AI In Scientific Research

Today at #AdoptAI, I thought back to the moment when artificial intelligence truly clicked for me. It didn’t come from a strategic report or a board discussion. It came from my teenage daughter. One evening, I caught her using Le Chat (France’s homegrown ChatGPT) while doing her homework. My first reaction was the one you would expect: a bit of parental panic of course. But then, I looked closer. She was not using it to cheat. She had uploaded her notes and was asking the AI to quiz her, acting as a study partner with infinite patience. That moment changed my perspective completely. I realized #AI really is about putting us back in control of our own progress, rather than merely replacing human intelligence. It is not a magic wand, but rather a very powerful catalyst to accelerate innovation and human expertise. At the same time, this experience reminded me of the importance of developing AI responsibly and ethically, and of carefully choosing when and how to use it. So, since we are on a quest to massively accelerate #EcologicalTransformation that delivers for our clients, I see AI as the means to multiply Veolia’s impact tenfold. How? We are already partnering with the world’s largest data center operators over 100 sites worldwide to transform these energy-intensive giants into agents of territorial circularity. ➡️ Instead of wasting the massive heat generated by computing power, we can capture it to warm nearby schools, hospitals, and homes, leading to +20% of energy reuse. ➡️ Instead of draining local water supplies, AI-enabled treatment systems can recycle cooling water, reducing the water footprint by up to 75%. ➡️ And instead of letting strategic metals go to waste, we can massively recycle them, getting up to 95% circularity. So yes, the AI boom will undeniably put tremendous stress on our natural resources. But yes, we have the tools to use AI itself to massively optimize the resource intensiveness, not only of data centers, but of all industrial activities. This is how we reconcile the digital and environmental transitions. By 2030, our obsession is zero waste, tracking every drop of water and every kilowatt in real time. At the end of the day, we will know that AI can succeed if we achieve a transition where its environmental benefits exceed the costs. I am fully confident that we can make it happen at Veolia, because we already are for many projects. Thank you to Adopt AI and Samantha Simmonds of the BBC for the opportunity to discuss this all-important topic. The future starts now!  

Reimagining Soil Health and Sustainability through Insoil - Empowering Agricultural Communities and Decarbonizing the Planet!! It was a pleasure to witness the most advanced soil testing technology in the world deliver comprehensive soil analysis in just 20 minutes, providing all the necessary parameters for farmers to understand their soil and make informed decisions. This patent-pending technology developed by Absolute®, the only one certified by the ICAR- Indian Council of Agricultural Research (ICAR), takes advancements in photo-spectrometry and machine learning to unprecedented levels. Observing the journey of Insoil from its inception to this point is nothing short of exhilarating. Restoring Soil Fertility: The Key to Sustainable Agriculture Insoil's technology represents a groundbreaking shift in how we approach soil health and sustainability. With the capability to provide detailed data on soil composition, mineral content (including nitrogen, potassium, phosphorus, and micronutrients), pH levels, and various soil fertility indicators, farmers are equipped with the knowledge to retain and enhance their soil health. Empowering Farmers to Grow Better Insoil by leveraging AI-driven nutrient recommendations based on precise soil test data helps farmers optimize their use of inputs, leading to improved crop yields and greater sustainability. This tailored approach not only fosters better agricultural practices but also enhances the profitability of farming operations. As farmers implement these data-driven insights as part of wider 'UPAJ' digital ecosystem, they experience firsthand the benefits of modern technology in boosting productivity and ensuring the longevity of their land. Saving Soil: A Pathway to Transforming Agriculture Saving soil is critical to transforming agriculture, preserving essential biodiversity, and sequestering carbon into the ground. The overarching purpose of Insoil is to heighten awareness about soil health through robust testing procedures and to provide expert-driven solutions tailored to the unique agricultural contexts of different regions. This initiative is not just about technology; it's about fostering a deeper understanding and appreciation for soil health among farmers and the broader agricultural community. As we look to the future, the potential of Insoil to revolutionize agriculture is immense. The journey of Insoil from an idea to a game-changing technology is a testament to the power of innovation in addressing some of the most pressing challenges facing agriculture today. Insoil is more than just a soil testing technology; it's a comprehensive solution that empowers farmers, promotes sustainability, and helps decarbonize the planet. My congratulations to team Absolute® and it's leadership Agam Khare, Prateek Rawat, Prateek Vidya, and Sourabh Bagla for such a fabulous product and for winning various awards at the 15th Agriculture Leadership Conclave.

