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From Hype to (uncomfortable) Truth: 5 Reasons Your Current Approach for Key Driver Analysis Likely Falls Short Reality check: Most current approaches might look good on paper, but they could be obscuring the insights you need. Here's why: 1️⃣ Most used methods are designed for prediction, not explanation: This means you're only scratching the surface of what matters. 2️⃣ Multicollinearity Distortions: Sure, these methods claim to handle multicollinearity, but in reality, they often leave behind biases that skew your results. 3️⃣ Overlooking Non-Linear Relationships: Real-world data is rarely linear! 4️⃣ Confusing Coefficient Interpretability: The bias-variance trade-off in these models often results in misleading interpretations. 5️⃣ Inconsistent Estimation: High dimensionality and multicollinearity? Good luck! These methods struggle, often producing inconsistent results that muddy the waters rather than clarify them. Time to move beyond the hype and demand more from your Key Driver Analysis! Reach out to discover our solution. #DataAnalysis #KeyDriverAnalysis #methodology #innovation

🧭 Transformative waves of the new EU Health Technology Assessment Regulation! The EU Health Technology Assessment Regulation is set to reshape how we evaluate clinical data across Europe. This change brings a new level of collaboration and efficiency to health technology assessments. What does this means for EU Member States and the pharmaceutical industry? Check out our latest article to understand the upcoming changes. And more to come from us on creative solutions to help you navigate this landscape, stay tuned! The article 👉 https://lnkd.in/eaZqrrH4 #Healthcare #EUHTAR #HealthTechnology #Pharma #Regulation #FutureOfHealthcare #Innovation

Fixed, differentiated, dynamic or algorithmic. That's it for Pricing ? Quite striking to take for granted that Pricing is somehow 'emotionless' and 'socially disconnected', whereas consumer behaviour is all about emotions social media influence today. That's exactly what our Emotional and Social Influence Pricing Algorithm aims to solve by leveraging: - behavioral and emotional analytics - social dynamics, social media influence, and network trends Think of it as a chip that makes your prices emotionally and socially aware of their consumers. It ensures that the pricing is aligned with the consumer’s perceived value at the moment of interaction, for every interaction. #consumerinsights #pricing #innovation #artificialintelligence

What is the common setback among conventional approaches like MaxDiff, Regressions (MR, PLS, etc.), Conjoint, Van Westendorp, IPA, Kano, Correlation Analysis, etc.? Spoiler: They all fall short in at least one way, as much of consumer behavior is subconscious and hard to articulate. This is where IntuiMetrics comes in. Wherever conventional approaches scratch 1 inch, IntuiMetrics goes 1 mile deep, without causing respondent fatigue, cognitive overload, or declarative bias. IntuiMetrics pioneers a comprehensive blueprint for delivering deeper actionable insights. Reach out for more! #MarketResearch #ConsumerInsights #IntuiMetrics #Innovation #FutureOfResearch

Generative AI, when combined with other AI technologies and analytics, holds immense potential to unlock new value. The energy and materials sector stands to gain significantly! This sector's heavy reliance on data analytics generates vast amounts of information. Gen AI has the capability to revolutionize various aspects of the industry for companies, impacting everything from back-office functions to core operational processes. #genAI #tech #artificialintelligence

From Under-sampled to Loud and Clear: Giving Voice to Your Niche and Granularity to Your Insights with Market Twin, the Moonshot for Consumer Insights. Capturing granular insights from underrepresented niches has always been daunting — until now. But Market Twin, our proprietary solution, gets you covered. It harnesses advances in synthetic methods and statistics to effectively double your sample size without issues like respondent fatigue and other forms of disengagement typically associated with traditional data collection methods. This means faster, more reliable insights that empower you to make informed decisions swiftly. Discover how Market Twin can transform your approach, providing the granularity you need. 👉 https://lnkd.in/eWgmk_KC

Better than MLPs for Deep Learning? Yes, we KAN! New neural network architecture, dubbed Kolmogorov-Arnold Networks (KANs), is set to revolutionize the field. Drawing inspiration from a profound mathematical theorem, KANs offer a novel approach by implementing learnable activation functions on edges rather than fixed ones on nodes. Why does this matter? This shift allows KANs to not only outperform traditional Multi-Layer Perceptrons (MLPs) in terms of accuracy and interpretability but also to do so with considerably smaller model sizes. As we continue to rely on MLPs in many advanced deep learning models, the advent of KANs paves the way for new possibilities in pushing the boundaries of what neural networks can achieve. Stay tuned as we explore how KANs continue to shape the future of artificial intelligence and machine learning. The implications for technology and science are vast and exciting! 👉 https://lnkd.in/dxPtcVyG #AI #MachineLearning #NeuralNetworks #Innovation

Are decoder-only models enough? Decoder-only Large Language Models (LLMs) excel in generative tasks but lag in text embedding—until now. LLM2Vec, an unsupervised method, revolutionizes this by turning any decoder-only LLM into a powerful text encoder. Combining bidirectional attention with masked token prediction and contrastive learning, LLM2Vec dramatically outperforms encoder-only models in word-level tasks and achieves unprecedented results on the Massive Text Embeddings Benchmark (MTEB). When enhanced with supervised learning, it reaches top performance on MTEB using only publicly available data. This marks a significant advancement in AI, paving the way for more innovative applications. 👉 https://lnkd.in/e79r7whc #AI #MachineLearning #NLP #Innovation #LLM2Vec

New Frontier in Consumer Insight Discovery with Gen-AI! In the quest to understand consumer preferences better, Gen-AI is emerging as a game-changer! 🔄 While traditional methods like polls and surveys have been instrumental, the introduction of Gen-AI is revolutionizing accuracy and transforming the landscape of market research. Embrace the future with our Gen-AI and stay ahead in decoding consumer needs! #MarketResearch #Gen-AI #Innovation #ConsumerInsights

Have you ever stumped an AI with an ultra-specific question? You're not alone. For those in the know, updating a Large Language Model's (LLM's) knowledge is crucial. Should we lean towards Retrieval Augmented Generation (RAG) or fine-tuning? Recent research has thrown light on this debate by comparing RAG and fine-tuning, specifically in the realm of question-answering tasks using synthetic data. The results are intriguing. Both strategies significantly enhance the model's performance on niche topics. However, RAG edges out, leading the way in efficiency, particularly for tackling rare or unique queries. Does this sideline fine-tuning? Absolutely not. It still plays a vital role, especially in deeply embedding knowledge. Yet, when it comes to agility in learning about infrequent concepts, RAG seems to hold the upper hand. 👉 https://lnkd.in/eQBgiPaC. Let's keep the conversation going: What's your experience with RAG and fine-tuning in AI development? Share your insights below! #AILLM #RAGvsFineTuning #AIResearch