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Email Verification
Agenda 2024
TBC
0830 - 0930 REGISTRATION AND MORNING REFRESHMENTS
0930 - 0940 OPENING ADDRESS
0940 - 1005 AI's ROLE IN SCALING MODERN AGRICULTURE TECHNOLOGY ACROSS RURAL FARMING GLOBALLY
- Utilizing precision agriculture and generative AI for optimized and efficient farming practices
- Enhancing supply chain efficiency and market access through AI-powered solutions
- Empowering rural farmers with AI education and tools to increase accessibility and productivity
Tyler Marshall
EYC Labs
EYC Labs
1005 - 1010 Q&A SESSION ON AI's ROLE IN RURAL FARMING AND AGRICULTURE TECHNOLOGY
1010 - 1030 SPEED NETWORKING SESSION
- Exchange business cards and get connected in short one-to-one meetings
- Start the conversation to arrange a more formal meeting later on in the conference
- Share your professional background and discuss your biggest business issues – don't forget your business cards!
Conference Host
1030 - 1100 MORNING COFFEE BREAK IN THE EXHIBIT AREA
1100 - 1125 IN-SEASON CROP MANAGEMENT AND EARLY-SEASON YIELD FORECASTS USING A DIGITAL TWIN-BASED PLATFORM
- Utilizing high-resolution UAS imagery to create Digital Twin models for crop management
- Weekly updates on Digital Twin models for canopy cover, plant height, canopy volume, and vegetative indexes
- Employing Artificial Intelligence algorithms for accurate cotton lint yield predictions
Juan Landivar
Texas A&M University
Texas A&M University
1125 - 1130 Q&A SESSION ON CROP MANAGEMENT AND YIELD FORECASTS USING DIGITAL TWINS
1130 - 1155 BUILDING THE FUTURE OF AG AI WITH ON-FARM DATA AND GEOSPATIAL MODELLING
- Harnessing broad sensing technology for comprehensive on-farm data collection
- Using ML/AI scenarios in INNOVA to enhance sustainability and product solutions
- Driving agricultural innovation through advanced geospatial modeling techniques
Randall Barker
INTENT
INTENT
1155 - 1200 Q&A SESSION ON THE FUTURE OF AG AI WITH DATA AND MODELLING
1200 - 1330 NETWORKING LUNCH & VISITING THE AGRI AI SUMMIT EXHIBITION
1330 - 1355 SATELLITE IMAGERY AND MACHINE LEARNING FOR DATA-DRIVEN EVIDENCE-BASED DECISION-MAKING IN SMALLHOLDER AGRICULTURE
- Addressing agricultural differences and climate transition challenges to ensure food and water security
- Highlighting advances in remote sensing and machine learning technologies
- Showcasing case studies on building national-scale agricultural understanding for resource allocation
Alok Talekar
Google
1355 - 1400 Q&A SESSION ON AI AND SATELLITE IMAGERY FOR AGRICULTURE
1400 - 1425 ENHANCING GROWER DECISION-MAKING WITH AI: INNOVATIONS AND INSIGHTS
- Overview of AI integration in agriculture and its key technologies
- Benefits of AI including yield increase, resource optimization, and risk management
- Challenges, solutions, and future trends in agricultural AI adoption
Jeremy Groeteke
Syngenta Group
Syngenta Group
1425 - 1430 Q&A SESSION ON AI SOLUTIONS FOR GROWERS
1430 - 1455 USING EARTH OBSERVATION (EO) AND AI FOR SUSTAINABLE REGULATORY MONITORING IN AGRICULTURE
- Woolpert uses EO and AI to monitor and promote sustainable agricultural practices
- Evaluating compliance with agricultural standards using innovative applications
- Monitoring crop areas to provide accurate data for tax assessments and incentives
Biplov Bhandari
Woolpert
Woolpert
1455 - 1500 Q&A SESSION ON USING EO AND AI IN AGRICULTURE MONITORING
1500 - 1530 AFTERNOON COFFEE BREAK IN THE EXHIBIT AREA
1530 - 1555 LEAF-LEVEL INSIGHTS AND BEYOND: THE FUTURE OF MULTIMODAL AND GENAI IN CROP MANAGEMENT
- Utilizing AI to tackle the primary challenges in agricultural retail today
- Understanding the significance of leaf-level insights for crop health and productivity
- Exploring the present and future roles of large language models in Agricultural AI
Jason Minton
Taranis
Taranis
1555 - 1600 Q&A SESSION ON THE FUTURE OF AI IN CROP MANAGEMENT
1600 - 1625 AI TECHNIQUES TO PEST AND DISEASE IN AGRICULTURE
- Leveraging machine learning to address and manage highly imbalanced agricultural datasets
- Efficient data cleaning techniques for large-scale labeled datasets in agricultural contexts
- Scalable inference methods for high-efficiency pest and disease detection using remote sensing and drones
Achyut Boggaram
Torc Robotics
Torc Robotics
