Latest news with #StefanLeichenauer
Tahawul Tech
05-05-2025
- Business
- Tahawul Tech
'We don't just want to create technology, we want to have a positive impact on the world.' – Stefan Leichenauer, SandboxAQ
CNME Editor Mark Forker sat down with Stefan Leichenauer, VP of Engineering at SandboxAQ, to find out why more and more industries are increasingly opting to adopt Large Quantitative Models (LQMs) to solve their complex challenges, as opposed to LLMs. Leichenauer also outlined that ultimately their mission is to not just create technology, but instead to have a positive impact on society. Stefan Leichenauer is a man on a mission. He is driven by the fact that he works for a company that is committed to making the world a better place. That company is SandboxAQ, a B2B company that delivers AI solutions that addresses some of the world's greatest challenges. SandboxAQ was born out of Alphabet Inc. as an independent capital-backed company in 2022. Over the last number of years, it has grown exponentially across multiple global markets, and has a major partnership here in the Middle East region with Aramco. Leichenauer spoke to CNME, about why the company wants to deliver technologies that have a positive impact on society, and the critical role played by LQMs in enabling the transformation pf industries such as the Oil & Gas sector. In a recent op-ed, the VP of Engineering at SandboxAQ made the case for enterprises to shift their focus away from LLMs and to look at the LQMs to foster real change across their organisation. According to Leichenauer, LLMs have limitations, and in order to solve the really complex challenges facing the world then businesses need to start looking at LQMs. 'Firstly, let me say that I think LLMs are fantastic, and we are not working to get rid of them. However, LLMs can't do everything by themselves, and I think that's the point that I am making, and I think more and more people are starting to realise that LLMs have their limitations. If you look at the latest LLMs that have been released over the last 3 years, then it seems like every release has a new set of capabilities that can do so much more, but we have sort of hit a ceiling of late. If you examine the latest releases of Llama 4 and GPT4.5 they are only incrementally better than what has come previously. So, I think there has been a realisation that LLMs as a capability are great, processing text and generating images then it is fantastic, but there is a whole set of capabilities that LLMs are just not going to get to by themselves,' said Leichenauer. The capabilities that LLMs are not going to be able to get to by themselves is associated with quantitative reasoning, and this is where LQMs come to the fore. 'LQMs is designed to model the physical with chemistry, physics, and medicine, and is essentially focused on doing things that has absolutely nothing to do with language-based content. You need other tools in the tool box, and that's where LQMs come in. LQMs are basically providing those other tools in toolbox and they compliment the capabilities provided by LLMs,' said Leichenauer. In his op-ed, Leichenauer also claimed that when precision is paramount then LQMs are indispensable, and said momentum was beginning to swing in favour of LQMs. 'We're now seeing more proof points that LQMs. I think in the past people would have deployed LLMs on to any given problem to see what works, and what doesn't, and I think everyone has been doing proof of concept trials with LLMs, but they've fallen short for a couple of reasons. As I stated earlier, in some areas they are fantastic, but in other areas they have fallen short. One of the reasons for this is the fact that LLMs are very non-transparent in terms of their reasoning. LLMs will give you an answer, but why is it true? And the LLM could be hallucinating, and we know that's been a big problem in some areas. Hallucinations are fine when it comes to generating an image, maybe it has the wrong number of fingers, but when it comes to creating a new molecule for Aramco, that is designed to making their processing plants more efficient, then you can't get that wrong because that's going to cost you a billion dollars. You need your answer to be correct, you need it to be grounded in real understanding of the problem, and LQMs can provide that verifiability and transparency,' said Leichenauer. As aforementioned above, SandboxAQ have enjoyed great success since spinning out of Alphabet Inc. in 2022, and are working with some of the biggest companies in the Middle East, including Aramco, who are the biggest integrated energy and chemicals company in the world. He spoke about their partnership, and again reiterated their mission which is to build purposeful technology designed to improve society. 'Our goal at Sandbox at the end of the day is not to create technology, of course we love to create technology, but we are doing it for a purpose. Ultimately, our goal is to have a positive impact on the world, and it just so happens that LQM technology is a great way to have a positive impact. The impact areas that we care about the most such as the medicine, pharmaceuticals, medical devices and GPS free navigation is something that we are very passionate about. These are all powered by LQMs. In terms of our collaboration with Aramco, the oil & gas industry is a really important industry in the world. However, we are all acutely aware that as we move forward, we need to be better about being environmentally friendly, and more efficient with our energy and more sustainable. We need to always be looking at better techniques, and Aramco is a real leader and pioneer when it comes to these sort of techniques,' said Leichenauer. He went into more detail in relation to how LQM technology is enabling Aramco to transform, and how the technology is helping the global energy incumbent to be more sustainable and efficient. 