Power electronics for next-generation electric vehicles

Standardised, highly compact, and cost-efficient power electronics to boost future electric vehicles and Europe’s e-mobility industry.

Europe’s ambitious goal to phase out new combustion-engine car sales by 2035 demands rapid innovation in electric vehicle (EV) technology. Key to this shift is improving the efficiency, reliability, and cost-effectiveness of power electronics, i.e., the systems converting electricity to drive EV motors and recharge their batteries. To strengthen Europe’s competitiveness and reduce reliance on external technology, the EU-funded SCAPE project (Switching-Cell-Array-Based Power Electronics Conversion for Future Electric Vehicles) is pioneering an innovative design approach to EV power converters. Coordinated by the Catalonia Institute for Energy Research (IREC), SCAPE (Grant No. 101056781, duration 2022–2026) introduces a standardised, modular, and scalable solution, directly addressing Europe’s electrification and industry leadership goals.

SCAPE targets groundbreaking key performance indicators: over 97.5% power conversion efficiency, a doubling of power density, and halving the cost per kilowatt compared to current standards. These advancements promise extended driving ranges, affordable EVs, and a strengthened European industry.
Modular and scalable power converters



SCAPE introduces a novel design approach with modular & scalable power converters based on multilevel neutral-point-clamped topologies. Its cornerstone is the switching cell, a standardised and compact basic building block, incorporating advanced power semiconductor technology and ancillary circuitry. Multiple switching cells interconnect to form ‘converter legs’, which then combine into complete power converters (Fig. 1). This modular approach enables flexible scaling, allowing the conception of power converters for small urban vehicles up to heavy-duty electric trucks from a single switching cell design, following standardised powertrain design rules, and leveraging on scale economies and low engineering effort for a potential manufacturing cost reduction.

The standardised design significantly reduces engineering complexity and cost. EV OEMs can now build customised converters efficiently, employing standardised modules produced at scale for a broad vehicle diversity.

SCAPE also proposes the integration of a traction inverter and an on-board charger into a single unit, leveraging a multiphase electric machine. This simplifies the vehicle design and manufacturing and greatly increases the powertrain capacity, reduces its cost, and increases its reliability through fault tolerance.
Chip-embedding integration technology

At the core of SCAPE’s innovation is the chip-embedding technology, placing power semiconductor chips directly inside the printed circuit board (PCB). Traditional power converters rely on separate, surface-mounted components, resulting in increased size, reduced switching speed, greater losses, and thermal limitations. SCAPE’s embedded approach substantially reduces stray inductance and enhances thermal management, boosting efficiency and power density. SCAPE has developed a first batch of chip-embedded switching cells (Fig. 2). Experimental validations confirm successful operation at demanding conditions and demonstrate a 45% reduction of junction-to-heatsink thermal resistance and an 85% reduction of the power-loop stray inductance, compared to a conventional implementation with discrete power devices in TO-247 packaging. Thus, chip-embedding not only shrinks the converter’s size but also enhances electrical and thermal performance and reliability, allowing for greater switching frequencies that further reduce the size of the converter capacitors and magnetic components, as well as the electromagnetic emissions.
Intelligent controls and predictive maintenance

SCAPE’s innovations extend to advanced controls and predictive health management (PHM) strategies. A powertrain digital twin – an exact virtual replica of the physical system – runs in parallel with the powertrain operation, processing data from an online monitoring system (OMS) to continuously assess the system state-of-health (SoH). PHM actions encompass predictive maintenance warnings and load redistribution among the switching cells, converter leg, and battery modules to maintain operation until servicing. Worth mentioning is the capability of the OMS to perform online measurements of the battery module’s internal impedance, a parameter directly linked to the battery’s SoH. The PHM proactive approach dramatically improves reliability, reduces downtime, and enhances user confidence in electric vehicles.
Expected impact

SCAPE aligns closely with European Commission objectives, contributing significantly to transportation decarbonisation and industrial resilience. By increasing powertrain efficiency, the project helps extend EV driving range, reduce battery size, and lower vehicle costs. Cost-effective power electronics directly translate into more affordable EVs, accelerating consumer adoption.

