for the public good. It stands among the few fully open LLMs at this scale and is the first of its kind to embody multilingualism, transparency, and compliance as foundational design principles”, says Imanol Schlag, technical lead of the LLM project and Research Scientist at ETH Zurich.
“Swisscom is proud to be among the first to deploy this pioneering large language model on our sovereign Swiss AI Platform. As a strategic partner of the Swiss AI Initiative, we are supporting the access of Apertus during the Swiss {ai} Weeks. This underscores our commitment to shaping a secure and responsible AI ecosystem that serves the public interest and strengthens Switzerland’s digital sovereignty”, commented Daniel Dobos, Research Director at Swisscom.
While setting up Apertus is straightforward for professionals and proficient users, additional components such as servers, cloud infrastructure or specific user interfaces are required for practical use. The upcoming Swiss {ai} Weeks hackathons will be the first opportunity for developers to experiment hands-on with Apertus, test its capabilities, and provide feedback for improvements to future versions.
Swisscom will provide a dedicated interface to hackathon participants, making it easier to interact with the model. As of today, Swisscom business customers will be able to access the Apertus model via Swisscom’s sovereign Swiss AI platform.
Furthermore, for people outside of Switzerland, the Public AI Inference Utility will make Apertus accessible as part of a global movement for public AI. “Currently, Apertus is the leading public AI model: a model built by public institutions, for the public interest. It is our best proof yet that AI can be a form of public infrastructure like highways, water, or electricity,” says Joshua Tan, Lead Maintainer of the Public AI Inference Utility.
Apertus is designed with transparency at its core, thereby ensuring full reproducibility of the training process. Alongside the models, the research team has published a range of resources: comprehensive documentation and source code of the training process and datasets used, model weights including intermediate checkpoints – all released under the permissive open-source license, which also allows for commercial use. The terms and conditions are available via Hugging Face.
Apertus was developed with due consideration to Swiss data protection laws, Swiss copyright laws, and the transparency obligations under the EU AI Act. Particular attention has been paid to data integrity and ethical standards: the training corpus builds only on data which is publicly available. It is filtered to respect machine-readable opt-out requests from websites, even retroactively, and to remove personal data, and other undesired content before training begins.
“Apertus demonstrates that generative AI can be both powerful and open,” says Antoine Bosselut, Professor and Head of the Natural Language Processing Laboratory at EPFL and Co-Lead of the Swiss AI Initiative. “The release of Apertus is not a final step, rather it’s the beginning of a journey, a long-term commitment to open, trustworthy, and sovereign AI foundations, for the public good worldwide. We are excited to see developers engage with the model at the Swiss {ai} Weeks hackathons. Their creativity and feedback will help us to improve future generations of the model.”
Future versions aim to expand the model family, improve efficiency, and explore domain-specific adaptations in fields like law, climate, health and education. They are also expected to integrate additional capabilities, while maintaining strong standards for transparency.
Small two-wheeled robots, equipped with high-tech sensors, will help to find survivors faster in the aftermath of disasters. © Tohoku University, 2023.
By Michael Allen
In the critical 72 hours after an earthquake or explosion, a race against the clock begins to find survivors. After that window, the chances of survival drop sharply.
When a powerful earthquake hit central Italy on 24 August 2016, killing 299 people, over 5 000 emergency workers were mobilised in search and rescue efforts that saved dozens from the rubble in the immediate aftermath.
The pressure to move fast can create risks for first responders, who often face unstable environments with little information about the dangers ahead. But this type of rescue work could soon become safer and more efficient thanks to a joint effort by EU and Japanese researchers.
Rescue organisations, research institutes and companies from both Europe and Japan worked together from 2019 to 2023 to develop a new generation of tools blending robotics, drone technology and chemical sensing to transform how emergency teams operate in disaster zones.
It is a prototype technology that did not exist before.
– Tiina Ristmäe, CURSOR
Their work was part of a four-year EU-funded international research initiative called CURSOR, which included partners from six EU countries, Norway and the UK. It also included Tohoku University, whose involvement was funded by the Japan Science and Technology Agency.
The researchers hope that the sophisticated rescue kit they have developed will help rescue workers locate trapped survivors faster, while also improving their own safety.
“In the field of search and rescue, we don’t have many technologies that support first responders, and the technologies that we do have, have a lot of limitations,” said Tiina Ristmäe, a research coordinator at the German Federal Agency for Technical Relief and vice president of the International Forum to Advance First Responder Innovation.
