What if we could understand brain activity in real-time to better diagnose neurological conditions? In this episode, part of a special mini-series on domain-specific foundation models, I sit down with Dimitris Sakellariou, the founder and CEO of Piramidal, to talk about their groundbreaking work in automating EEG interpretation. Piramidal is focused on democratizing brain health insights, making interpreting brainwave data more accessible and accurate. With a strong foundation in neuroscience and AI, Dimitris and his team are developing models that could revolutionize how we understand brain activity and diagnose neurological conditions.

In our conversation, Dimitris explains the challenges of building a foundation model for brain activity, the role of data diversity, and the future potential for personalized brain health monitoring. Discover the implications of Piramidal’s technology beyond healthcare and its application in cognitive enhancement and stress management. Tune in as we explore how Piramidal is paving the way for personalized brain health monitoring and why this could be a game-changer for the future of medicine!

Key Points:

• Dimitris discusses his journey from physics to a career in neuroscience.
• Explore Piramidal's mission to automate EEG interpretation.
• Learn about the complexity and variability of brainwave patterns
• Hear how machine learning can better analyze brain activity.
• Uncover the challenges of building a foundation model for EEG data.
• Why diverse data sets are vital for training the foundational model.
• Piramidal's plans for making EEG analysis more accessible.
• Future use cases for Piramidal’s model in healthcare and beyond.
• Discover why domain knowledge for model building is essential.
• He shares advice for AI startup founders.

Quotes:

“Piramidal is primarily focused at the moment in automating, or otherwise democratizing the interpretation of these tests, these brainwave recordings so that patients and people that have issues with their brain can get access to the diagnosis much, much, much faster.” — Dimitris Sakellariou

“It's very important to have discussions with neuroscientists and clinical experts in order to understand what is the end-to-end pipeline from receiving data all the way to inference.” — Dimitris Sakellariou

“Finding the right person. Someone that is very keen to build together with you and make important and difficult decisions can change massively a trajectory of your company.” — Dimitris Sakellariou

Links:

Dimitris Sakellariou on LinkedIn

Dimitris Sakellariou on X

Piramidal

Piramidal on LinkedIn

Resources for Computer Vision Teams:

LinkedIn – Connect with Heather.

Computer Vision Insights Newsletter – A biweekly newsletter to help bring the latest machine learning and computer vision research to applications in people and planetary health.

Computer Vision Strategy Session – Not sure how to advance your computer vision project? Get unstuck with a clear set of next steps. Schedule a 1 hour strategy session now to advance your project.

In a world where conventional drug discovery methods frequently fall short, today's guest addresses the critical challenge of fighting human diseases by drawing inspiration from nature’s most resilient creatures. Could the secret to overcoming our most stubborn illnesses lie in the extraordinary adaptability of extreme mammals? Veterinarian-scientist Ashley Zehnder, the Co-founder and CEO of AI-driven drug discovery company Fauna Bio, believes so.

By leveraging data from 100 million years of evolved disease resistance in mammals, Ashley sees a unique opportunity at the crossroads of genomics and emerging model species to improve health for all species, including humans. In this episode, she explores how harnessing the biological secrets of these animals using AI and machine learning could revolutionize medicine, leading to breakthroughs that benefit us all. Tune in to discover how Fauna Bio is pioneering a new frontier in drug discovery and how understanding the resilience of these creatures could reshape the future of healthcare!

Key Points:

• Insight into the diverse backgrounds of Fauna Bio’s founding members.
• Ways that Fauna Bio uses AI and genomics to identify key targets for new therapeutics.
• The role machine learning plays in analyzing and annotating large volumes of data.
• Gene expression and other data inputs that drive Fauna Bio’s discoveries.
• The collaborative effort required to collate datasets from 400+ mammals.
• Challenges of working with genomic data and training ML models on it.
• How Fauna Bio rigorously validates their AI-driven discoveries.
• Cooperation between ML developers and domain experts to advance this technology.
• Technological advancements that enable Fauna Bio’s innovations.
• Ashely’s advice on differentiation for leaders of AI-powered startups.
• Where she sees Fauna Bio making the biggest impact in the future.

Quotes:

“[Fauna Bio uses] AI and genomics as a way to identify the most impactful targets for new therapeutic programs across a broad number of diseases.” — Ashley Zehnder

“It’s certainly easier than it has been in the past to generate very high-quality single-cell RNA sequencing. We’re doing a lot of that. The challenges on the technical side are getting much easier. The challenges on the interpretation side are still there.” — Ashley Zehnder

“There are many points along the drug discovery path where AI companies can differentiate. But that story has to be clear because, otherwise, it's very hard to get out of the signal-to-noise that is the AI discovery landscape in biopharma” — Ashley Zehnder

Links:

Fauna Bio

Ashley Zehnder on LinkedIn

Ashley Zehnder on X

Ashley Zehnder Email

Zoonomia Project

Science Issue dedicated to the Zoonomia Project

Resources for Computer Vision Teams:

LinkedIn – Connect with Heather.