Moreover, SCAPE fosters European technological sovereignty. By standardising the switching-cell technology, the project supports the development of a robust, EU-based supply chain, minimising dependence on imported components and expertise. The innovative modular design enables rapid adaptation across vehicle classes, creating economies of scale within the European market.

The project’s predictive maintenance capabilities further enhance lifecycle sustainability, reducing electronic waste and improving environmental performance. SCAPE’s holistic approach thus ensures that Europe’s EV transition is technologically advanced, economically viable, and environmentally responsible.

Through strategic innovation and European collaboration led by IREC, SCAPE demonstrates how targeted research can yield practical solutions for a greener, more competitive automotive future.

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How AI Is Helping Companies Translate Data Into Stories

 

Company data tells all kinds of stories but they are often difficult for employees to read. Natural Language Generation (NLG), a form of artificial intelligence, is helping change that by extracting insights from complex data sources and communicating that information in natural language as if it were written or spoken by a human.

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How To Get Better Data Insights And Compete With Google

 

Johnson & Johnson, AstraZeneca and GlaxoSmithKline are among 10 pharmaceutical companies that are jointly leveraging data insights to accelerate drug discovery, development and go-to-market times while reducing costs. It is just one example of how companies are starting to use federated learning, a machine learning framework that allows artificial intelligence algorithms to learn from data distributed across multiple locations and owners, without the need to share sensitive data directly.

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Manufacturing Shifts For The Great Reset

The World Economic Forum this week announced the addition of 10 new factories to its Global Lighthouse Network, a community of companies deemed to have succeeded in the adaptation of the Fourth Industrial Revolution at scale. Despite the disruptions caused by the COVID-19 pandemic, the Forum says these manufacturers have found ways to improve sustainability, competitiveness and customer satisfaction. Among the factories added to the network are plants in Asia run by Alibaba and Unilever, plants in Europe run by Groupe Renault and Novo Nordisk and a plant in the U.S. run by Schneider Electric. The network and its 54 factories are a platform to develop, replicate and scale up innovations, creating opportunities for cross-company learning and collaboration and for setting new benchmarks for the global manufacturing community. A new Forum report, Global Lighthouse Network: Four Durable Shifts For A Great Reset In Manufacturing, details how factories in the network have adapted.

The lighthouses showcase significant, measurable improvements across several key performance indicators (KPIs), including productivity, sustainability and eco-efficiency, agility, speed-to-market and customization, says the Forum report, which was prepared with McKinsey. Productivity improvements include increases of factory outputs and overall equipment effectiveness , along with reduction in product cost, operating cost and quality cost. Sustainability gains come from reducing waste along with water consumption while increasing energy efficiency. More agility has led to reductions in inventory, lead-times and changeovers. Speed-to-market reduction reflects shorter design iteration time, and customization has yielded lot size reduction and improved configuration accuracy.

“Recent world events have led to unprecedented disruptions, affecting nearly every aspect of global industry. Lighthouses demonstrate how Fourth Industrial Revolution technologies can drive efficiency in operations, enhance supply chain resilience and improve customer experience, while augmenting the workforce and enabling more sustainable production systems,” Francisco Betti, Head of Shaping the Advanced Manufacturing and Production, World Economic Forum, said in a statement. “They have the opportunity and responsibility to become the engine of the Great Reset.”


The new lighthouses include:

Asia

Alibaba (Hangzhou): Combining powerful digital technologies with consumer insights, Alibaba’s pilot Xunxi factory brings a fully digitized new manufacturing model to life. It empowers end-to-end, on-demand production based on consumer needs, and enables small businesses to be competitive in the fast-paced fashion and apparel market by shortening delivery time by 75%, reducing the need to hold inventory by 30% and even cutting water consumption by 50%.

Micron Technology (Taichung): To drive the next wave of productivity improvement, Micron’s high-volume advanced semiconductor memory manufacturing facility developed an integrated Internet Of Things and analytics platform, ensuring that manufacturing anomalies can be identified in real time while providing automated root-cause analysis to accelerate new product ramp-up by 20%, reduce unplanned downtime by 30% and improve labour productivity by 20%.