At the heart of the researcher’s work is a small robot called Soft Miniaturised Underground Robotic Finder (SMURF). The robot is designed to navigate through collapsed buildings and rubble piles to locate people who may be trapped underneath.
The idea is to allow rescue teams to do more of their work remotely, localising and finding humans from the most hazardous areas in the early stages of a rescue operation. The SMURF can be remotely controlled by operators who stay at a safe distance from the rubble.
“It is a prototype technology that did not exist before,” said Ristmäe. “We don’t send people, we send machines – robots – to do the often very dangerous job.”
The SMURF is compact and lightweight, with a two-wheel design that allows it to manoeuvre over debris and climb small obstacles.
“It moves and drops deep into the debris to find victims, with multiple robots covering the whole rubble pile,” said Professor Satoshi Tadokoro, a robotics expert at Tohoku University and one of the project’s lead scientists.
The development team tested many designs before settling on the final SMURF prototype.
“We investigated multiple options – multiple wheels or tracks, flying robots, jumping robots – but we concluded that this two-wheeled design is the most effective,” said Tadokoro.
The SMURF’s small “head” is packed with technology: video and thermal cameras, microphones and speakers for two-way communication, and a powerful chemical sensor known as the SNIFFER.
This sensor is capable of detecting substances that humans naturally emit, such as C02 and ammonia, and can even distinguish between living and deceased individuals.
Put to the test in real-world conditions, the SNIFFER has proved able to provide reliable information even when surrounded by competing stimuli, like smoke or rain.
According to the first responders who worked with the researchers, the information provided by the SNIFFER is highly valuable: it helps them to prioritise getting help to those who are still alive, said Ristmäe.
To further improve the reach of the SMURF, the researchers also integrated drone support into the system. Customised drones are used to deliver the robots directly to the areas where they’re needed most – places that may be hard or dangerous to access on foot.
Ιt moves and drops deep into the debris to find victims, with multiple robots covering the whole rubble pile.
– Professor Satoshi Tadokoro, Tohoku University
“You can transport several robots at the same time and drop them in different locations,” said Ristmäe.
Alongside these delivery drones, the CURSOR team developed a fleet of aerial tools designed to survey and assess disaster zones. One of the drones, dubbed the “mothership,” acts as a flying communications hub, linking all the devices on the ground with the rescue team’s command centre.
Other drones carry ground-penetrating radar to detect victims buried beneath debris. Additional drones capture overlapping high-definition footage that can be stitched together into detailed 3D maps of the affected area, helping teams to visualise the layout and plan their operations more strategically.
Along with speeding up search operations, these steps should slash the time emergency workers spend in dangerous locations like collapsed buildings.
The combined system has already undergone real-world testing, including large-scale field trials in Japan and across Europe.
One of the most comprehensive tests took place in November 2022 in Afidnes, Greece, where the full range of CURSOR technologies was used in a simulated disaster scenario.
Though not yet commercially available, the prototype rescue kit has sparked global interest.
“We’ve received hundreds of requests from people wanting to buy it,” said Ristmäe. “We have to explain it’s not deployable yet, but the demand is there.”
The CURSOR team hopes to secure more funding to further enhance the technology and eventually bring it to market, potentially transforming the future of disaster response.
Research in this article was funded by the EU’s Horizon Programme. The views of the interviewees don’t necessarily reflect those of the European Commission. If you liked this article, please consider sharing it on social media.
This article was originally published in Horizon, the EU Research and Innovation magazine.
AI startup Fable Studio is out with a new tool — dubbed ‘Showrunner,’ that long-term, promises to forge entire TV episodes and movies in minutes.
Simply enter a text prompt describing what you want, click enter, and in about 22 minutes, you’ll have your 22-minute TV episode.
Even better: You can use the tool to drop yourself into the action as a character.
Currently demoing with short clips in cartoon form, Fable Studio is promising film-like TV shows and movies in about two years, according to CEO Edward Saatchi.
In other news and analysis on AI:
*ChatGPT Rated Number One Consumer App: Venture capital firm Andreessen Horowitz has released its latest analysis of the AI market, pegging ChatGPT as the top AI app, based on unique monthly visits.
On its heels is Google’s Gemini chatbot, followed by DeepSeek – a chatbot made in China.