AI that counts sheep. Not the kind that helps you sleep. This footage shows AI models counting and tracking sheep with accuracy that would take humans hours to achieve manually. Agriculture is being transformed by computer vision that can detect, count, and monitor livestock at scale. Farmers managing thousands of animals can now get precise counts instantly instead of manual tallies that are always approximate. But the applications extend far beyond counting. The same technology detects health issues by identifying animals moving differently. → Tracks growth rates.  → Monitors feeding patterns.  → Identifies animals that need veterinary attention before visible symptoms appear. This is precision agriculture enabled by AI that can process visual information faster and more consistently than human observation. The technology applies to crops as well. → Detecting disease in plants. Identifying optimal harvest timing.  → Monitoring soil conditions.  → Tracking equipment across vast properties. Agriculture has always been about managing biological systems at scale. AI gives farmers tools to observe and respond to those systems with precision that was never possible before. The revolution is giving farmers capabilities to manage complexity that overwhelmed manual observation. What other industries have observation problems that computer vision could solve at scale?

From Policy to Practice: A New Era of Agritech Innovation for Maharashtra As Maharashtra charts its path toward inclusive agritech transformation, AI is emerging as a powerful ally for smallholder farmers — not just in theory, but through real, ground-level impact. Here’s how AI is already making a difference: 1. Personalized Advisory in Marathi AI-powered apps like #MahaVISTAAR_AI deliver crop-specific guidance in local languages — from sowing to pest control — making precision farming accessible to all. 2. Crop Monitoring & Yield Forecasting Satellite imagery + AI models help forecast yields, detect vulnerabilities, and guide climate-resilient planning. 3. Disease & Pest Detection via Smartphones Farmers can snap a photo of a diseased leaf and receive instant AI-driven diagnoses and treatment suggestions. 4. Market Intelligence & Price Forecasting AI tools analyze mandi arrivals and demand trends to help farmers time their sales and avoid distress pricing. 5. Curbing Black Marketing of Inputs AI-backed traceability platforms ensure certified seeds and fertilizers reach the right hands. 6. AI-Based Credit Scoring New models bypass traditional CIBIL scores, unlocking formal credit and insurance for smallholders. 7. Sandbox Pilots for Local Innovation Startups can test AI tools using anonymized farm data from #CropSAP, Mahavedh, and #AgriStack — driving region-specific solutions. Maharashtra’s AI & Agritech Innovation Center is laying the groundwork for scalable, farmer-first solutions. The opportunity to co-create with startups, policymakers, and researchers has never been more exciting. What do you think? PoCRA: Nanaji Deshmukh Krushi Sanjivani Prakalp #Agritech #AIForFarmers #MaharashtraInnovation #InclusiveGrowth #StartupIndia #DigitalAgriculture #ThoughtLeadership

AI is making the invisible visible. Ghost nets, or abandoned fishing gear, make up almost 30% of ocean plastic waste. They drift silently through our seas and oceans, entangling over 500 species—from turtles to sharks to whales. These nets can take centuries to decompose and locating them has long been a near-impossible task. But today, with the help of AI-powered platforms like https://msft.it/6047sNT7V, the tide is turning. By combining expert knowledge with the power of AI, WWF Deutschland has recovered 33 tons of ghost nets from the Baltic Sea. Biologists are using AI to scan enormous amounts of sonar data to pinpoint patterns that suggest ghost nets may be hiding beneath the waves. With an impressive 94% accuracy, this tool can guide divers to the likely locations of these nets, making cleanup efforts faster, smarter, and safer. And when it’s time to dive, Crayton Fenn leads the way. With decades of experience and a deep understanding of underwater recovery, Crayton turns AI signals into successful missions, navigating tough conditions to recover ghost nets and protect marine life. His work is a reminder that even the most advanced technology still relies on human skill to fulfill its potential. Through powerful partnerships with WWF Germany and Accenture, we’re combining technological innovation with field expertise to protect our oceans for future generations. It’s inspiring to see what’s achievable when passionate people and advanced technology join forces. https://msft.it/6048sNT7n