Midea Group (Guangzhou): Faced with intense appliance industry competition and increasing complexity and speed in e-commerce, Midea leveraged Fourth Industrial Revolution technologies to transform from an automated factory to an end-to-end connected value chain, improving labour efficiency by 28%, reducing unit cost by 14% and shortening order lead time by 56%.

Unilever (Hefei): With e-commerce booming in China, Unilever built a pull-production model by deploying Fourth Industrial Revolution solutions such as flexible automation and artificial intelligence at scale across production, warehousing and delivery, reducing order-to-delivery lead time by 50% and e-commerce consumer complaints by 30% while reducing costs by 34%.

Europe

Groupe Renault (Maubeuge): To protect the plant competitiveness (recognized as the best-performing light commercial vehicle plant in the Alliance), Groupe Renault deployed Fourth Industrial Revolution technologies at scale in its 50-year-old plant, reducing warranty incidents by 50%, increasing its flexibility to deal with the many vehicle configurations and reducing manufacturing costs by 16%.

Janssen Large Molecule (Cork): With a fast-changing and increasing demand for biological products, Janssen has digitally connected R&D, its internal and external manufacturing, and deployed advanced process control solutions to drive near real-time visibility of supply chain status, improve reliability by 50%, as well as accelerate technology transfers while reducing costs by 20%.

Novo Nordisk (Hillerød): Facing volume growth and rising complexities, Novo Nordisk has invested in digitalization, automation and advanced analytics, building a robust Industrial Internet of Things operating system to be scaled across their manufacturing footprint, increasing equipment efficiency and productivity by 30%.

Middle East

Saudi Aramco (Khurais): As part of Aramco’s dedication to increase the resiliency of its operations, the Khurais oil field was built as a fully connected and intelligent field, with over 40,000 sensors covering over 500 oil wells spread over 150km x 40km. This enabled autonomous process control, remote operation and monitoring of equipment and pipelines, resulting in maximizing the oil well production with at least 15% attributed to smart well completion technology alone.

North America

DCP Midstream (Denver): Driven by the need to combat market volatility with operational transformation and innovative efficiencies, DCP Midstream leveraged internally developed digital solutions and tech-venture partnerships to integrate the remote control of operations with its planning, logistics and commercial systems, allowing real-time optimization of margins and creating over $50 million in value.

Schneider Electric (Lexington): To maintain a business and technological edge, Schneider Electric’s more than 60-year-old facility has implemented Fourth Industrial Revolution technologies to achieve a complete end-to-end transformation of its operations from supplier to customer. This has improved customer satisfaction by 20%, demand forecast accuracy by 20%, and reduced energy costs by 26%.

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Trustworthy AI May Be In Reach

 

What do chatbots emulating the role of a rabbi or medical school professor have to do with business? A lot, it turns out. Projects involving both are testing a technology call Retrieval Augmented Generation (RAG) a technique for enhancing the accuracy and reliability of generative AI models by fetching facts from qualified sources. The approach could democratize education and, if pundits are right will also enable the dependable scaling of generative AI, helping companies reap the full business benefits.

RAG is able to digest complex queries and give models sources they can cite, like footnotes in a research paper, so users can check their legitimacy. It can also reduce the possibility a model will hallucinate.

Once companies get familiar with RAG, they can combine a variety of off-the-shelf or custom large language models (LLMs) with internal or external knowledge bases to create a wide range of assistants that help their employees and customers, says a blog posting by Nvidia, which has developed an enterprise offering that includes a sample chatbot and the elements users need to create their own applications with RAG.

“Looking forward, the future of generative AI lies in creatively chaining all sorts of LLMs and knowledge bases together to create new kinds of assistants that deliver authoritative results users can verify,” says the Nvidia blog post.

The integration of RAG technology offers significant business benefits, “particularly when coupled with existing search modules and enterprise databases,” says Bernhard Pflugfelder, head of The Innovation Lab at Germany’s appliedAI Initiative a venture involving over 50 partners from science and industry, the public sector, and selected start-ups working on the development of trustworthy AI.  “By harnessing RAG’s capabilities, businesses can empower their knowledge management processes, enabling swift and effective provision of information regarding products or processes,” he says. “This integration facilitates the generation of highly reliable answers to customer or employee inquiries, advancing organizational efficiency and customer satisfaction.”