'Aramco is not an AI company, they are an oil & gas company, so we are here to help our partners like Aramco to advance their operations to be able to do things in a much better way. SandboxAQ provides software tools, AI models and the LQMs that really help them to transform the way they operate their business. What we're doing with Aramco specifically is partnering with them to look closer at the oil & gas processing facilities. Ultimately, a lot of what is happening there is you've essentially got liquids and gases flowing through pipes and going through various kinds of processes, refineries and machines. However, in order to make those processes more efficient, one way to make them more efficient is to model them computationally better,' said Leichenauer. Leichenauer conceded that these processes are complex, but insisted that in order to make them more efficient and sustainable then companies like Aramco had to implement LQM technologies. 'It's a complex physical process, and if you want to make your plants more efficient, and reduce emissions and waste then modelling that process computationally allows you to make tweaks and changes virtually to enable you to implement them in real-life. Modelling all of those processes computationally is something that our software is helping Aramco with,' said Leichenauer. Leichenauer is delighted at the progress SandboxAQ has made with Aramco since their collaboration started, and believes that by 2030, it will fundamentally be a completely different business. 'The part that Sandbox has control over, and the computational modelling that enables these kinds of changes, the good news is, well from our perspective anyway is relatively simply compared to actually implementing these things physically. We have been working with Aramco for several months now, and we've already achieved significant milestones with our modelling. The LQMs that can do that sort of modelling and give you the answers and the playbook that what you need to do to make the changes those exist, and in a matter of months we have made huge progress on that. If I had to speculate a little bit then I'd guess that in the next 5 years we'll see a lot more changes coming through and being implemented. It may take longer to become 100% sustainable and 100% green, but in the oil and gas industry and other industries we can affect real changes and see real progress in a sort of 5-year timeline. By 2030 or so, a lot of the work we are doing today will have real tangible impact by then,' said Leichenauer. Another industry that SandboxAQ is looking to transform in order to ensure they are having a meaningful impact on society is the healthcare industry. 'The healthcare sector is a major industry for us. It is a major source of grand challenges for the world, but we have seen a lot of progress in the last years in terms of how technology is being used to transform healthcare. When we are talking about real positive impact on the world then there's almost no better place to have that impact than in healthcare. Within healthcare, there is obviously the pharmaceutical industry, and there's always a lot to do in that space, and in terms of medical diagnostics that is a space that also can be transformed. The MRI machine is an amazing machine, it transformed medicine when it was invented several decades ago, but it is big, it is expensive, and it's clunky, and it takes a lot of expertise to use it. The next-generation of medical diagnostic devices can bring the kind of transformative impact of the MRI machine, but in a form factor that is more like an ultrasound machine, where it can something that can be much smaller and can be in every hospital emergency room. That kind of technology is coming, and some of that is what we are working on and using LQMs to enable,' said Leichenauer. Leichenauer outlined that SandboxAQ is working on a diagnostic designed to tackle the issue of heart disease. 'We're working on a device right now using LQMs that is specifically for diagnosing heart disease, and various kinds of heart disease in an emergency room setting in a way that you could actually apply it to every patient that walks in complaining of heart problems, or persistent heart pain. One of the first things that you do is take five minutes to give them a scan using the machine, and that really improves the care of the patient, and heart disease is one of the biggest killers in the world, so this is a truly transformative device. At the minute, we have a prototype device being tested in hospitals right now, and within a couple of years I'd expect this device to be used on a everyday basis in hospitals. Early indications of the prototype is that we are on the right track, and appear to be doing a good job. However, you have to prove you're doing a good job and pass regulations and so on before you can actually go to market with such a device, but the technology is there and we are actively working on it,' said Leichenauer.