The world is changing. 2024 was the first year to surpass 1.5 degrees Celsius. Climate change, deforestation, pollution—the challenges aren’t new. We have been hearing about them for years. But can AI become a true game-changer in addressing them? In 2024, natural disasters caused $368 billion in economic losses worldwide, with 60% of these damages uninsured. Despite this, AI-powered tools are beginning to shift how we respond. ➡️ AI-powered tools, like Google Earth’s Cloud Score+, are stepping up to fill critical gaps. By providing clearer images of ecosystems obscured by clouds, such innovations make monitoring the environment faster and more accurate. ➡️ AI Algorithms now track polar ice melt, analyze deforestation trends, and even alert authorities to illegal logging within hours. ➡️  In Brazil, AI-driven deforestation monitoring cut illegal activities by 20% last year, saving millions of hectares of rainforest. These advancements highlight how AI turns raw satellite data into tools for immediate action. ➡️  Researchers are deploying AI-powered drones to track marine species, improving conservation efforts. Smart fishing systems, driven by AI, help reduce bycatch by distinguishing between target fish and other marine life. ➡️ Air quality monitoring is being transformed by AI. Google’s Air View+ system in India has improved air quality in cities like Aurangabad by 50% over three years, proving how AI can drive cleaner urban environments. The possibilities are limitless, from personalized climate action plans to autonomous drones monitoring remote ecosystems. But technology alone isn't enough. AI gives us the tools to combat environmental crises, but the question remains: how will you contribute? Whether adopting eco-friendly habits, supporting AI initiatives, or staying informed, every action counts. What do you think? #AI #climatechange #technology

Some thoughts on the state of the AI Industry today: Hype is omnipresent in the rapidly evolving world of Artificial Intelligence (AI). Every day, new breakthroughs and advancements are touted as the next big thing, promising to revolutionize industries and solve complex problems. However, amidst this excitement lies a significant danger: the risk of being misled by the noise and falling victim to inflated expectations. One of the primary dangers of AI hype is the potential for misallocation of resources. Companies and individuals, driven by the fear of missing out, often invest heavily in AI technologies without fully understanding their capabilities and limitations. This can lead to wasted resources and failed projects. For instance, the AI bubble of the 1980s, known as the "AI Winter," saw massive investments in AI technologies that were not yet mature. Many investors suffered significant financial losses when these technologies failed to deliver on their promises. To avoid falling prey to the hype, it is crucial to filter out the noise and focus on the signal – the true, sustainable advancements in AI. Here are some practical steps to help navigate this landscape: - Do Your Research: Before investing in or adopting any AI technology, conduct thorough research. Understand the technology's underlying principles, its current state of development, and its realistic applications. Be wary of exaggerated claims and seek information from reputable sources. - Look for Proven Use Cases: Focus on AI solutions that have demonstrated success in real-world applications. Case studies and testimonials from credible organizations can provide valuable insights into the technology's effectiveness. - Adopt a Skeptical Mindset: Approach AI innovations with a healthy dose of skepticism. Question the feasibility of grand promises and seek out expert opinions. Remember that if something sounds too good to be true, it probably is. - Learn from History: Historical examples, such as the Dot-Com Bubble and the AI Winter, serve as cautionary tales. During the Dot-Com Bubble of the late 1990s, many internet companies with unsustainable business models received exorbitant valuations, leading to a market crash when reality set in. Similarly, the AI Winter reminds us of the importance of aligning expectations with technological realities. In conclusion, while the potential of AI is immense, it is essential to navigate its landscape with caution. By filtering out the noise and focusing on substantiated advancements, we can harness the true power of AI without falling victim to the dangers of hype. Let's learn from the past and approach the future of AI with informed optimism and strategic discernment.

Forest carbon monitoring gets an AI boost, reports Abhishyant Kidangoor. Forests have long been surveyed from above. Satellite data reveal where they stand and how they shrink or grow, while lidar—laser-based radar—has allowed scientists to map them in 3D, uncovering details that lie beyond human sight. Now, artificial intelligence is adding a new layer of insight. Earth-imaging company Planet has unveiled a Forest Carbon Monitoring tool that fuses its satellite imagery with lidar data. The tool can estimate carbon storage, tree height, and canopy cover in remote forests at a granular resolution of three meters. “It will help us understand aspects of the forest that might not be initially accessible to the naked eye,” says Andrew Zolli, Planet’s chief impact officer. Satellites track forest cover but not the carbon stored in biomass. Measuring this requires lidar, which calculates tree dimensions by measuring the time laser beams take to bounce off foliage. NASA’s GEDI mission, mounted on the International Space Station, has mapped swathes of forests, but coverage gaps persist. Planet’s tool aims to bridge these voids, training machine-learning models to infer carbon data in areas without lidar coverage. Initial findings from the tool have been striking. While deforestation ravages the Amazon, the northern reaches harbor untouched carbon reserves. “What really resonated with me is the understanding of where we have extant forest carbon stocks which we must absolutely protect,” says Zolli. The data also underpin Project Centinela, which supports conservation efforts in biodiversity hotspots like Tanzania’s Gombe Stream National Park. Meanwhile, carbon markets—often criticized for opacity—may gain credibility through applications of the tool argues Zolli: “The data gives a shared, common picture of what’s actually happening on the ground.” Planet’s innovation rests on decades of data, cutting-edge AI, and cloud computing. “We are the first generation that has had all three in place,” Zolli says, enabling swift, confident assessments of carbon across the globe. 📰 story: https://lnkd.in/gwRWf5Qf 📷: A view of carbon storage in forest and an area of fishbone deforestation in the Brazilian Amazon. Image courtesy of Planet.