In addition to streamlining decision-making processes, RAG promises to democratize enterprise knowledge, ensuring that valuable insights are available to all employees, says Pflugfelder. And, since RAG empowers businesses to develop more intelligent customer interfaces and services, it promises to enhance the overall user experience and foster stronger client relationships.

Will Chatbots Replace Rabbis?

In keeping with its mission to develop trustworthy and secure AI applications the appliedAI Initiative is working with partners to establish a “RAG evaluation and benchmarking framework.” As part of that work appliedAI is involved in a project called Virtual Havruta to explore any potential gaps in RAG technology. The project aims to give people all over the world the option of turning to a chatbot with questions about the Jewish faith rather than simply asking their local rabbi. Partners on the project include Sefaria, the largest provider of digitalized open-source Jewish texts and the Software and Artificial Intelligence Venture Lab at the Technical University of Munich. Virtual Havruta has the buy-in of the Reform, Conservative and Orthodox branches of Judaism. Instead of spitting out answers like a search engine, the domain-specific LLM-based RAG being tested in the project acts as a sparring partner. It outlines the thinking of each branch of Judaism and then proposes relevant links for further study, encouraging people to form their own opinions.  The Havruta project was the subject of a panel entitled “Will Chatbots Replace Rabbis?” moderated by The Innovator’s Editor-in-Chief during the DLD conference in Munich in January.

“No, chatbots will not replace rabbis,” says Antoine Leboyer, managing director of the Technical University of Munich’s Software and AI Venture Lab, who participated in the panel. “But the help and contribution of AI has unique potential to enhance and facilitate the study of Jewish texts.”

The implementation of RAG technologies developed and deployed  by the appliedAI Initiative “makes us confident that we can use such a platform in a wide group without concerns of poor links and hallucination,” says Leboyer. “This is a particularly relevant for such projects where there is not a one single specific answer for every question but a set of directions to deepen a question.”

The Havruta project is a perfect test case for RAG technology, says Paul Yu-Chun Chang, a senior AI expert at the appliedAI Initiative, who also took part in the panel. “It poses challenges, particularly given the solemn nature of the topics involved and the need to delicately distinguish different interpretative perspectives for the same reference data,” he says.

Like in business, queries about religion “demand a serious, fact-based approach for both in- and out-of-context question”, says Chang, who developed the RAG technology for the Havruta project. “Addressing sensitive and unethical topics requires meticulous filtering, with an expectation that results are delivered in an inclusive, unbiased manner. These challenges extend to existing techniques for anti-adversarial attacks and effective benchmarking and evaluation.”

Virtual Havruta “serves as a tangible testing ground in our pursuit of achieving explainable, traceable, and controllable generative AI,” says Chang. “The insights gained from this use case play a pivotal role in advancing the industry-standardized framework that we are dedicated to developing.”

Democratizing Education

Another notable new project is looking to use RAG to democratize education for women. That project involves SandboxAQ, a company spun out from Google parent Alphabet that delivers AI + quantum solutions that run on today’s classical computing platforms. It has partnered with LibreTexts and The Female Quotient to equip women with the skills required for immediate workforce entry through AI-enhanced personalized education. LibreTexts is the world’s largest centralized open education project and online platform. It was founded in 2008 at the University of California, Davis, to reduce the burdens of textbook costs to students who can’t afford them.

The idea behind the project is to upskill women and girls in different parts of the globe. In locations such as India, where there is a huge shortage of doctors and nurses, the RAG project is looking to leverage medical textbooks on LibreTexts platform and an AI-powered chatbot plus RAG. The tool can develop personalized lesson plans for, allow students to ask questions of their textbooks, quiz themselves along the way and provide clickable links to relevant materials.

