InnerPlant’s Post

Leveraging AI for Ecological Sustainability: An Emerging Business Imperative 🌱🤖 In the professional community, there's a growing conversation about the role of AI in driving ecological sustainability. As someone passionate about both technology and the environment, we find this intersection incredibly promising. AI's capability to analyze vast data sets can help businesses make more environmentally sound decisions. It's not just about compliance anymore; it's about leading the way in sustainable practices. From supply chain optimization to reducing carbon footprints, the applications are vast. But what's truly exciting is the innovation potential. Startups and established companies alike are finding unique ways to integrate AI into ecological efforts, creating not only environmental impact but also new business opportunities. As professionals, how do we see AI shaping our approach to sustainability? What are the challenges and opportunities? Let's connect and discuss how we can be part of this positive change. #ai #sustainability #businessinnovation #ecology

Empowering farmers with technology. #AI gives farmers the tools they need to overcome challenges and create a more sustainable and profitable future for their communities. #FarmerEmpowerment #AgInnovation #FutureOfFarming

Excited to share some of the AI use cases we’ve been exploring for measuring the societal impacts of spending on products and services for global brands. Not a definitive list but 12 to get things started: • Supply chain analysis: AI can dissect complex global supply chains to pinpoint social and environmental impacts at every stage. • Carbon footprint calculation: AI models accurately calculate the carbon footprint of products across their lifecycle. • Social impact assessment: AI gauges public sentiment and measures the social impact of a brand’s initiatives by analyzing social media data and news. • Sustainable product development: AI optimizes materials, manufacturing, and packaging to create more sustainable products. • Ethical sourcing verification: AI-powered systems ensure compliance with labor standards and fair trade practices throughout the supply chain. • Consumer behavior analysis: AI interprets purchasing patterns to align product offerings with consumer values. • Impact reporting and transparency: AI automates impact data collection and analysis, producing comprehensive performance reports. • Predictive modeling: AI forecasts the long-term societal impacts of product launches and marketing campaigns. • Waste reduction optimization: AI identifies opportunities for reducing waste and enhancing resource efficiency. • Personalized sustainability recommendations: AI offers tailored advice on using products more sustainably or choosing eco-friendly alternatives. • Community impact assessment: AI evaluates the impact of a brand’s presence on local economies and social indicators. • Biodiversity impact analysis: AI processes ecological data to assess the effects of sourcing practices on local ecosystems. By leveraging these AI applications, global brands can gain deeper insights into the societal impacts of their products and services, enabling them to make more informed decisions and demonstrate their commitment to sustainability and social responsibility. #AI #Sustainability #SocialImpact #SupplyChain #CarbonFootprint #EthicalSourcing #ConsumerBehavior #ImpactReporting #PredictiveModeling #WasteReduction #CommunityImpact #Biodiversity #GlobalBrands #TechForGood #Innovation #EnvironmentalImpact #SustainableDevelopment

We’re still glowing over the fact that TIME Magazine named us as one of America’s Top GreenTech Companies! Statista and Time analyzed 4,600 companies to find 250 companies making the biggest impact in sustainability and innovation. Learn more in our press release: https://lnkd.in/e_dV49gt #ai #deeplearning #govtech #sustainabilitytech #greentech #greentechnology #publictransit #publictransportation #computervision #visionai

The environmental impacts of AI definitely give me pause. I’ve seen a viral image indicating each email written equates to a bottle of water. That kind of helpful visualization will certainly influence my usage a bit. At the same time, it seems we have a huge opportunity in front of us to bring the popularity of ESGs to bear on AI and, in our decisions around which platforms we decide to use, prioritize sustainability as a key factor. How are you accounting for the environmental impact of you AI use? What would you like to see companies do? Does this factor into your decision making at all? https://lnkd.in/eq3DtTza

Growing New Business Model(s) Along Side Emerging Technology, And More… [ref: https://lnkd.in/gFx4g2ns ] This article, among other things is about What a “Collapse of Traditional Structures: An Ecosystem Evolution” looks like in the real world[1]. Question(s) to Learn, Not Questioning to Challenge℠ ∞ 1. How “stable” can #ExtractionAge oligopolistic business and other administrative model(s)—not to mention 1) those deemed too big to fail in agriculture[2]—including its Financial, Logistical, Analytical, Biological, Social monoculture commodity-based administering bodies 2) the many cloud-based tech companies—e.g.: #ClimateTech (#AgTech, #AgriFoodTech, #FarmTech, #FoodTech,etc.)—seen, among other things, seeking to prop up crumbling #EcosystemAge industrial sectors as their markets evaporate 3) within the broader context of seeing similar #ExtinctionBurst collapse patterns across a wider range of other human endeavors[3], (and more…)—be as their double down on their follow-the-leader strategy of throwing more money and resources at a problem fails? ∞ 2. Does anyone really think all the cash pouring into #LabGrownMeats, #InsectsReplacingMeat, #RegenerativeAgriculture has any chance of any meaningful return—with #OnDeviceGenernativeAi and other #EcosystemAge technologies* now in the hands of people not seeking to continue the #ExtractionAge’s drama and destruction cycle(s), but instead seek to optimize what Nature has already perfected?   * The inducing near zero marginal cost(s) thinking, deciding and acting now seen happening across a broad number of human endeavors[3] and are how they are influencing physical world outcomes. This leaves the ready with one simple question: ∞ 3. Do we really what to make anything Nature can deliver for free? Cumulative Impact Focal Point Item(s): #SpatialComputing ∞ #Trustworthiness ∞ #GenerativeAI: Is there a better metaphysical combination(s) capable of reshaping physical world outcomes available today[4, 5, 6, 6a]? A Natural Confluence Where does it make sense/cents for you to spend your time, talent and resources? ∞ A. In a crumbling lead-with-leveraging empire with friction heavy across-the-board administrative taxes[7]? or consider alternative? ∞ B. The Soils as Health™ Consumer Centric Conversation: Inviting those in agriculture, food, and healthcare—and other communities—into the same conversation, and more….[8]. Need more? How well does your current business model’ communications ∞ connections ∞ coordinations resemble The Three Sister’s Ecosystem[6, 9]? [1 of 4]

