📈 📉 💹 Want to know where the #price of wheat is going to be in the next few weeks? Read our latest analysis to find out! #ai #genai #wheat #commoditytrading #commodities #trading
Check out this week's blog to understand "Where in the world is #wheat going?" We're doing a deep dive on the what's been driving the price increases and where it's going to go! #commoditytrading #genai #ai https://lnkd.in/eWXEUFNq
Check out this week's blog to understand "Where in the world is #wheat going?" We're doing a deep dive on the what's been driving the price increases and where it's going to go! #commoditytrading #genai #ai https://lnkd.in/eWXEUFNq
Interpretability in healthcare AI is a delicate area to work in, as it’s all too easy to draw the wrong conclusions using contemporary explainable AI (XAI) methods. This highly readable book chapter by Christoph Molnar is one of the best treatments I’ve read about the complexities of this space. He discusses how XAI is typically used to justify or debug models, and to discover new knowledge, and how these goals are subject to significant limitations. One of these is the Rashomon effect, which poses several questions: (1) When you have multiple models with different structures that have similar prediction performance, how do you decide which one to trust from an XAI perspective? And (2) can/should you trust any of them? These questions have particular significance in the healthcare AI domain, when explaining how models work to clinical stakeholders and end users. https://lnkd.in/em9Fmyi7 #ai #ml #bigdata #datascience #machinelearning #healthcare These views are my own, and do not reflect the views of IQVIA. #IWork4IQVIA
AGRO COMMODITY
🚀 🚀 EXPANSION DAY! Today we launched the expansion of our #CommodiTrack #AI platform to over 58 #agricultural #commodities! Check out how #fruits and #vegetables are doing globally - and where the next price increase will come from!
We're excited to launch the EXPANSION of our #CommodiTrack #AI platform to 58 #commodities! Our customers now have access to the most comprehensive platform in the world to predict #agricultural commodity prices! https://lnkd.in/eUESkaCr
Lights, camera, action! Introducing Source Cultivate, the all-in-one AI solution built for precise harvest predictions. How does it work? Find out in the video below 🍿 Watch here: https://lnkd.in/eztf_Fpp #Horticulture #AI #GreenhouseInnovation
Let's make veggies cool again, and let's root for the people that make them. A diet of more fruit and vegetables is better for the planet, and better for our health. To get there, we need to make the growers successful that work tirelessly to produce them for us. But, even though they often work 7 days per week, waking up every morning at the crack of dawn to grow these veggies for us, they often only get a fraction of the price you pay in the supermarket. This is for a large part driven by the extreme uncertainty of production volumes, and the need to sell volumes within a few days as it's a perishable fresh product. That means growers often find themselves with their back against the wall. Let's change that. Let's give growers more certainty about the future. Let's give the reigns back to growers. Let's make growers successful so they can invest in new technologies to adapt to climate change, so they can invest in new sustainability technologies, so they can invest in growing more healthy fruit and veggies for more people. Launching Source Cultivate. Real world AI, solving real world problems. https://lnkd.in/eX7JYy3E
Lights, camera, action! Introducing Source Cultivate, the all-in-one AI solution built for precise harvest predictions. How does it work? Find out in the video below 🍿 Watch here: https://lnkd.in/eztf_Fpp #Horticulture #AI #GreenhouseInnovation
I am thrilled to share my recent article in the prestigious journal #Paddy and Water Environment. (Springer, IF:2.2)# 🌾 ☘ Titled : “Prediction of pulse suitability in rice fallow areas using fuzzy AHP‑based machine learning methods in Eastern India” ☘ - 🔌 Objective: we tried to detect pulse appropriateness geographically and temporally while considering fifteen natural, climatic, environment, and soil health-related characteristics in the Western Lateritic Zone of the Indian State of West Bengal through the different Artificial Intelligence (AI) techniques. 🕸 For those interested in exploring this research, the entire workflow is documented and available on Weblink: https://lnkd.in/dcB_vFvB #Rice fallow areas# Pulse suitability # Fuzzy-AHP # Machine learning#
This week, I talked more about fertiliser with Eddy Fay and, in the process, learned more about the power of AI.
We used to do it with just a threshold of shade. Now we can do it more accurately with AI. However, the cost of using AI is higher. So, we have to see if low cost conventional techniques are good enough before exploring AI options.
Explore our Fruit Quality Detection System using Artificial Intelligence! Revolutionize your fruit inspection process with advanced technology. Discover more about its features and benefits: https://lnkd.in/dXBJRYQ8 Enhance accuracy and efficiency in fruit quality assessment! #AI #FruitQuality #Innovation #TechnologyAdvancement
