ASH CLOUD

Artificial intelligence is advancing at an astonishing pace—improvements measured in five-thousand-fold increases from week to week according to AI researchers at Singularity University. Yet in agriculture, most farmers remain largely disconnected from these advances, using AI only at the most basic level for administrative tasks like finance, report writing, and form filling. This widening gap threatens to leave the agricultural sector further and further behind as the world accelerates into what might be called the "bullet train moment" of AI adoption.
Today we are joined by Aidan Connolly, CEO of Agritech Capital, who has spent the past years advising agricultural organizations on AI readiness.  Aidan joins Ash Cloud to discuss how to restructure agricultural businesses for AI-driven decision-making without waiting for others to lead the way.
The big challenge is that AI systems can only work with the data available to them. In agriculture, that data is fundamentally flawed. Most farm information is still captured by humans in notebooks, then transcribed into databases. Each step introduces errors, misinterpretation, and gaps that make datasets unsuitable for the sophisticated decision-making AI promises to deliver. Meanwhile, the major AI companies racing forward at incomprehensible speeds won't wait for agriculture to catch up.
When you consider that farmers are constantly gathering sensory information through sight, sound, and observation while working in the field, data that never enters any database, the informational chasm becomes even more apparent. Yet animal production systems offer unique opportunities. Dairy cows milked three times daily provide recurring windows to assess milk quality, animal health, fertility, and nutrition. Hens laying eggs daily, pigs weighed multiple times, animals with collars and sensors, these continuous data streams contain vastly more untapped value than the sector has realized.

 

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“I’m yet to meet a grazier that doesn’t want a 5-15% feed conversation ratio improvement.” says Tom Williams, CEO of Number 8 Bio. 
Producers motivated by not losing 10% of their feed to the atmosphere.
Enteric methane from livestock represents one of the rare climate challenges where environmental impact aligns with economic opportunity. Methane is a potent greenhouse gas and  it also represents wasted nutrition. Approximately 10% of feed energy consumed by ruminants escapes as methane rather than supporting growth or milk production. Few climate solutions offer both emissions reduction and immediate productivity gains for those implementing them.