Since not everyone has access to personal computers the project is considering the uses of carts that contains slots for a classroom’s worth of smart tablets. The carts both charge the tablets and enables networking to a central computer. “You don’t even need Internet access, all you need is electricity,” says Marianna Bonanome, PhD, SandboxAQ’s Head of External Education Programs. She used the carts while teaching at the City University Of New York (CUNY) because many of her students couldn’t afford computers and there were a limited number of computer classrooms available. Bonanome co-authored free textbooks for her own students, a mission that brought her into contact with the founder of LibreTexts.

When Bonanome, a trained physicist and mathematician specialized in quantum algorithms computing, was hired by SandboxAQ to launch an external education program she discovered the benefits of using RAG technology. That got her thinking about marrying open educational resources with a RAG to help both democratize and personalize education for students globally. She didn’t need to do much convincing to get LibreTexts onboard.

During a soft launch of the project during the World Economic Forum’s annual meeting in Davos, SandboxAQ CEO Jack Hidary talked about the power of RAG technology to transform education. When it comes to healthcare training, the RAG ensures that the LLM does not search the Internet but only looks at textbooks validated from the LibreTexts corpus, he says. “This will give the Best of ChatGPT and LLM’s ease of use for things like grabbing text and video but also the best of validated information,” he said. “That is the promise of personalized education, that is how we can scale it.”

Adding AI and RAG technology on top of validated digitized free textbooks “will enable us to take education to the next level,” says Bonanome. “We are still mid-development with LibreTexts, and partners The Female Quotient and Future Brilliance,” she says. “We haven’t yet pinned down our pilot schools but are exploring several locations.”

There are so many potential applications, she says. In discussing this topic with Jonas Haertle, Chief of the Office of Executive Director for UNITAR, so many use cases related to the UN were on the table. One potential use case is the training of United Nations diplomats. It is impossible for them to digest all the past and current resolutions, says Bonanome. “Applying RAG to all UN resolutions would give diplomats a tool in real time to access and digest complicated back stories and concepts.”

From RAG to Riches?

So how does RAG overcome the issues that have been holding back the use of Generative AI? The idea behind RAG is to enrich the actual prompt with the most relevant information and context. “By doing so, the LLM aggregates and summarizes but does not add additional information based on its trained weights, “ says Plugfelder. The second issue to overcome is an LLM can only reason about data it has already seen in the training process. The challenge is find a way to incorporate additional knowledge without training / fine-tuning the LLM. RAG’s technical solution is to not only include external knowledge into the prompt but also include a retrieval step to find the relevant data among relevant knowledge bases, he says.

Given RAG’s potential to reduce hallucinations and extract reliable information should companies start embracing it now? “Absolutely, says Plugfelder. There are a wealth of advantages including improved code generation, customer service, product documentation, internal knowledge retrieval and engineering support. “Compared to other generative AI technologies, businesses can leverage RAG more easily and swiftly as RAG is indeed a mitigation of one of the main limitations of current LLMs for industry applications, namely hallucination and robustness,” he says.

The appliedAI Initative’s partners are already actively advancing RAG technology in prototypes and minimal viable products, says Pflugfelder. “Waiting is not advisable for businesses; they should proactively embrace this transformative technology and learn about best practices and potential use cases in their organizations.

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Preserving Memory In The Age Of AI

The guardians of the Auschwitz Memorial understand the imperative of maintaining authenticity to immunize the Holocaust against doubt and denial. Few survivors remain eighty years after the liberation of the notorious concentration camp, where more than a million Jews met their death. And the further into the past the genocide fades, the greater the danger of repudiation.

But how do we preserve memory and distinguish truth from fiction in the age of AI?

Maciej Zemojcin, a virtual production and AI films specialist, believes that digital tools hold the key. With the support of the Auschwitz-Birkenau Foundation and Memorial, he is using advanced reality capture technologies to create a certified 1:1 3D digital replica of the former concentration camp.

The project will be revealed publicly for the first time at the Cannes Film Festival on May 15.

Feature films have not been permitted on the grounds of the Auschwitz Memorial for some 40 years. Schindler’s List, Steven Spielberg’s film about a German industrialist who saved more than a thousand mostly Polish–Jewish refugees from the Holocaust, was among those denied access.