1625 - 1630 Q&A SESSION ON SCALABLE AI SOLUTIONS FOR AGRICULTURE
1630 - 1700 RESERVED PRESENTATION
1700 - 1800 NETWORKING DRINKS RECEPTION
TBC
0900 - 0930 MORNING REFRESHMENTS
0930 - 0940 OPENING ADDRESS
0940 - 1005 USING AI TO DELIVER A "CAMPAIGN OF ONE" IN AGRI-INPUT MARKETING
- Discover how AI and customer data can create highly targeted, dynamic marketing campaigns
- Learn AI-driven methods to enhance sales and engagement with timely, personalized communications
- Explore a case study on AI and data-driven personalized marketing in agriculture
Preston Fay
The Context Network
The Context Network
1005 - 1010 Q&A SESSION ON AI-DRIVEN AGRI-INPUT MARKETING STRATEGIES
1010 - 1035 LEVERAGING AI FOR STRATEGIC MATERIAL SOURCING
- Utilizing AI-powered tools to streamline training and onboarding processes for new growers and partners
- Leveraging AI-generated insights to guide strategic conversations about sourcing raw materials
- Enhancing sourcing efficiency and quality standards while adapting to market dynamics using AI
Ruohan Liu
PepsiCo
PepsiCo
1035 - 1040 Q&A SESSION ON AI-ENABLED MATERIAL SOURCING
1040 - 1105 HOW AGRICULTURAL RETAILERS SEE AI AND AUTOMATION IMPACTING THEIR BUSINESS
- Results from the 2024 survey showcasing the current and future adoption trends
- Retailers' perspectives on labor, costs, and agronomic expertise with new technologies
- Strategies for educating workers and customers to leverage information-intensive skills
Bruce Erickson
Purdue University
Purdue University
1105 - 1110 Q&A SESSION ON AI AND AUTOMATION IN AGRICULTURAL RETAILING
1110 - 1130 MORNING COFFEE BREAK IN THE EXHIBIT AREA
1130 - 1155 AI FOR SMALLHOLDER FARMERS
- Exploring how Generative AI can transform the lives of rural farmers in low and middle-income countries
- Understanding the potential benefits of AI in addressing information asymmetries and advancing research
- Examining the risks related to exclusion, bias, transparency, and misuse, especially for marginalized populations
Stewart Collis
Bill & Melinda Gates Foundation
Bill & Melinda Gates Foundation
1155 - 1200 Q&A SESSION ON AI BENEFITS AND RISKS FOR FARMERS
1200 - 1225 REVOLUTIONIZING LIVESTOCK MANAGEMENT WITH LORE: AN AI-DRIVEN SOLUTION FOR SMART AGRICULTURE
- Introducing LORE, an advanced AI for comprehensive livestock management
- Enhancing farm management capabilities with Artificial Intelligence
- Applying LORE for digital monitoring and user-friendly farm tracking
Ana Gomes
dsm-firmenich
dsm-firmenich
1225 - 1230 Q&A SESSION ON AI-DRIVEN LIVESTOCK MANAGEMENT WITH LORE
1230 - 1255 CURRENT ACCEPTANCE AND ADOPTION OF AI IN DUTCH AGRIBUSINESS: ASSESSING AI READINESS
- Presenting insights from MBA research on AI acceptance and adoption in Dutch agriculture
- Enhancing AI readiness through data management, technology integration, and talent development
- Assisting leading companies in future adaptation and implementation across the value chain
Cynthia Zhu
Agri-AI
Agri-AI
1255 - 1300 Q&A SESSION ON THE FUTURE OF AI IN DUTCH AGRICULTURE AND READINESS ADOPTION
1300 - 1315 FEEDBACK & RAFFLE DRAW
1315 - 1430 NETWORKING LUNCH
Key topics for 2024:
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Future trends in AI adoption for agriculture
Explore how AI is transforming the agricultural market, reshaping farming, and ensuring food security -
AI advancements for data collection and livestock monitoring
Discussing AI's role in modern farming for data-driven decisions, cost savings through precision agriculture, and mitigating labor shortages with automation -
Latest research on data-driven strategies and smart agriculture
Learn how agricultural data and IoT technologies enhance risk management, crop health, fertilization, and harvesting -
AI tools that revolutionize and optimize traditional farming
Leverage AI for remote livestock management, smart pesticide use, precise irrigation, crop and soil monitoring, and disease detection -
Supportive policies and regulations to promote AI in agriculture
Collaborating with industry leaders to navigate policy pathways towards sustainable, healthy, and equitable urban communities -
Case studies on AI-driven solutions digitizing agricultural processes
Scale AI-driven, sustainable farming practices through smart Agri AI systems
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