The economic impact of AI depends on two factors: First, whether AI addresses productivity bottlenecks in the economy. If AI can increase productivity in areas with current bottlenecks, such as healthcare or transportation, its impact will be significant. Second, the level at which AI can perform cognitive tasks compared to humans is crucial. If AI only marginally outperforms humans, it may replace human labor without significant productivity gains. However, if AI dramatically outperforms humans, it could lead to substantial economic growth and improved living standards, even if it replaces many human jobs... Decoding AI's Economic Revolution: Two Key Factors #AIEconomicImpact #ProductivityRevolution #AIinBusiness #FutureOfWork #AIandEconomy https://lnkd.in/dpEMgVZ9

I'm incredibly proud to be working at a company that TIME Magazine named as one of America’s Top GreenTech Companies! Clearing bus stops and bus lanes makes a difference for everyone! Learn more in our press release: https://lnkd.in/e_dV49gt #ai #deeplearning #govtech #sustainabilitytech #greentech #greentechnology #publictransit #publictransportation #computervision #visionai

I just asked AI the following question; “Plastic and coal were considered terrific innovations when they were found, however decades later we are seeing the adversarial impact of these innovations. Perhaps they were great innovations but how we chose to use, and the extent we leveraged it, caused a negative impact to our environment. How can humans become better in identifying and mitigating the adversarial impacta of innovation?” AI Response: Humans can become better in identifying and mitigating the adversarial impacts of innovation by adopting the following approaches: 1. Education and awareness: Increasing knowledge and understanding about the potential risks and consequences of new innovations is crucial. By educating ourselves and raising awareness about the environmental and social impacts of new technologies, we can make more informed decisions. 2. Ethical considerations: Incorporating ethical considerations into the development and implementation of new innovations is essential. This includes considering the potential environmental, social, and economic impacts of an innovation before it is widely adopted. 3. Sustainable practices: Embracing sustainable practices is key to mitigating the adverse impacts of innovation. This includes adopting technologies and practices that minimize resource consumption, reduce waste generation, and promote environmental conservation. 4. Collaboration and dialogue: Encouraging collaboration and dialogue between different stakeholders, including scientists, policymakers, businesses, and communities, can help identify and address potential adverse impacts of innovation. By working together, we can find innovative solutions and ensure that the benefits of new technologies are maximized while minimizing negative consequences. 5. Regulatory frameworks: Developing and implementing effective regulatory frameworks can help ensure that innovation is conducted responsibly and in line with societal and environmental goals. Governments and international organizations play a crucial role in establishing and enforcing regulations that promote sustainable and responsible innovation. By combining these approaches, humans can become better equipped to identify and mitigate the adverse impacts of innovation, ensuring a more sustainable and responsible future.” #innovation #ai #sustainability

I had the privilege of participating in a lively and engaging discussion with members of the #SingaporePressClub yesterday evening, focusing on the intersection of #AI and #sustainability. A big thank you to our moderator, Audrey Tan, and my insightful co-panelists Raju C. and Rizwi Wun for their invaluable perspectives on this complex yet crucial topic. Key Takeaways: 🔹 AI’s Growing Power to do Good: Over the past two years, AI has evolved to become more powerful and versatile, capable of disrupting industries and tackling significant challenges like sustainability and climate change. Our work with clients highlights AI’s potential to: ➡ Enhance energy efficiency ➡ Integrate renewable energy sources ➡ Strengthen emissions monitoring ➡ De-carbonize operations, assets and value chains ➡ Uncover innovative sustainability solutions These applications have led to remarkable energy savings, cost reductions, and a decrease in GHG emissions. 🔹 Challenges and Governance: Despite its potential, AI faces issues such as inaccuracies, bias, and hallucinations. It can also infringe on IP rights and be manipulated by bad actors. Therefore, strong AI governance is essential for organizations looking to deploy AI at scale. 🔹 Responsible Use: AI is a powerful tool that must be used wisely and regulated appropriately. We all have a responsibility to ensure the creation of trustworthy and responsible AI that benefits society. Let’s collaborate to harness the power of AI for good and pave the way for a sustainable future. 🌍🤝 Patrick Daniel, Janet Wee - Ng, Augustine Anthuvan, Joon-Nie Lau, Selvi R, Juhi McClelland, Abraham Thomas, Balasubrahmanyam Pappu, Praveen Hariharan, Abhishek Kaul, Krishnakumar Nagarajan (KK), Ashutosh Deshmukh, Ram Panwar, Bharati Muthu, Paranee Reymondon, IBM