Brian Land’s Post

You likely use AI frequently in your daily work and life, and you're probably aware of bias in AI. While bias is inherent in human nature, have you considered the implications of bias in Industrial AI? How can we address it to ensure data integrity, protection, and transparency? Learn more about Siemens' perspective, strategies, and solutions. Here are my takeaways: 1️⃣ Bias is part of our specie’s evolution 2️⃣ Even industrial AI is not immune: There are different ways to classify bias 3️⃣ It’s crucial to enhance AI’s reliability and trust in critical sectors like transportation and manufacturing 4️⃣ The trust factor: Together we can break bias Read the whole article and find out more here 👉 https://sie.ag/2kADEz

Some really fascinating insights coming out of the latest McKinsey report on The State of AI. In 2024 Generative AI adoption has accelerated rapidly. We are now seeing Gen AI utilised across a wide range of industries and business functions. Companies are seeing the potential that it can have to streamline processes and improve output. If Gen AI is in your pipeline for the second half of 2024, get in touch for a free Gen AI 'Infrastructure Health Check' with TitanML to ensure optimal performance, security and scalability. See the full report 🔽 https://lnkd.in/dqBGgssP #GenAI #LLMs #McKinsey

Industrial AI opens up unimagined possibilities for a smarter, future-proof world. Yet to realize this, we must ‘break bias’ to ensure data integrity, protection and transparency. In a recent article, I learned about bias in AI and what it means for trust in industrial AI ⚖️ 🤖 Here are my takeaways: 1️⃣ Bias is part of our specie’s evolution 2️⃣ Even industrial AI is not immune: There are different ways to classify bias 3️⃣ It’s crucial to enhance AI’s reliability and trust in critical sectors like transportation and manufacturing 4️⃣ The trust factor: Together we can break bias Read the whole article and find out more here 👉 https://sie.ag/2kADEz

Gen-AI has been a buzzword for a while now, but it comes with its own inherent challenges. Check out this podcast wherein our CEO and President, Anurag Lal, addresses the risks and best practices associated with deploying AI within an enterprise. #genai #ai

Industrial AI opens up unimagined possibilities for a smarter, future-proof world. Yet to realize this, we must ‘break bias’ to ensure data integrity, protection and transparency. In a recent article, I learned about bias in AI and what it means for trust in industrial AI Here are my takeaways: 1️⃣ Bias is part of our specie’s evolution 2️⃣ Even industrial AI is not immune: There are different ways to classify bias 3️⃣ It’s crucial to enhance AI’s reliability and trust in critical sectors like transportation and manufacturing 4️⃣ The trust factor: Together we can break bias Read the whole article and find out more here 👉 https://sie.ag/2kADEz

Industrial AI is not immune! How to keep BIAS out of your systems ⚖️ 🤖 Industrial AI holds immense potential, but bias—an inherent part of human evolution—can still seep into these systems. By recognizing and addressing biases in data and processes, we can enhance AI reliability and foster trust in critical sectors like transportation and manufacturing. Curious about how we’re "breaking bias" for a transparent and future-proof AI? Take a look at concrete examples, tools and strategies in this article 👉 https://sie.ag/PGD9U #Siemens

Just read an interesting article: Industrial AI is not immune! How to keep BIAS out of your systems ⚖️ 🤖 Industrial AI holds immense potential, but it isn’t immune to bias—an intrinsic part of human evolution that can still seep into these systems. By actively recognizing and addressing biases in data and processes, we can enhance AI reliability and build trust in critical sectors like transportation and manufacturing. Curious about how we’re breaking down bias to pave the way for transparent and future-proof AI? This article offers concrete examples, tools, and strategies—worth a read! 👉https://sie.ag/PGD9U #TeamSiemens #TransformTheEveryday

Industrial AI opens up unimagined possibilities for a smarter, future-proof world. Yet to realize this, we must ‘break bias’ to ensure data integrity, protection and transparency. In a recent article, I learned about bias in AI and what it means for trust in industrial AI ⚖️ 🤖 Here are my takeaways: 1️⃣ Bias is part of our specie’s evolution 2️⃣ Even industrial AI is not immune: There are different ways to classify bias 3️⃣ It’s crucial to enhance AI’s reliability and trust in critical sectors like transportation and manufacturing 4️⃣ The trust factor: Together we can break bias Read the whole article and find out more here 👉 https://sie.ag/2kADEz

Industrial AI opens up unimagined possibilities for a smarter, future-proof world. Yet to realize this, we must ‘break bias’ to ensure data integrity, protection and transparency. In a recent article, I learned about bias in AI and what it means for trust in industrial AI ⚖️ 🤖 Here are my takeaways: 1️⃣ Bias is part of our specie’s evolution 2️⃣ Even industrial AI is not immune: There are different ways to classify bias 3️⃣ It’s crucial to enhance AI’s reliability and trust in critical sectors like transportation and manufacturing 4️⃣ The trust factor: Together we can break bias Read the whole article and find out more here 👉 https://sie.ag/2kADEz

Industrial AI is not immune! How to keep BIAS out of your systems ⚖️ 🤖 Industrial AI holds immense potential, but bias—an inherent part of human evolution—can still seep into these systems. By recognizing and addressing biases in data and processes, we can enhance AI reliability and foster trust in critical sectors like transportation and manufacturing. Curious about how we’re "breaking bias" for a transparent and future-proof AI? Take a look at concrete examples, tools and strategies in this article 👉 https://sie.ag/PGD9U