Computer Vision Insights Newsletter – A biweekly newsletter to help bring the latest machine learning and computer vision research to applications in people and planetary health.

Computer Vision Strategy Session – Not sure how to advance your computer vision project? Get unstuck with a clear set of next steps. Schedule a 1 hour strategy session now to advance your project.

One of the biggest hurdles in medical research is the gap between animal studies and human trials, a disconnect that often leads to failed drug tests and wasted resources. But what if there was a way to bridge that gap and create treatments that are more effective for humans from the start?

Today, I am joined by Dr. Andrei Georgescu, Founder and CEO of Vivodyne, a groundbreaking biotechnology company that is transforming how scientists study human biology and develop new therapeutics. In this episode, he reveals how Vivodyne harnesses lab-grown tissue and advanced multimodal AI to create more effective therapeutics. We explore the challenges of gathering human tissue data, the collaboration between biologists, robotics engineers, and machine learning developers to build powerful machine learning models, and the profound impact that Vivodyne is poised to make in the fight against diseases. To discover how Vivodyne’s innovations can lead to more successful treatments and faster drug development, tune in today!

Key Points:

• Insight into Andrei’s background and how it led him to create Vivodyne.
• What Vivodyne does and why it’s so important for drug discovery.
• The role that AI and machine learning play in analyzing vast amounts of data.
• Different data inputs and outputs for Vivodyne’s advanced multimodal AI.
• The value of biased and unbiased AI outputs depending on the context.
• Why interpretability and explainability are crucial in fields like biotechnology.
• Challenges associated with collecting human tissue data to train Vivodyne’s models.
• What goes into validating Vivodyne’s machine learning models.
• Difficulties in integrating biology knowledge with robotics and machine learning.
• Andrei’s business-focused advice for technical founders.
• The profound impact that Vivodyne will have on drug discovery in the future.

Quotes:

“Vivodyne grows human tissues at a very large scale so that we can understand human physiology and we can test directly on it in order to discover and develop better drugs that are both safer and more efficacious.” — Andrei Georgescu

“We use machine learning and AI as a mechanism to understand the complexity of very deep data and to very efficiently apply that complexity and infer from what we've learned across the very large breadth of data that we collect.” — Andrei Georgescu

“To address [the problem of a] glaring lack of trainable data, we create that data by growing it at scale.” — Andrei Georgescu

“If you're a technical founder, do something that is incredibly hard because the ability for you to do that thing will grant you much more leverage than creating what is otherwise a much more simple and generic business.” — Andrei Georgescu

“[With Vivodyne], we will enter a world of plenty where the development of new drugs against diseases becomes a far more successful, reliable, and predictive process, and we're able to make much safer and much more effective drugs just by virtue of being able to optimize that therapeutic on human tissues before giving it to people for the first time in-clinic.” — Andrei Georgescu

Links:

Andrei Georgescu

Vivodyne

Andrei Georgescu on LinkedIn

Resources for Computer Vision Teams:

LinkedIn – Connect with Heather.

Computer Vision Insights Newsletter – A biweekly newsletter to help bring the latest machine learning and computer vision research to applications in people and planetary health.

Computer Vision Strategy Session – Not sure how to advance your computer vision project? Get unstuck with a clear set of next steps. Schedule a 1 hour strategy session now to advance your project.

Marie Coffin is the Vice President of Science and Modeling at CIBO Technologies, and she is with me today to discuss regenerative agriculture. Join us as we explore CIBO’s work to influence company carbon footprints across industries, and how machine learning supports this process through remote sensing. Delving deeper, Marie unpacks how satellite imagery integrates with their computer vision system for a more scalable solution. Next, we discuss obtaining and categorizing data in the US, exploring some of the obstacles that stem from privacy and data protection concerns. We touch on data quality and discuss the reason behind the geographical parameters they have applied to the work before Marie shares her approach to collaborating with external experts and agronomists. She offers her advice for startups in the tech space, emphasizing creating value for your clients over keeping up with trends, predicts the future endeavors that CIBO will focus on, and more. Thanks for listening!

Key Points:

• Introducing Marie Coffin and her background leading up to her role at CIBO Technologies.
• CIBO’s work to influence company carbon footprints to improve agricultural sustainability.
• The role of machine learning in this process: remote sensing.
• What remote sensing is used for at CIBO.
• How satellite imagery interacts with their computer vision system.
• Gathering, labeling, and annotating data with a focus on the boundary of the field.
• Obtaining this information through a farmer’s recording process.
• Why their work is largely limited to the US at the moment.
• Challenges related to privacy and data protection while working with training models.
• Managing data quality issues.
• Validating models within a geographical context.
• Collaborating with domain experts and external agronomists to understand and validate thier approaches.
• How the seasonal nature of agriculture impacts the timing of reports and outputs.
• Advice for tech startups; addressing trends, who to hire, and more.
• Qualities Marie seeks in new hires.
• Her prediction for CIBO’s growing impact in the next three to five years.