But here's the challenge: the rumen contains billions of microorganisms competing, collaborating, and interacting across complex metabolic pathways. Human knowledge of this biological complexity remains incomplete. Finding molecules that reduce methane without compromising animal health or performance requires casting an extraordinarily wide net.
Today we are joined by Tom Williams, founder and CEO of Number 8 Bio, a synthetic biology company developing feed additives to reduce enteric methane emissions. 
Number 8 Bio's journey demonstrates rapid adaptation to scientific reality. Initially engineering yeast to produce bromoform and seaweed molecules, the team quickly recognized cost barriers for feed additive markets. They pivoted entirely, developing an automated in vitro rumen screening system processing approximately 100 tests weekly. Over several years, they screened thousands of potential products—peptides, enzymes, probiotics, natural extracts, small molecules, and combinations—seeking winners through systematic trial rather than theoretical prediction.
The company now focuses on a single organic molecule showing methane reductions and productivity improvements in grazing systems. Initial feedlot trials revealed hydrogen buildup and intake reductions, so Williams followed the science toward pasture-based applications first. The discovery platform—now enhanced with bioreactors predicting live animal productivity outcomes—positions Number 8 Bio to develop additional molecules for different markets and stacking strategies as regulatory pathways allow.
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The green revolution resulted in unprecedented improvements in the efficiency and productivity of food production. Recent decades of increasingly globalized free trade has further imporved efficiecies across the supply chain. These improvements that have benefited millions have done so largely at the expense of resiliance and the shock waves of this vulnerability are starting to be felt as fertilizer and energy prices rise.  
Today I am joined by Bram Govaerts, Director General of the International Maize and Wheat Improvement Center (CIMMYT), to his efforts to build resilient agrifood systems across conflict zones and climate-stressed regions.
Seventy percent of food consumed in the Gulf states of Bahrain, Kuwait, Qatar, UAE, Saudi Arabia, and Iraq, flows through the Strait of Hormuz. Twenty percent of global nitrogen-based fertilizer exports through this same chokepoint. For decades, global food systems have been optimized for efficiency. Nitrogen fertilizer plants positioned beside oil fields and shipped on demand. This efficiency created abundance and affordability, but at a cost. 
But here's the challenge: we have become victims of our own success. Pursuit of efficiency without resilience has created dangerous choke points in systems we depend upon for survival. 
Food system fragility is never just about production disruptions. In Sudan, fertile soils along the Nile could feed the Gulf region, yet conflict has collapsed production systems that previously supplied the area. Across the globe, 60% of countries most affected by climate change also face armed conflict. Food insecurity drives migration and instability that compound the original crisis.
CIMMYT's approach operates across three pillars: discovery, system development, and humanitarian response. Current research on biological nitrification inhibition could enable crops to utilize nitrogen fertilizer 30% more efficiently. In conflict zones like Sudan, CIMMYT works alongside internally displaced communities to maintain food production even during active warfare, embedding drought-tolerant seeds and recovery mechanisms directly into humanitarian interventions to reduce the traditional seven-year post-conflict rebuilding timeline.
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The journey toward sustainable beef production in the United States began before the term "sustainability" entered common usage. 
Today we are joined by Steve Wooten, a rancher in southeastern Colorado's shortgrass prairie and a founding member of the U.S. Roundtable for Sustainable Beef. Wooten manages Beatty Canyon Ranch in a region receiving 11-14 inches of annual rainfall, where the same perennial grass species documented in Native American archaeological sites continue thriving today under rotational grazing systems.
Steve approach to grazing and sustainability changed when he met Alan Savory and learned of his work on holistic management.
Eleven years ago, the National Cattlemen's Beef Association established the U.S. Roundtable for Sustainable Beef, bringing together the entire beef supply chain—from cow-calf producers through feedlots, packers, processors, and retailers—alongside civil society organizations and universities. This unprecedented collaboration addressed a critical reality. Only 85% of the nation's cows currently brings a calf to weaning. No major corporation would accept a 15% efficiency loss before year-end, yet the beef industry has operated at this level while simultaneously wrestling with climate concerns and supply chain pressures. 
Steve's approach integrates multiple data streams, Agriwebb and Pasture Map for grazing tracking, Enriched Ag camera systems capturing images every six seconds for vegetation analysis, and soil carbon sampling. His drought management plan includes trigger dates in March, June, and October for adjusting stocking rates, early weaning protocols, and strategic culling based on meteorological projections. The ranch maintains ungrazed pastures as drought mitigation, ensuring forage reserves for subsequent years while varying grazing timing to provide near-full growing season rest between grazing events—defined in his environment as March through October.
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Feed efficiency remains one of the biggest gray areas and least understood aspects of livestock production. Yet understanding how much grass a cow consumes to produce a calf or a ewe to produce a lamb is critical not only to farmer and ranch profitability, but also to the sustainability of the industry. At 19 cents per kilogram to grow dry matter, inefficiency compounds rapidly. The difference between efficient and inefficient animals can determine whether operations generate profit or struggle to cover overhead costs.

Today we are joined by Andrew Freshwater, who has spent over 30 years using data to drive efficient breeding decisions across his sheep and cattle production enterprises in northeastern Victoria. Freshwater's family brought Angus cattle and Romney sheep to Australia in 1849, establishing a multi-generational commitment to livestock genetics.
Recent heifer trials demonstrated dramatic efficiency differences between groups run as contemporary cohorts. Through Zoetis genomic testing, Freshwater documented that genetically inferior heifers showed poor feed conversion efficiency and marginal annual returns, while superior genetics in the same management system generated excellent profitability. The lesson is clear: breeding animals is neither pure art nor pure science, but rather a data-informed approach that acknowledges biological complexity while leveraging technology—from genomics to artificial intelligence—to optimize resource utilization across diverse farming systems.

Beginning performance recording in 1989 as a teenager, Freshwater has accumulated over 80,000 sheep records representing approximately 3.5 million data points through long-term progeny testing programs. Rather than relying on static estimated breeding values, he has developed proprietary software that runs Monte Carlo simulations incorporating local climate data, grass types, and historical weather patterns to identify the most profitable animals for specific environmental conditions and management systems.

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