AI is everywhere nowadays. But do you know how you can incorporate it into your commercial real estate business? Avison Young Chair & CEO Mark E. Rose shares how we are leveraging artificial intelligence to drive innovation and stay ahead of the curve in the #CRE investment landscape. Read Commercial Property Executive: https://lnkd.in/eb_McSPU #Tech #AI #AYdifference
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Web developer || MERN stack || Python || Node.Js || React.Js || AWS-Solution Architect || Javascript || HTML || CSS
📊 Synergy Between Data Analytics and AI 🤖 the synergy between Data Analytics and Artificial Intelligence (AI) is undeniable. These two pillars of modern technology are not only interdependent but also transformative in their own right. 🔍 **Data Analytics**: The Foundation Data Analytics serves as the bedrock of this partnership. It involves collecting, processing, and interpreting vast amounts of data to extract meaningful insights. It's the process of uncovering hidden patterns, trends, and correlations within data that drive informed decision-making. 🤯 **AI**: The Powerhouse On the other hand, AI is the powerhouse that takes data analysis to the next level. By leveraging machine learning algorithms, AI systems can not only analyze data but also learn from it. This ability to learn and adapt is what makes AI a game-changer. It can recognize complex patterns, make predictions, and automate tasks at unprecedented speeds and accuracy. 🔄 **The Interdependence** The relationship between Data Analytics and AI is symbiotic. Data Analytics provides AI with the raw material it needs to function effectively – the data. AI, in turn, enhances Data Analytics by automating tasks, identifying anomalies, and offering predictive analytics that can revolutionize business strategies. In the era of data-driven decision-making, the collaboration between Data Analytics and AI is a powerful force. Together, they unlock insights, drive efficiency, and enable us to tackle complex challenges like never before. Embrace this partnership, and you'll find the key to unlocking new opportunities and elevating your organization to new heights. 📈 #DataAnalytics #ArtificialIntelligence #AI #DataScience #Innovation #LinkedInPost #TechTrends
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ML Engineer in HealthTech | OpenSource Maintainer | Member at MLCommons | Ex-Chair of IEEE Student Branch NSEC
Reliable data availability is a challenge and is harder to get than it seems. Most of the startups struggle with this issue. They prepare their business plans and strategies to launch a superior model compared to their competitions but then struggle at the very first step of data availability. The 80:20 rule for data:model should be a basic thumb-rule consideration.
AI Advisor | Author “From Data To Profit” | Course Instructor (Data & AI Strategy, Product Management, Leadership)
The problem is that most companies are investing 80% of their AI budget into models and only 20% into data. Here’s what needs to change to unlock AI value. Shift investment from gathering data to curating data. Curation builds a dataset for model consumers vs. human consumers. The cost of model training drops because reliable use case support is delivered with less data and less complex models. Shift investment from engineering data pipelines to engineering data-generating processes. Moving data from one place to another creates no value, while each new dataset makes the business more valuable. Data creates more AI opportunities. Unique datasets are the primary competitive advantage and AI moat. Models are only best-in-class for a few months. GPT-4o was upstaged by Gemini 1.5, which was just surpassed by Claude 3.5. The investment required to win on massive models is much too high for enterprise business models to support. Follow me here and click the link under my name to learn more about how to deliver value-centric AI. #AI #Data #AIStrategy #DataQuality
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AI Advisor | Author “From Data To Profit” | Course Instructor (Data & AI Strategy, Product Management, Leadership)
The problem is that most companies are investing 80% of their AI budget into models and only 20% into data. Here’s what needs to change to unlock AI value. Shift investment from gathering data to curating data. Curation builds a dataset for model consumers vs. human consumers. The cost of model training drops because reliable use case support is delivered with less data and less complex models. Shift investment from engineering data pipelines to engineering data-generating processes. Moving data from one place to another creates no value, while each new dataset makes the business more valuable. Data creates more AI opportunities. Unique datasets are the primary competitive advantage and AI moat. Models are only best-in-class for a few months. GPT-4o was upstaged by Gemini 1.5, which was just surpassed by Claude 3.5. The investment required to win on massive models is much too high for enterprise business models to support. Follow me here and click the link under my name to learn more about how to deliver value-centric AI. #AI #Data #AIStrategy #DataQuality
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I innovate by dreaming and meditating. CEO at CODIUM and #1000C startups. PhD Candidate at CUTIP. My artistic moniker is Pacasso; I paint heretical experiences about tech, business, and spirituality. #Treelionaire
Exactly CODIUM’s “Trump card” In fact, our rule is not AI 80/20. It’s “Trusted” Data 100/0. And we started building the infrastructure for this since 2021 even before OpenAI ChatGPT became popular. Heck, even after ChatGPT and a bunch of copycats went mainstream, and amidst the ongoing AI hype, we double downed our penetrating “Truth” insights by never spending a single dime on building ANY AI models. We also don’t sell “AI hype” to any of our customers. Never done it. Ain’t never gonna do it in the future. Our goal has never been about get-rich-quick, get-famous-quick, nor get-Unicorn-quick. Fuck all of that. Since Day 1 (circa 2013), it has ALWAYS been about building something that will fundamentally transform Thailand with technology. That something finally is being manifested on our CODIUM YouTube channel and my own personal #Pacanata YouTube channel now. The time has come to “walk the talk” by storytelling our mission to the mass. And to my dying day, We #will #never #stop #period #โคตรเยี่ยม #AIdata #data #Strategy
AI Advisor | Author “From Data To Profit” | Course Instructor (Data & AI Strategy, Product Management, Leadership)
The problem is that most companies are investing 80% of their AI budget into models and only 20% into data. Here’s what needs to change to unlock AI value. Shift investment from gathering data to curating data. Curation builds a dataset for model consumers vs. human consumers. The cost of model training drops because reliable use case support is delivered with less data and less complex models. Shift investment from engineering data pipelines to engineering data-generating processes. Moving data from one place to another creates no value, while each new dataset makes the business more valuable. Data creates more AI opportunities. Unique datasets are the primary competitive advantage and AI moat. Models are only best-in-class for a few months. GPT-4o was upstaged by Gemini 1.5, which was just surpassed by Claude 3.5. The investment required to win on massive models is much too high for enterprise business models to support. Follow me here and click the link under my name to learn more about how to deliver value-centric AI. #AI #Data #AIStrategy #DataQuality
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Exciting times for #opensource #AI! 🦙 According to a recent Databricks report, Meta's Llama 3 captured nearly 40% of all open-source model usage within a month of its launch. With 3/4 of enterprises opting for open-source large language models, it's clear that cost and latency are driving this trend. Interestingly, most users of Meta’s Llama 2, Llama 3, and Mistral prefer models with 13 billion parameters or fewer. Open-source AI isn't just a trend—it's becoming a cornerstone of enterprise AI strategy. #AI #OpenSource #Llama3 #EnterpriseAI Follow Ray Estevez Advisory LLC and sign up for our newsletter to keep up with all the AI, Data, and Technology innovations. https://lnkd.in/ggbxXW5U
State of Data + AI
databricks.com
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VP, Head of Governance for SaaS, Vulnerability Management, Security Posture Management, State Street Alpha
Fantastic report on institutional investing in the AI world especially highlighting the need for data transformation first as opposed to focusing on digital or AI transformation first.