Quotes:

“It’s pretty straightforward to estimate the carbon footprint of a single farmer’s field or even the carbon footprint of a whole farm, but, to make an impact, we need to be able to scale that across the landscape.” — Marie Coffin

“That is really the biggest challenge; it’s just getting enough data.” — Marie Coffin

“When you’re working in a really cutting-edge area, it’s tempting to sort of get caught up in the buzz of the new technology and lose sight of what the customer needs.” — Marie Coffin

“We need to not always be following the latest, greatest advance. We need to be going in a direction that’s going to really provide value.” — Marie Coffin

Links:

CIBO Technologies

Marie Coffin on LinkedIn

Resources for Computer Vision Teams:

LinkedIn – Connect with Heather.

Computer Vision Insights Newsletter – A biweekly newsletter to help bring the latest machine learning and computer vision research to applications in people and planetary health.

Computer Vision Strategy Session – Not sure how to advance your computer vision project? Get unstuck with a clear set of next steps. Schedule a 1 hour strategy session now to advance your project.

What if technology could be the key to averting a biodiversity crisis? Today, I explore this possibility with Mads Fogtmann, Chief Data Officer of FaunaPhotonics, as we discuss their groundbreaking approach to biodiversity monitoring. I talk with Mads about the looming biodiversity crisis, the innovative solutions his team is developing to address the urgent need for scalable biodiversity monitoring, and the central role that humans have to play in all this. Find out how the FaunaPhotonics platform is employing advanced sensing technology and machine learning to protect ecosystems, why insects are such useful proxies for monitoring ecosystem health, and their successful partnerships with other domain experts and researchers. Our conversation also covers the broader implications of biodiversity loss, the role of public awareness in conservation, and the future of biodiversity monitoring. Join us for a comprehensive and insightful discussion on how technology can help safeguard our planet's future and ensure the stability of natural and human systems alike!

Key Points:

• Some background on Mads and his transition from academia to the private sector.
• The FaunaPhotonics platform and how it monitors biodiversity.
• An overview of the biodiversity crisis and the urgent need to address it.
• Understanding our connection to, and dependence on, nature.
• The risks that the biodiversity crisis poses for supply chains.
• FaunaPhotonics’ role in measuring the biodiversity crisis: why this protects ecosystems.
• Why insects are the best available proxy for measuring ecosystem health.
• How sensing technology and machine learning are utilized by FaunaPhotonics.
• Case studies showcasing the impact of FaunaPhotonics' technology.
• Future directions and innovations in biodiversity monitoring.
• Key challenges faced in developing and deploying biodiversity monitoring technology.
• FaunaPhotonics’ collaboration with other domain experts and researchers in the field.
• Why there is such an urgent need for scaleable biodiversity monitoring.
• The importance of public awareness and education in addressing the biodiversity crisis.
• Mads’ advice to leaders of other AI-powered startups and the future of FaunaPhotonics.

Quotes:

“The clothes we wear, the food we eat, the water we drink, the material we use to build houses: everything comes from nature. And right now, we are destroying that foundation rapidly.” — Mads Fogtmann

“I think it’s important that we become more aware that we are an integral part of nature.” — Mads Fogtmann

“If you can’t measure it, then how can you protect the rights? – [We come with the solution] that allows them to measure [the impact on biodiversity] so they can protect it. We do this by using insect sensing. The reason we do this is that insects are so fundamental to the ecosystem.” — Mads Fogtmann

“Insects are the best proxy that you can have for actually measuring the health of [an] ecosystem.” — Mads Fogtmann

“There’s a huge need and an interest in ‘how we can actually scale biodiversity monitoring to kind of help us understand what’s going on with nature at the moment.’” — Mads Fogtmann

Links:

Mads Fogtmann on LinkedIn
FaunaPhotonics

FaunaPhotonics on LinkedIn

Resources for Computer Vision Teams:

LinkedIn – Connect with Heather.

Computer Vision Insights Newsletter – A biweekly newsletter to help bring the latest machine learning and computer vision research to applications in people and planetary health.

Computer Vision Strategy Session – Not sure how to advance your computer vision project? Get unstuck with a clear set of next steps. Schedule a 1 hour strategy session now to advance your project.

Manufacturing is a fundamental part of our economy. Unfortunately, a huge swath of the industry is still dependent on outdated methods, adversely impacting our environment. To address these challenges, one company is harnessing the power of AI to transform traditional manufacturing, driving unprecedented efficiency and sustainability in the industry. Joining me today is Berk Birand, co-founder and CEO of Fero Labs, to unpack how AI is optimizing the manufacturing sector.