Picture from Auschwitz, the 3D digital replica, will make the historical site available for feature film making, allowing film productions to license the 3D virtual version from the Auschwitz-Birkenau Foundation. The fees will be used to further support the Memorial. Among the project’s supporters is Ryszard Horowitz, a survivor of the Auschwitz concentration camp and one of the youngest people included on the real Oskar Schindler’s list.

The idea is to both ensure an authentic record of the past and create a digital representation that will be open and available for the future.

“In the beginning it was only about movies but in unpredictable times a secure and authenticated digital copy [of the camp] is as precious as it gets,” says Wojtek Soczewica, Director General of Auschwitz-Birkenau Foundation.

The toll that time takes on the physical evidence is not the only threat. Severe weather conditions, armed conflicts or AI-powered deep fakes can pose dangers too. And, as 3D digital replicas of physical spaces become more widespread, it is raising questions about who owns the rights to digital twins of physical places.

In the case of Auschwitz Birkenau Zemojcin has agreed to donate the rights to the Foundation and Memorial, ensuring that the guardians of this world heritage site maintain control of its digital replica.

Now that the 1:1 3D digital replica of Auschwitz I-Main Camp is finished. The next steps include doing the same for of all the interiors of Auschwitz as well as the exteriors and interiors of Auschwitz II-Birkenau, safeguarding the entire former Auschwitz-Birkenau camp area.

The Genesis of the Auschwitz Picture Project

The Auschwitz Memorial is visited by over two million people every year and remains a carefully preserved historical site. This is one of the reasons why filming at this physical location has not been possible for almost four decades.

At the same time the Memorial and Foundation realized that the site could not limit itself to physical tours and traditional means of educating people about the Holocaust. “We knew that if we decided not to enter the digital sphere others who have bad intentions would not hesitate to do so,” says Soczewica.

There are millions of pictures of Auschwitz on the Internet. Anyone with production skills could use to try and make a digital replica that could distort history. “AI opens many windows,” he says. “We are doing what is necessary to provide to the market and to the public a 100% accurate digital replica.”

Picture from Auschwitz was produced using lidar 3D scanning methods and drones, highlighting details barely visible to the naked eye, with every original brick and roof tile diligently documented.

The collected raw data will be reprocessed again in the future as emerging technologies evolve. It will also provide an accurate copy of the whole historical terrain and all post-camp infrastructure, thus securing Auschwitz evidence from any unforeseen circumstances in the future.

“What we are trying to do is find a technological way to preserve memory,” says Zemojcin.

The project was approved three years ago by the Memorial after Zemojcin produced a proof-of-concept. Producing the first phase of the project – the 1:1 3D imaging of the exterior of Camp 1 – proved challenging and took about ten times longer than expected. Auschwitz has roughly 2 million visitors a year and is open every day except for Christmas, New Year’s Day and Easter Sunday. The project had to get special permission to use drones since the site is a no-fly zone. During winter the early morning is often shrouded in fog and by the time it lifts, around 8 a.m., visitors start arriving. It is difficult to do accurate scanning if there is any movement in the frame – such as falling leaves – so filming in autumn proved to be issue. Zemojcin and a colleague did some of the filming on January 1 when the site was closed, and conditions were right.

So far, the project has collected 18,000 x 60 megapixel photographs, 1,300 lidar 3D scanning stations, 4.6 terrabytes of source data, 40 terrabytes of processed data and five hours of 360 degree video.

The project used a variety of cutting-edge methods:Photogrammetry, a method of approximating a three-dimensional (3D) structure using two dimensional images.
A point cloud, a set of data points in a 3D coordinate system that each represents a single spatial measurement on an object’s surface and taken together, represent its entire external surface.
Data collected by drone that establishes the positioning on Earth of the concentration camp barracks with an accuracy rate within two centimeters.
Gaussian splatting, a process powered by an AI neural network, was used to render extremely high-quality images — using numerous scans of an object — that can then be viewed from any angle and explored in real time.

The plan is to eventually add the collected data to the blockchain.