Capturing the data opportunity: Institutional investors in the age of AI | State Street
statestreet.com
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Driving Success in Complex Programmes | Expert in Private Equity Transitions & Startups | Senior Programme Manager delivering business results
A great insight here, about the real value generation from good quality data, thus unlocking value from AI implementation efforts, and making them simpler.
AI Advisor | Author “From Data To Profit” | Course Instructor (Data & AI Strategy, Product Management, Leadership)
The problem is that most companies are investing 80% of their AI budget into models and only 20% into data. Here’s what needs to change to unlock AI value. Shift investment from gathering data to curating data. Curation builds a dataset for model consumers vs. human consumers. The cost of model training drops because reliable use case support is delivered with less data and less complex models. Shift investment from engineering data pipelines to engineering data-generating processes. Moving data from one place to another creates no value, while each new dataset makes the business more valuable. Data creates more AI opportunities. Unique datasets are the primary competitive advantage and AI moat. Models are only best-in-class for a few months. GPT-4o was upstaged by Gemini 1.5, which was just surpassed by Claude 3.5. The investment required to win on massive models is much too high for enterprise business models to support. Follow me here and click the link under my name to learn more about how to deliver value-centric AI. #AI #Data #AIStrategy #DataQuality
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Business Analyst | Cyber Security Risk Manager | Governance, Risk and Compliance Specialist | ITIL v4 Expert | Programme Manager | Service Delivery Specialist | Information Security Practitioner | Oupa (Grandad)
Time for Businesses to Take Back Ownership - Part 5 - The Perils of Disconnected Ownership: AI and the Need for Integrated Business Insight As businesses increasingly look to integrate leading-edge technologies like neural networks and other forms of artificial intelligence (AI), the foundational understanding of their own systems, processes, and data becomes crucial. Without a deep and nuanced grasp of these elements, leveraging AI effectively is not just challenging—it's fraught with uncertainty. AI technologies are potent tools that can drive innovation and efficiency across a multitude of business domains—from customer service and sales forecasting to risk management and product development. However, for AI to deliver on these promises, it must be trained on robust, relevant datasets that reflect the unique aspects and operational realities of the business it's meant to enhance. The disconnect that arises when businesses do not maintain ownership and intimate knowledge of their systems and data is a significant barrier. AI models are only as good as the data they are trained on. If a business has ceded control of its systems and data management to IT without maintaining a collaborative and integrated approach, it risks compiling datasets that are either incomplete or not fully aligned with the business’s strategic goals. This misalignment can lead to AI outputs that are misleading or irrelevant, thus wasting resources and potentially leading to strategic missteps. Moreover, without proper data governance, the quality and integrity of the data used for training AI could be compromised. Poor data quality directly impacts the reliability and accuracy of AI predictions and decisions, which could have serious repercussions for decision-making processes. For businesses to truly benefit from AI and other advanced analytical tools, there needs to be a reestablishment of control over business processes and data. Business leaders must work closely with IT to ensure that data is not only secure and well-managed but also strategically aligned with the business's needs. This collaborative approach will facilitate the development of AI models that are both powerful and tailored to specific business objectives, ensuring that the technology adds real value. In essence, as businesses venture into the future with AI, the clarity and ownership of their underlying systems and data will not merely be a matter of operational necessity but a strategic imperative. The successful integration of AI into business strategies hinges on this fundamental alignment, ensuring that these advanced technologies drive meaningful outcomes #AI #technology #data
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3 Reasons to Choose Insenuity Pty Ltd: -Expert guidance in Data Analytics, AI, and Program Governance. -True partnership with experienced teams for successful project execution. -Leading businesses through the 4th Industrial Revolution. Contact us today to learn more. 🌐 https://lnkd.in/gNAiXZnX #insenuity #programgovernance #datavisualization #businesscentral #businessanalytics #datamanagement #businessdata #innovation #technology #dataasset #futureofbusiness #digitaltransformation #businessgrowth #bi #ai #microsoftbusinesscentral #powerbi #powerapp #datagovernance #businessintelligence #artificialintelligence #digitaltransformation #programmanagement
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