United States Artificial Intelligence Institute’s Post

📢 Tune Into Our Next Live Event on Primary Data vs Synthetic Data with AI: The Right Approach! We'll discuss the critical differences between these data types and cover some practical insights, cutting-edge strategies, and the right approach to leverage data effectively in your projects. Join Doug Slohm, Anna Marszalik-Kraszewska, Andrew Santana, and Richard Preedy on Oct 17th at 11.30am EST and learn about: - some parameters to keep in mind with synthetic data - best practices for using primary vs. synthetic data, or both - ethical impacts of using synthetic data in our studies - tools and technologies for working with synthetic data Stay ahead in the data-driven world and register today: https://shorturl.at/MvDjv Can't make the live session? Register anyway and get access to the recording! #IRB #MRX #MarketResearch #DataQuality #ResearchPanels #BigData #SyntheticData #AI

In a recent interview with Light Reading, Gal Schreiber discussed how Generative #AI is revolutionizing #telecom by converting unstructured data into actionable insights, even without deep data science expertise. The success of these AI models hinges on high-quality, accurate, telecom-specific data. However, many CSPs face challenges with siloed and ungoverned data, which can undermine AI effectiveness and hinder its adoption. This emphasizes the urgent need for CSPs to prioritize robust data management strategies, fully harnessing AI's potential in the industry Watch the full interview for more insights: https://lnkd.in/e4fMmnNw #GenerativeAI #Innovation #CustomerExperience #TechTrends #Amdocs

Solving AI hallucination with grounded data: Meet DataGemma! One of the key challenges in AI today is hallucination—when models generate inaccurate or misleading information. Our new DataGemma models solve this by grounding LLMs in real-world statistical data from Google’s Data Commons. AI outputs directly link to factual, verifiable data, ensuring more accurate insights and predictions across industries. This breakthrough allows for AI systems that generate predictions with a higher degree of reliability and real-world relevance for sectors like manufacturing, retail, and science. In this manner, DataGemma sets a new standard for AI reliability: https://ow.ly/q1JO50TB3Yg #DataGemma #AI #LLM #GroundingAI #DataCommons

Fuel your innovation with the power of high-quality data! Access free, ready-to-use datasets on YouData.ai and bring your AI projects to life. Don’t let data be a barrier to your success—explore our extensive collection today! 🌐 Visit www.youdata.ai #DataScience #AI #YouDataAI #BigData #Innovation #ExploreDatasets

Drowning in inaccurate data? Our AI solution cleans and analyzes data for smarter decisions. Stop wasting time and money and get the edge for your business with Pedals Up. #pedalsup #dataanalysis #ai #cleandata #aidevelopment #mobiledevelopment #softwarecompany #SoftwareSolutions

Transform your data into a wide array of information through AIDEN. Watch this demo and let us know what you think of it. #AI #AIDEN #artificalintelligence #Dataengineering #information #AiDataEngineer

🙏 A big thank you to Light Reading and Jim Hodges for the fantastic interview opportunity! It was a pleasure discussing the transformative power of #GenerativeAI. 🧬 From my customer conversations, it’s clear GenAI is more than a buzzword—it’s democratizing #AI and unlocking new opportunities. Crucially, GenAI enables CSPs to leverage unstructured data without deep data science expertise, but the output is only as good as the data it’s trained on. 🔍 Successful telecom use cases need clean, accurate, and comprehensive data. Siloed and fragmented environments often block CSPs from realizing GenAI’s full potential, prompting them to rethink data infrastructure. At #AmdocsDataIntelligence, we’re supporting them every step of the way. 🚀 The future of #AI in #telecom is bright, and I’m excited to see how it will reshape the industry.

AI and data science models can be complex, making them hard to trust and adopt. Explainability and interpretability are essential for the effective deployment and acceptance of AI across industries. By employing a range of techniques and maintaining robust documentation, organizations can ensure transparency, build trust and drive value from their AI initiatives. The future of AI is built on a foundation of trust, and explainability is key to achieving this. #AI #DataScience #ExplainableAI #Interpretability #Transparency #TrustInAI #ModelComplexity #IndustryApplications #AIFramework #PracticalExamples #DataSecurity #DataStrategy

Today’s businesses generate huge amounts of data that can help companies deliver better service and grow their presence in the market 📈 Yet many AI systems fail to utilize them effectively. Instead, they often deliver generic, uninspired responses. Why? 🤔 Because there’s a gap between the AI’s knowledge base and the wealth of information unique to your organization. Retrieval Augmented Generation (#RAG) is a revolutionary approach that bridges this gap by enabling AI to directly access and use your business data. Here's how RAGs can help your business grow and get ahead of competitors ⬇️ Unleash the power of YOUR data with AI. Book a FREE RAG workshop and see how: https://lnkd.in/dwQaNr8b #ZazmicEMEA #RAG #AI #Data

The 'best' embedding model may not always the right choice for your specific application 💡 In his latest blog, KX AI developer advocate Michael Ryaboy reveals the common mistakes AI practitioners make when choosing an embedding model: ❌ Benchmark scores don’t tell the whole story: Leaderboards are great for academic comparisons but often miss the nuances of your data and use case. 💻 Bigger isn’t always better: Massive models are tempting but have higher computational costs, slower inference and deployment complexities. 🔍 Overlooking domain specificity: Generic models are trained on broad data and might miss critical nuances in specialized fields. ⚙️ Ignoring practical constraints: Resource availability, latency requirements and scalability are often overshadowed. Read the full blog: https://lnkd.in/e8CavV6N #EmbeddingModels #AI #Data #DataQuality #ModelSelection