Also high-up on the list:
–Grok
–Character.ai
–Perplexity
–Claude
*Google’s Text-to-Talking-Heads Podcast Tool Gets an Upgrade: NotebookLM, a research and production tool that has wowed users by being able to transform an article or other text into an audio podcast featuring two people discussing the substance of that text has a new spring in its step.
Now, you can tweak the tool so that your text-to-podcast emerges in any of four formats:
–Brief, which offers-up a two-minute summary of the text
–Deep Dive, which offers an in-depth discussion of your
material
–Critique, which features talking heads critically discussing
your text
–Debate, which creates two hosts who take different points-
of-view on your article or similar
*Google’s New ‘Nano Banana’ Image Editor: Cool Use Cases: The fervor over Google’s new image editor continues to rage across the Web, as increasingly numbers of users are entranced by its power and surgical precision.
One of the new tool’s most impressive features: The ability to stay true to the identity of a human face – no matter how many times it remakes that image.
For a quick study, check-out these videos on YouTube, that show you scores of ways to use the new editor – officially known as Gemini 2.5 Flash Image:
–Google Gemini 2.5 Flash Image (Nano Banana) – 20 Creative Use Cases
–15 New Use Cases with Nano Banana
–The Ultimate Guide to Gemini 2.5- Flash (Nano Banana)
–New Gemini 2.5 Flash Image is Insane & Free
–Nano Banana Just Crushed Image Editing
*One Educator’s Take: Human-Generated Writing Still Essential in the Age of AI: College writing teacher Liz Stillwaggon Swan insists that without formal writing instruction, college students will be unleashed on the world sans the ability to think clearly and deeply.
Observes Swan: “I explain to my students that writing is a process of making the subconscious conscious—of bringing hazy, half-baked assumptions, biases, intuitions, ideas, anxieties, and hopes to the surface.
”Often, we don’t know what we believe until we start writing. We put our feelings and experiences into words and stories, even arguments, and through that arduous process, we begin to feel utterly human.”
*Another Educator’s Take: AI Has Rendered Traditional Writing Instruction Obsolete: It’s time to trash the teaching of writing at the college level as we know it, according to John Villasenor, a writing instructor at University of California Los Angeles.
Instead, today’s college students – who already know that AI will be handling most of the writing needed in years to come – should be taught how to get the most from AI when using it for writing.
Observes Villasenor: “It means helping students become proficient at using AI as a force multiplier to improve the depth, versatility, and speed of their writing.
“Today’s young people know that when it comes to writing, the technology landscape has undergone a tectonic shift, and they have already found their new footing. Those of us involved in teaching them need to do the same.”
*AI Agents and Marketing: A Primer: AI startup Smartcat.ai is offering a free eBook detailing how marketers can use multiple agents to automate much of their work.
Observes Nicole Di Nicola, VP of marketing, Smartcat.ai: “It’s like every marketer can now become a content creator. A product marketer can take a messaging doc and have AI turn it into a campaign plan with emails and sequences—fewer handoffs, less lag, more ownership. ”
One caveat: Given that AI agents are brand new technology that sometimes gets ahead of its skis, ‘pilot trial’ is the operative phrase here.
*Anthropic to Cough-Up $1.5 Billion to Book Authors: AI startup Anthropic – maker of the popular Claude chatbot – has agreed to pay $1.5 billion to authors and publishers as compensation for using their intellectual property to train its AI.
Observes writer Cade Metz: “The settlement is the largest payout in the history of U.S. copyright cases.
”Anthropic will pay $3,000 per work to 500,000 authors.”
*Google Promising AI Writing for More Android Phones: Google’s Gboard’s AI Writing Tools will be rolled-out to more phones in coming weeks, according to the tech goliath.
The tool enables users to proofread and rephrase text on their Android smartphones – without being forced to go to the cloud.
But so far, only devices featuring Gemini Nano v2 or higher are being promised the tools.
*AI BIG PICTURE: AI’s Next Killer App: Emotional Manipulation?: Geoffrey Hinton, the Godfather of AI, warns that the tech will soon be better at manipulating people than the most accomplished con man.
Observes writer Eric Hal Schwartz: Hinton “believes AI will be smarter than humans in ways that let them push our buttons, make us feel things, change our behavior, and do it better than even the most persuasive human being.
“The nightmare is an AI that understands us so well that it can change us, not by force, but by suggestion and influence.”
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–Joe Dysart is editor of RobotWritersAI.com and a tech journalist with 20+ years experience. His work has appeared in 150+ publications, including The New York Times and the Financial Times of London.
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