Every organization wants to deploy AI. But AI without high-quality operational data is just an algorithm waiting for a purpose. Generative AI and machine learning models are powerful, but they are only as effective as the data they're fed. Before you can predict, you must see. Before you can optimize, you must measure. Thinaer delivers the foundational layer: a clean, structured, real-time data stream from your physical operations, making AI possible. #AI #GenAI #MachineLearning #DataFoundation #DigitalTransformation #BigData #AIImplementation #DataQuality #OperationalExcellence #DataDriven #MachineLearningModels #RealTimeData #DataStrategy #AIForBusiness #DigitalInnovation #DataAnalytics

💡 Smaller Models, Bigger Impact Reddit discussions and my experiments confirm: more parameters ≠ better results. Small, fine-tuned models can match or outperform larger ones for domain-specific tasks. 🔍 Example: A 7B parameter transformer matched a 13B model’s accuracy on a specialized task while using half the energy. ⚡ Lesson: Efficiency isn’t optional; it enables faster iteration, cheaper deployment, and more sustainable AI. 🔥 Takeaway: Focus on right size + right tuning rather than blindly scaling up. #MachineLearning #AI #ModelOptimization #EfficientAI #DeepLearning

A recent study from McKinsey shows that less than 10% of firms adopting AI see a positive ROI. Foresight Strategy can work with you to create positive ROI with AI: from generative Ai to quickly illustrate concepts that can drive your innovation, to agentic AI to create synthetic data or even "PersonaGPT" that are calibrated with research data + context from the web to deliver insights that your data alone could never deliver. Get in touch with us to learn about the many use cases that have already been successfully been delivered to our clients. #AI #createROIwithAI #AIinsights #foresightstrategy

https://lnkd.in/eA4gsRkh AI's been around longer than you think! 🤖 From reading car plates to generating music, it's all AI in action. Machine learning uncovers data patterns, while generative AI creates new things. LLMs are part of GenAI, but GenAI does more than just LLMs. Think funny cat videos: AI translates your prompt into reality! The possibilities are endless, and the future is bright! ✨ #AI #MachineLearning #GenerativeAI #TechInnovation

AI and ML continue to evolve faster than most teams can adapt from multimodal models that process text, images, and video simultaneously to smaller, fine-tuned LLMs that outperform larger ones in domain-specific tasks. It’s no longer just about scale it’s about efficiency, context, and responsible deployment. The companies getting it right are those integrating AI into existing workflows, not just building shiny new tools. I’m curious what recent AI/ML advancement do you think will have the biggest practical impact in the next year? #AI #MachineLearning #LLMs #TechTrends #DataScience

Ever wondered how AI can get even smarter? Google DeepMind just unveiled Gemini 1.5, and it's a game-changer! 🚀 This new model is designed to enhance reasoning capabilities and provide more accurate responses. Imagine an AI that not only understands your queries better but also delivers faster and more reliable answers. Here’s what stands out: 🔹 Enhanced reasoning capabilities for complex queries 🔹 Improved accuracy in responses 🔹 Faster processing times How do you think this will impact the way we interact with AI in our daily lives? #AI #MachineLearning #TechInnovation

Accuracy isn't about the model. It's about what you feed it. Better chunking + smarter embeddings = 80% of accuracy gains. You don't need a bigger model; you need better retrieval. Start with semantic chunking (keeping related sentences together) instead of arbitrary chunk sizes. Then test different embedding models — sometimes a mid-tier embedding beats expensive closed-source options. One change: from naive chunking to semantic chunking. Accuracy jumped 25%. #RAG #LLM #Accuracy #AI #GenAI

Prompt-Tuning vs Fine-Tuning — Which One Should You Choose? I recently wrote a blog breaking down two key AI customization approaches — fine-tuning and prompt-tuning — and when to use each. Whether you’re building smarter chatbots or domain-specific AI tools, understanding the difference can save time, cost, and effort. 👉 Check it out here: Fine-Tuning vs Prompt-Tuning: - https://lnkd.in/dapTYmus 💬 Curious to know — which approach do you prefer for your AI projects? #AI #MachineLearning #PromptEngineering #FineTuning #ArtificialIntelligence #TechInsights #neovasolutions

Predictive Analytics in Business Decision-Making uses AI and machine learning to analyze historical and real-time data, allowing organizations to forecast future outcomes with accuracy. This proactive approach enables smarter decisions, whether it’s seizing growth opportunities or preventing costly setbacks. This post was synthetically created. #PredictiveAnalytics #AI #MachineLearning #DataScience #BusinessIntelligence #RiskManagement #AIInsights #SmartDecisions #DataDriven #fAlpha

Predictive Analytics in Business Decision-Making uses AI and machine learning to analyze historical and real-time data, allowing organizations to forecast future outcomes with accuracy. This proactive approach enables smarter decisions, whether it’s seizing growth opportunities or preventing costly setbacks. This post was synthetically created. #PredictiveAnalytics #AI #MachineLearning #DataScience #BusinessIntelligence #RiskManagement #AIInsights #SmartDecisions #DataDriven #fAlpha