Tuning in, you'll learn all about Fero Labs' innovative software and how it’s empowering engineers in industries like steel and chemicals to harness machine learning, drastically reducing waste and energy consumption. We discuss how their AI analyzes historical production data to ensure factories operate at peak performance and how this is boosting sustainability and profitability. Our conversation also unpacks the critical role of explainable AI in building trust within the industrial sector, where precision and reliability are essential. Tune in to discover how Fero Labs is paving the way for a greener industrial future!

Key Points:

• Berk Birand’s education and career background.
• How he co-founded Fero Labs with his business partner.
• An overview of Fero Labs’ AI software.
• Fero Labs’ role in reducing raw material waste in the steel industry.
• How they have helped improve energy efficiency in chemical manufacturing.
• Data analysis and how their software provides recommendations for efficient operations.
• Understanding the high stakes involved in manufacturing processes.
• Why AI explainability is crucial in the industrial sector.
• How they are building explainable models that engineers can trust and understand.
• Why now is the right time to build this technology.
• His advice to AI-powered startups: seriously consider the cost of a bad prediction.
• Fero Labs’ long-term vision to achieve a more circular and sustainable industrial sector.

Quotes:

"One of our largest customers was able to reduce the waste of raw materials, about a million pounds just throughout last year, by using our software AI system." — Berk Birand

"We think AI will play a key role in the transition to a green economy." — Berk Birand

"The best people to be solving these types of challenges, ultimately, are the engineers that work at the plants. The engineers that have the most domain expertise." — Berk Birand

"In an environment like this, an engineer in a factory would just not want to use a software that they don't trust, because ultimately, it's their job that's on the line." — Berk Birand

“With the new drive towards building an industrial sector that is more circular and more sustainable, there's incredible potential to optimize not just an individual factory, but beyond that, to optimize the entire supply chain by optimizing factories jointly.” — Berk Birand

Links:

Berk Birand on LinkedIn

Fero Labs

Resources for Computer Vision Teams:

LinkedIn – Connect with Heather.

Computer Vision Insights Newsletter – A biweekly newsletter to help bring the latest machine learning and computer vision research to applications in people and planetary health.

Computer Vision Strategy Session – Not sure how to advance your computer vision project? Get unstuck with a clear set of next steps. Schedule a 1 hour strategy session now to advance your project.

In this episode of Impact AI, we delve into the transformative impact of AI on in-vitro fertilization (IVF) with Daniella Gilboa, co-founder and CEO of AIVF, a startup that develops AI-powered IVF solutions to help increase the certainty of a successful journey to parenthood. Join me as Daniella shares her mission to democratize fertility care and offers insight into AIVF’s proprietary technology that delivers reliable, objective, and data-driven IVF outcomes for clinicians, embryologists, and patients. We explore the role and challenges of machine learning at AIVF, strategies for validating AI models in clinical practice, and the current demand for AI-powered IVF solutions. We also discuss the metrics used to measure the impact of AIVF's technology, Daniella’s advice for other AI-powered startup leaders, and her vision for the future. Tune in to gain valuable insights into the future of fertility care and find out how AI is making IVF more effective and accessible!

Key Points:

• How Daniella came to understand the epidemiology and data aspects of fertility.
• What AIVF does and why it’s so important for both patients and clinicians.
• The role of machine learning at AIVF and the challenges their models encounter.
• AIVF’s strategy for validating their models and translating KPIs into clinical settings.
• The value of explainability to empower embryologists to use AI as a tool.
• Daniella’s definition of computational embryology, assisted by machine learning.
• Why now is the right time for AI-powered IVF solutions.
• Metrics that AIVF uses to measure the impact of their technology.
• Danielle’s advice for leaders of AI-powered startups and her vision for the future.

Quotes:

“We showed that if you use AI as a tool for the embryologist – [it] increased the success rates – The decision-making is faster, more accurate. You freeze less embryos because each embryo you freeze is accurate – It changes the way the lab works and it optimizes everything.” — Daniella Gilboa

“The way you interact with the patient and consult the journey ahead is changing. It’s more accurate. It allows you to make more informed decisions. This is the right way of doing medicine. It needs to be data-driven rather than subjective human analysis.” — Daniella Gilboa

“AIVF needs to become the standard of care.” — Daniella Gilboa

Links:

AIVF

Daniella Gilboa on LinkedIn

Daniella Gilboa on X

Resources for Computer Vision Teams:

LinkedIn – Connect with Heather.

Computer Vision Insights Newsletter – A biweekly newsletter to help bring the latest machine learning and computer vision research to applications in people and planetary health.

Computer Vision Strategy Session – Not sure how to advance your computer vision project? Get unstuck with a clear set of next steps. Schedule a 1 hour strategy session now to advance your project.