𝐈𝐧𝐝𝐢𝐚, 𝐭𝐡𝐞 𝐠𝐥𝐨𝐛𝐚𝐥 𝐥𝐞𝐚𝐝𝐞𝐫 𝐢𝐧 𝐫𝐞𝐝 𝐜𝐡𝐢𝐥𝐥𝐢 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧, 𝐜𝐨𝐧𝐭𝐫𝐢𝐛𝐮𝐭𝐞𝐬 𝐨𝐯𝐞𝐫 𝟒𝟎% 𝐨𝐟 𝐠𝐥𝐨𝐛𝐚𝐥 𝐞𝐱𝐩𝐨𝐫𝐭𝐬. However, traditional farming practices have often limited this potential. High input costs, pest infestations, and chemical residue issues in exports have historically posed significant challenges for farmers. The integration of Artificial Intelligence (AI) into agriculture is now transforming this scenario, creating success stories across the nation and revolutionizing farming practices. 𝐆𝐮𝐧𝐭𝐮𝐫, 𝐀𝐧𝐝𝐡𝐫𝐚 𝐏𝐫𝐚𝐝𝐞𝐬𝐡, famously known as the Chilli Capital of India, has emerged as a shining example of AI-powered precision farming. By leveraging satellite-based soil monitoring and automated irrigation systems, farmers in this region are achieving remarkable results. Production has surged by 25%, meeting both domestic and export demands. Simultaneously, pesticide usage has reduced by 40%, ensuring the produce is residue-free and compliant with international standards. This shift has opened up lucrative export opportunities, particularly in premium markets across Europe and the Middle East, significantly boosting farmers’ incomes. In Punjab, a state renowned for its wheat and paddy cultivation, AI tools are being seamlessly integrated into traditional agricultural practices. Farmers here are utilizing satellite imagery and real-time analytics to revolutionize water and disease management. AI-driven irrigation systems have reduced water consumption by 35%, addressing the critical challenge of groundwater depletion in the region. Additionally, during a recent yellow rust outbreak, AI-enabled early detection systems helped prevent a 10% yield loss, saving farmers from significant economic losses. Similarly, Karnataka's Belgaum district is embracing AI for effective crop disease management. Farmers are using computer vision technology to detect leaf blight in tomato and chilli crops with an impressive 96% accuracy. The Indian government is playing a pivotal role in facilitating AI adoption through initiatives under the Digital Agriculture Mission. Farmers can avail themselves of subsidies for drones, sensors, and other AI-based devices through the 𝐏𝐌-𝐊𝐈𝐒𝐀𝐍 𝐬𝐜𝐡𝐞𝐦𝐞. Furthermore, the Indian Council of Agricultural Research (ICAR) conducts 𝐰𝐨𝐫𝐤𝐬𝐡𝐨𝐩𝐬 𝐭𝐨 𝐭𝐫𝐚𝐢𝐧 𝐟𝐚𝐫𝐦𝐞𝐫𝐬 in the practical use of AI tools, ensuring that even small-scale farmers benefit from these technological advancements. AI is effectively addressing some of the most pressing challenges in traditional farming. With the pesticide application, it minimizes chemical residues, making Indian produce export-ready. Weather analytics powered by AI predict rainfall and temperature changes, allowing farmers to adapt and mitigate risks proactively. AI adoption has led to a 20–30% reduction in overall input costs, improving farmers' profitability and financial resilience.

"This paper presents novel empirical evidence on AI development and its environmental implications in 23 middle and high-income countries, confirming that, initially, in the majority of countries AI increases energy consumption and CO2 emissions. However, we also show that these relationships are not linear, since, over time, AI has a positive impact on the environment in terms of emission reduction and higher reliance on renewable energies, a kind of Green AI Kuznets curve. This reversal in the trend is achieved from $220-$580 AI market per capita. As of today, AI leading countries, such as Singapore and the US, are already benefitting from this technological dividend. These results have clear policy implications, calling for a less fragmented global AI and energy governance, national AI strategies, innovations in financing to mobilize additional funds towards greener AI adoption, while achieving more transparency and standards for measuring and reporting its use of energy " Angel Melguizo, TIDE Centre, University of Oxford Raul Katz, Columbia Institute for Tele-Information, Juan Jung