One of my takeaways from the Collide conference the other week is that if you wait to start on AI until your data is ready (clean and accurate), you’ll never start. Many companies are spending huge amounts of time and money on nebulous data prep projects, but it also seems clear to them that they’ll never be "done," and that in most cases they’re not even able to answer the question “ready for what?” Once you've figured out basic data access and governance questions, it's time to start. You may be surprised by how much more robust modern AI methods are to messy data, and you'll be able to direct your data prep investments toward what's actually required for specific use cases. #CollideConference #Graft #AI
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Great point(s) by Adam. If you wait until you have perfect data to start experimenting with AI…you’ll never start. Modern AI platforms like Graft derisk the leap into AI by alleviating the need to build out costly infrastructure and resources. Start today!
One of my takeaways from the Collide conference the other week is that if you wait to start on AI until your data is ready (clean and accurate), you’ll never start. Many companies are spending huge amounts of time and money on nebulous data prep projects, but it also seems clear to them that they’ll never be "done," and that in most cases they’re not even able to answer the question “ready for what?” Once you've figured out basic data access and governance questions, it's time to start. You may be surprised by how much more robust modern AI methods are to messy data, and you'll be able to direct your data prep investments toward what's actually required for specific use cases. #CollideConference #Graft #AI
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AI isn't a silver bullet and it's not a straightforward process to create value from your data - even with the arrival of some remarkable new tools. In reality, the path to unlocking value is far from simple. Behind the scenes, AI involves intricate data engineering and strategic planning. This encompasses a range of critical steps from sourcing and cleaning data to training models. Additionally, it includes navigating ethical considerations and ensuring robust security measures are in place. At Blue Margin, we can guide and support you on this journey. With our Managed Data Service (MDS), we help you navigate the complexities of AI, ensuring you have the data foundation in place to create value. Download our Guide to Data and AI: https://lnkd.in/grzJqPqw #GenerativeAI #DataAnalytics #BusinessIntelligence #AIdata #data
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A very likely scenarion is unfolding as many companies are venturing into AI. We all know about the elephant in the server room, a crucial concern often overlooked during this pioneering phase: bad data quality. From my perspective, the real challenges with data inaccuracies and biases may not become apparent until much later, leading to costly consequences. Wasted investments, diminished trust in AI, and potential legal risks can all stem from poor data practices. I believe it’s essential for businesses to address data quality early on. By prioritizing robust data governance and validation from the start, we can better harness AI’s potential and achieve meaningful, effective results. #ai #business #data #digitaltransformation
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In today’s fast-paced digital world, efficient data management is the key to staying ahead of the competition. Say goodbye to manual data entry and complex processes! Our AI Data Extraction Tool is here to transform the way you handle data, making it faster, smarter, and more accurate than ever before. Get in touch with us today to learn more about how our AI Data Extraction Tool can drive efficiency and innovation in your organization. 💬 Contact us now! www.novazenithai.com #AI #DataExtraction #Innovation #DataProcessing #TechSolutions #BusinessGrowth #Efficiency #DataSecurity #MachineLearning
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Big data is a rich strategic resource — but it’s a resource that is out of reach for most enterprises. The digital divide between big and small-data organizations is a serious concern due to self-reinforcing data network effects, where more data leads to better AI tools, which help attract more customers who generate more data, and so forth. Federated machine learning (FedML) is a recent innovative technology that overcomes this problem by means of privacy-preserving collaborative AI that uses decentralized data. It´s built on the idea of multiple small-scale companies pooling their data in a jointly controlled central repository. And it has already been successfully implemented in industry. Read more here in this article from MIT Sloan Management Review by auditors Yannick Bammens & Paul Hünermund. #ai #bigdata #data #machinelearning #business #economy #future #strategy #digitaltransformation #innovation #technology #collaboration
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Data Culture Data-driven Organization Do you believe that data can leverage your organization by giving insights which otherwise aren't visible? Do you believe that it isn't a privilege for select group in your organization? Rather it is a support for everyone to maximize the augmentation of AI and human intelligence? Then, giving your users access to (self-service) analytics without exception is the theme. Rather than predefined sets of dashboard that limits creativity and innovation. #self-service-analytics
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Discover the Hidden Treasures within Data: Your Business's Key Asset In today's tech-driven world, data isn't just information; it's the fuel that propels success—an expansive realm bursting with opportunities. Predictive AI thrives on accurate, unbiased, and high-quality data, illuminating valuable insights for effective decision-making. Although internal data is essential, the unexplored riches of external data hold immense potential. Neglecting these sources might hinder the success of your AI endeavors. Welcome to the era of data-driven strategies! #DataIsKey #AIInsights #UnlockingPotential
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AI assistants are revolutionizing the way we interact with data, but they're still on a journey toward perfect accuracy and relevance. As these tools mature, they continue to face challenges with accessing up-to-date and accurate enterprise information. For instance, an AI might respond with last year's data or miss current details about a company's executive team. As we harness the power of AI, ongoing refinement and updates are essential to ensure that these assistants can deliver the precise information businesses need to make informed decisions. #AIAssistants #DataRevolution #EnterpriseAI #DataAccuracy #ArtificialIntelligence #InformationAccess
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Digital Creator & Tech Influencer | LinkedIn Top Voice | Infopreneur 💡 Thought Leader | Sustainability Advocate
The right formula to facilitate the adoption of AI in our company is not: Tech + Money + Tech It's actually a little more complex, and we could write it as: Use Cases + Skills + Data + Tech + Organization Any other additions you'd suggest? #AI #Tech #Data
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🤔 This journey into the AI-enhanced future of small businesses has prompted me to ponder a few critical questions: 1. How can we best leverage AI to enhance our efficiency while ensuring our clients receive the personalized attention they deserve? 2. What skills should we focus on developing to complement the analytical prowess of AI and maintain the essential human element in our services? 3. As we navigate ethical considerations around data security and fairness in AI applications, what measures should we prioritize to uphold our commitment to customer trust and transparency? I'm eager to engage with fellow professionals on how AI is shaping your practices and the strategies you're employing to balance technology with the human aspect of our work. How are you navigating these changes, and what insights can you share about integrating AI into the small business landscape? #AITransformation #ProfessionalInsights
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VP Alliances & Products @ Centific | GenAI
10moAI is iterative, and compositional. Waiting for perfection is a failing strategy.