Tahawul Tech
14-04-2025
- Business
- Tahawul Tech
SandboxAQ executive believes businesses need to look beyond LLMs, and adopt LQMs to achieve AI success
Stefan Leichenauer, VP of Engineering at SandboxAQ, has penned an exclusive op-ed for April's edition of CNME, where he makes the case that businesses seeking success with AI, need to look beyond LLMs, and instead focus on LQMs. The Middle East has for a while now signaled its intentions of being a leading player in the AI revolution. And while the United Arab Emirates (UAE) became the first nation globally to appoint a Minister of Artificial Intelligence back in 2017, it was the advent of generative AI that has truly accelerated the region's ambitions. In a study of 63 use cases, McKinsey estimated the economic potential for GenAI in the GCC: it could be responsible for between US$21 billion and US$35 billion of annual value, to accompany a projected US$150 billion generated by other AI technologies in the region. But the large-language models (LLMs) that form the foundation of many, if not most, regional GenAI solutions are just the start of the story. Already another form of machine learning is getting onto the radar of forward-focused decision makers around the globe — large quantitative models (LQMs). While LLMs work with and generate language content, LQMs do the same with quantitative data that is ordinarily handled through purely numerical methods. The challenges we face in areas such as finance, healthcare, and sustainability are not fundamentally language-based challenges, and so the most effective and natural tools are not language-based tools. For a region that has shown laudable ambition in these areas, LQMs will be transformative. On the back of the UAE's' recent hosting of COP28, LQMs could help with net-zero initiatives by optimizing renewable energy integration and improving climate modelling to guide sustainable policies. And as Gulf nations ramp up their manufacturing sector to boost non-oil GDP, they can ensure businesses have access to the best material science through LQMs' ability to accelerate R&D. We're already seeing industry leaders taking action, with Aramco recently revealing its strategy for leveraging quantitative AI models for increasing value of downstream products. The right tool for the job To be clear, LQMs are not here to replace LLMs. In fact, in many cases the tools are complementary. While LLMs are fantastic for human-machine-interaction, the imprecise nature of language means that when acting alone, they will not solve quantitative problems. For example, while a user-facing LLM may work well for basic software development, additional heuristic layers may be required to align with best practices and compliance obligations. Also, an LLM may be great for customer service, but it would be an inappropriate tool for, say, pharmaceutical drug discovery. Where precision is paramount, LQMs are indispensable. Let's say you are trying to predict the weather. You have data from the past three days, and you want to predict the weather for the next three days. Imagine putting an LLM to work on the task. It acts as a sophisticated almanac, and having trawled through thousands of weather reports will extrapolate patterns, potentially delivering a result that's accurate most of the time. However, if billions of dollars or thousands of lives are on the line, 'most of the time' simply isn't enough. In predicting the next hurricane, the next wildfire, or the next sandstorm, LQMs would include physics-based models, AI models, and data from past events — any relevant technique to encode the underlying phenomena of the weather, leading to reliable and trustworthy predictions. This approach is a far cry from the simple LLM-based approach, and clearly more aligned with the task. LLMs consume the data they're served. LQMs create their own meals. The capabilities of an LLM are determined by the data it was trained on, which in most cases is just everything on the open web. There is no great store of data beyond that, and that is a limitation that LLMs have to deal with. With an LQM, we can always generate trustworthy data because we understand the fundamental principles underlying the data. We have the equations, and we can solve them in a new domain to give our models something new to train on. This infinite extensibility is special to LQMs, and is part of why they have the ability to go well beyond what LLMs alone can do. Yes, LLMs are excellent at conversation and search and can even take bold initiatives in certain controlled circumstances where they have been optimized for a specific task. But they cannot match LQMs for their ability to optimize for case-specific objectives and parameters. For example, in battery development, where lithium-ion technology has dominated for 45 years, LQMs can correct the stall in progress by simulating millions of possible chemical combinations without the need for physical prototyping. Such models can also be of great help in pharmaceutical development, where traditional approaches are beset with the high failure rates of clinical trials. LQMs can analyze molecular structures and interactions at the electron level, drastically reducing the costs of trial phases. Arts versus science Drug discovery, materials science, healthcare diagnostics, financial modelling, and industrial optimization — these are all growth areas in the GCC. Since the region's governments launched their national AI strategies, the field has expanded rapidly, culminating in the rise of GenAI. But the challenges of the day will call for decision makers to dig deeper into the AI toolbox. The precision and data-driven insights provided by LQMs are just such a tool. LQMs also operate by reaching for the most appropriate tool (be it GenAI, non-GenAI, or even non-AI) or data to solve the problem at hand. This flexibility makes LQMs an ideal investment for regional enterprises that have sought to solve their complex problems with LLMs alone, only to be disappointed. That's why forward-thinking leaders are exploring LQMs as a critical tool for tackling complex, quantitative challenges.