“We have the opportunity to be at the forefront of a discussion about authentic digital IP, how to standardize the scanning of historical sites, and how to control, certify, and authenticate, says Zemojcin. “It is a non-regulated area. We really believe that the digital replica should belong to its owners. This is why we have donated our work and the copyrights to the Auschwitz Foundation.”

The film making industry can use the Auschwitz Picture to help accurately build images in a movie, as a virtual production for real time shooting, or in post-production, Zemojcin says.



The project received minimal funds from the European Commission and the Polish Film Institute for the first phase as well as other private funds. It is currently trying to raise €1.5 million to complete the 1:1 digital rendering of the entire former Auschwitz-Birkenau camp area.

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How A “Transformer” Could Transform Healthcare, Finance And Other Industries

 

There has been a lot of buzz in the mainstream press in the last few weeks about GPT-3 which stands for “Generative Pre-Training Transformer.” Launched by OpenAI, an artificial intelligence research laboratory based in San Francisco, the beta program of GTP-3 had been described as the most powerful, yet not perfect, AI language model ever released to the public. Put simply, it is a natural language processing AI that can learn the relationships among “tokens” in a sequence, such as words in a sentence, and generate realistic sequences. This gives it the ability to write sentences in natural language, generate HTML code, compose music and more. Once perfected some speculate that GPT-3 algorithms could compete with, and maybe even replace, authors, coders and composers. But it is what is coming next that could be really interesting for healthcare, finance and other businesses, says Reza Khorshidi, one of the founders of, and currently a research leader at, the Deep Medicine Program at the University of Oxford’s Martin School, and also the Chief Scientist for global insurance company AIG. “What we are doing in our lab is taking things one step further

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How Do We Keep The Hippocratic Oath Alive In The Age Of AI?

Since the 5th century BC the medical profession has been guided by the ethical maxims enshrined in the Hippocratic Oath, which, among other things obliges physicians to share — at no cost — medical knowledge with others who are interested.

But how do we keep the oath of Hippocrates alive in a digital world in which knowledge is created by algorithms, asks Berlin-based Bart De Witte, who was, until recently a regional director of digital health at IBM. De Witte left that job earlier this year to focus on creating artificial intelligence that is based on open models available to all, a key component, he says in ensuring universal health care.

De Witte is in the process of formingthe Hippo Foundation, a not-for-profit organization that is raising funds in stealth mode.

He says he believes we are at a pivotal time in history. When Gutenberg invented the printing press he effectively democratized knowledge. “Without it, none of the stunning inventions that have changed medicine and our world, increased prosperity, and decreased inequalities in wealth, status, education and health would have been possible,” he says. Currently, investments in AI are being driven by private investors, mostcoming from venture capital firms,he says, and this will lead to a world where knowledge gets privatized, leading to data hegemony. Knowledge needs to be open and remain a public good, or we could risk to turn back to the pre-Gutenberg era, he says.

“Open and free access to knowledge leads to human societal progress,” he says. “Having no access to data and open AI models leads to zero progress.” What’s more, he says, the expected market consolidation of AI health care data could undermine the foundation of altruism on which modern medicine was built.

Major internet platforms like Amazon, Google and Alibaba have started significant investments in the digital health care sector. And consolidations through mergers and acquisitions of innovative AI appear likely. As these companies feed more data into its algorithms, it will give the companies important competitive advantages and enable winner-take-all markets, rather than ensuring that society benefits the most from AI in medicine,says De Witte.

“With AI we have the opportunity to really solve current and future inequalities in health care or to increase them,” he says. “The question we need to ask as a society is do we want health care expert knowledge to become a private or a public good?” De Witte argues that “AI should not be owned by a corporate or a government — it should be owned by all of us.” His NGO would act as an open source foundation that facilitates open sourced training of medical AI algorithms. It will introduce a new licence model that is based on so- called federated AI. Federated learning is a new framework for AI model development that can be distributed via decentralized organizations, centralizing the learning effects without compromising user privacy. The new licence model allows entrepreneurs and developers to build for-profit products and services. “While the end-products won’t be free, the knowledge will be,” says de Witte. “Anyone using the database would be obliged to give back by sharing their learnings, enriching the data, and improving healthcare.

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