Teddy Bekele’s Post

With the latest updates to Azure Data Manager for Agriculture, generative AI in agriculture is now a reality. The capabilities enable farmers with interactive, intuitive and human-centric insights that can accurately answer common questions like “which fields had rain last night?” or “how many acres have been harvested?”   We're already putting this in motion in partnership with Bayer, who is using AI to support sustainable agriculture and food production. In its early stages, Bayer is presenting an agriculture copilot and testing multiple scenarios with internal teams to discover where large language model (LLM) capabilities can add value to the company's operations.

Here’s a customer story that’s using data science to deliver regenerative agriculture! By leveraging Google Cloud’s machine learning operation tools, Regrow Ag found a solution to operate at scale without worrying about complexity: goo.gle/3Pp0gax

Here’s a customer story that’s using data science to deliver regenerative agriculture! By leveraging Google Cloud’s machine learning operation tools, Regrow Ag found a solution to operate at scale without worrying about complexity: goo.gle/3Pp0gax

Last week, I had the privilege of joining forces with Guus van Heijningen from PEAX Data, a vibrant startup within the Microsoft for Startup Foundation Hub. Together, we ignited the spark of AI in a group of young entrepreneurs linked to Royal FloraHolland. It was more than an evening discussing AI; it was an exploration of the transformative power of (generative) AI for agriculture and how we can empower farmers to reach new heights. Thank you Royal Flora Holland and especially Michiel Beemster for having us. The data landscape in agriculture is vast and growing, brimming with untapped potential for predictive AI insights. Yet, the challenge lies in unifying this data and transforming it into actionable insights that drive progress. Microsoft Azure Data Manager for Agriculture is the key to unlocking this potential, offering agriculture-specific data connectors and capabilities that seamlessly integrate farm data from diverse sources. Imagine a world where high-quality datasets accelerate the development of digital agriculture solutions that not only analyze market demand and forecast prices but also optimize farming practices, monitor weather, and so much more. Azure Data Manager for Agriculture is not just a tool; it's a gateway to a future where digital solutions and AI coalesce to create a resilient and efficient agricultural sector. AI solutions are reshaping the agricultural landscape, like Copilot for Agri empowered with GPT4 which are partners in innovation, enabling conversations with data in natural language and extending the capabilities of your data platform with even more sources. Take, for example, the Planetary Computer, a treasure trove of Earth system data hosted on Azure, accessible via web portal or API. Or the Aurora model by Microsoft Research, a groundbreaking foundation model of the atmosphere that offers accurate predictions with reduced computational costs. These are the innovations that pave the way for a more informed and precise approach to weather and climate forecasting. But the journey to digital transformation begins at home. Start by harnessing the data already available at your farm or greenhouse and within your supply chain. Embrace the tech intensity that we champion at Microsoft. Be an early adopter of digital technology and build your unique digital capabilities. This is how you become a leader in the digital agriculture revolution. Join us on this journey. Together, we can cultivate a future where technology and agriculture grow hand in hand, fostering a world that is more sustainable, efficient, and ready for the challenges ahead. Read more about: > Azure Data Manager for Agriculture: https://lnkd.in/eEXjPj5M > Copilot for Agriculture: https://lnkd.in/eJFaVFyP > Planetary Computer: https://lnkd.in/e6p_vbVF

Here’s a customer story that’s using data science to deliver regenerative agriculture! By leveraging Google Cloud’s machine learning operation tools, Regrow Ag found a solution to operate at scale without worrying about complexity: goo.gle/3Pp0gax

This is some of the most significant work that Microsoft is working on, led by the amazing (and good friend) Ranveer Chandra. Agri has traditionally been an analog industry. If you go back one or two generations, decisions at the farm level were made by instinct or through tribal knowledge. Today, we are partnering with some fantastic organizations to digitally transform farms to revolutionize their ability to plan, manage, and extract value out of data. Read below for more information... #MSFTAdvocate

Per The Wall Street Journal, a decade after data analytics promised to revolutionize agriculture, most farmers still aren’t using data tools or specialized software, and of those who do, many are swamped by a deluge of data. Based on a McKinsey survey, less than half of farmers are using farm management software and 25% are using remote-sensing and precision agriculture hardware. Only 3% of American farmers said they plan to adopt software or precision agriculture hardware over the next two years. There are many different players in the agriculture industry that now have a wide range of digital capabilities, equipment providers, drone applications, different dealers and suppliers. Capturing data, and sharing it across multiple platforms, can be difficult and daunting. Bayer acquire Monsanto in 2018, including Climate Corporation’s FieldView farm software. In June, they announced an update to their partnership with Microsoft that links data sources within Microsoft’s Azure cloud platform. This is one of the first major tie-ups between an agri-business and a cloud provider to tackle agriculture’s data integration problems. Amazon and Google are also looking to gain a foothold in the sector. In March, Amazon Web Services (AWS) joined with Agtech startup Leaf, which provides connectors between data sources in different formats. AWS also works with John Deere, providing cloud services for the machinery manufacturer’s data services. In 2022, Google Cloud joined with climate-tech startup Agrology to help predict farm microclimates and process data. In January, its parent Alphabet spun off a company called Mineral to aggregate agricultural data and apply AI to it. AI could become a key technology to tackle numerous agriculture industry challenges. MOSIMTEC specializes in simulation modeling to build digital twins, which requires clean, accurate, and near-real-time data. We help our clients manage/enhance data sources, quality, availability, data integration, and governance to improve decision-making and support their digital strategy. Projects typically focus almost half of the time on data-related issues to ensure needed data quality and integrity. We help companies avoid common data-related pitfalls based on our work in the trenches of >300 projects. We work with big data every day and know how to make it work for you. MOSIMTEC data scientists and industrial engineers can help future-proof your business. #farming #dataanalytics #WSJ #futureproofyourbusiness  

Really proud of what we built this last year at Bountiful. Truly a product born out of necessity for farmers. Attempting to put into practice what Y Combinator tells startups: get product out to your customers quickly, talk to them and iterate. Good is better than perfect. And sometimes, do things that don't scale. Paul Graham's blog on that is a gold mine. Counterintuitively, this process helps you identify the best way to scale and build for the future.