Tahawul Tech
10-03-2025
- Business
- Tahawul Tech
SandboxAQ joins the United Nations International Computing Centre's AI Hub as a founding member
SandboxAQ has joined the United Nations International Computing Centre (UNICC) as a founding member of its new AI Hub, which has been established to be the primary AI solutions provider and resource centre for more than 100 UN entities and other international organisations around the globe. The UNICC is the largest strategic partner for digital solutions and cybersecurity within the United Nations system. Leveraging SandboxAQ's AQtive Guard unified encryption management platform, the UNICC will begin offering AI-enhanced cryptographic discovery services to identify any vulnerable cryptography (e.g., outdated or expired algorithms, keys and certificates) throughout a member organisation's entire IT infrastructure, including applications, networks, and filesystems. These insights will enable constituents and partners to upgrade their cryptography to meet emerging and future threats, including AI- and quantum-based attacks. 'Over the last five decades, UNICC has continually expanded the diverse technology services designed for the UN family, including fostering strategic partnerships with trusted partners like SandboxAQ to develop state-of-the-art solutions', said Sameer Chauhan, Director, UNICC. 'Leveraging SandboxAQ's innovative quantum, AI and cybersecurity solutions, we're pleased to welcome them as a founding member of the UNICC AI Hub and share their expertise with our partners'. The UNICC AI Hub's focus and mission The new UNICC AI Hub will serve as a center of excellence for AI deployment within the UN system and other international organizations, gathering best-in-class experts, partners, knowledge, solutions and capabilities to help constituents and partners accelerate positive impact around the world. The AI Hub will provide expertise and training on a broad range of predictive, generative and quantitative AI solutions that are UN-tailored, battle-tested, cost-effective, secure and compliant. The AI Hub and members such as SandboxAQ will assist with setting up and scaling AI projects, ensuring robust data integrity, ethical compliance, optimal model performance, and measurable results. In addition to cybersecurity services and solutions, SandboxAQ will collaborate with the UNICC to roll-out additional quantitative AI solutions powered by Large Quantitative Models (LQMs). These solutions will drive breakthroughs in complex system modeling, post-quantum cryptography, predictive analysis, and other areas related to the Sustainable Development Goals, such as clean water, good health and wellbeing, climate action, and affordable clean energy. 'As AI continues to fundamentally transform all aspects of our daily lives and the global digital economy, we applaud the UNICC's bold step to create a one-stop shop where all UN agencies and affiliates can find the AI expertise, resources and solutions they need to protect themselves from cyber attacks and affect positive change on a global scale', said Stefan Leichenauer, VP Engineering of SandboxAQ. 'SandboxAQ is incredibly proud to be a founding member of the UNICC's AI Hub, and we look forward to helping its members tackle some of society's biggest challenges'. For more information about SandboxAQ's solutions, please visit For more information about UNICC, please visit Image Credit: SandboxAQ
TECHx
04-03-2025
- Business
- TECHx
SandboxAQ Joins UNICC AI Hub to Boost Global Cybersecurity - TECHx Media SandboxAQ Joins UNICC AI Hub to Boost Global Cybersecurity
SandboxAQ Joins UNICC AI Hub to Boost Global Cybersecurity SandboxAQ has become a founding member of the United Nations International Computing Centre (UNICC) AI Hub, which aims to provide AI solutions and resources to over 100 UN entities and international organizations worldwide. The UNICC, the largest strategic partner for digital solutions and cybersecurity within the UN system, will integrate SandboxAQ's AQtive Guard unified encryption management platform to offer AI-powered cryptographic discovery services. This collaboration will help organizations identify vulnerable cryptography—such as outdated algorithms, keys, and certificates—across their IT infrastructure, including applications, networks, and filesystems. The service will equip members with the insights needed to upgrade cryptographic security and prepare for future threats, including AI- and quantum-based attacks. Sameer Chauhan, Director of UNICC, expressed excitement over the new partnership: 'Over the last five decades, UNICC has continually expanded the diverse technology services designed for the UN family, including fostering strategic partnerships with trusted partners like SandboxAQ. Their innovative quantum, AI, and cybersecurity solutions will be a valuable addition to the AI Hub.' The UNICC AI Hub, launched as a center of excellence, will focus on deploying AI within the UN system and other global organizations. The Hub will bring together top experts, partners, and knowledge to help accelerate positive global impact. It will provide training and expertise in predictive, generative, and quantitative AI solutions that are secure, compliant, and tailored for the UN system. SandboxAQ and other members will collaborate on scaling AI projects, ensuring data integrity, ethical compliance, and optimal model performance. In addition to its cybersecurity contributions, SandboxAQ will help the UNICC roll out additional quantitative AI solutions powered by Large Quantitative Models (LQMs). These solutions are expected to drive innovations in areas such as post-quantum cryptography, predictive analysis, and sustainable development goals, including clean water, health, climate action, and affordable energy. Stefan Leichenauer, VP of Engineering at SandboxAQ, emphasized the significance of the AI Hub: 'As AI continues to transform the digital economy, the UNICC's creation of a one-stop shop for AI expertise and solutions is a major step forward. We're proud to be a founding member and look forward to supporting its mission to tackle global challenges.' Through this partnership, SandboxAQ is set to play a critical role in advancing cybersecurity and AI solutions to address some of the world's most pressing challenges.
