EM360Tech’s Post

🎤 EM360Tech caught up with Ataccama CPO Jay Limburn at Big Data LDN to discuss successful AI adoption and strategy. ▶️ Watch the full interview here: https://lnkd.in/epBwRMXV. #Ataccama #EM360Tech #BigDataLDN #AI #AIAdoption #Data

Great interview with ThoughtSpot CEO Ketan Karkhanis in diginomica with Derek du Preez on how GenAI and LLMs are supercharging analytics. As Ketan says, "There's no better time to be in this analytics industry, because we are going through a profound change. AI is the new BI and ThoughtSpot is leading the way, because we were meant for this moment." 🏆

Did you know that 2.5 Quintillion bytes of data are generated daily? In this digital age, harnessing this vast sea of information is crucial. That's why we trust Reveal Data, our end-to-end e-Discovery platform powered by advanced technologies like large language models (LLM) and AI-assisted review. Transform raw data into actionable insights effortlessly! #DataAnalytics #TechInnovation https://lnkd.in/gNEwq9zU

📽️ From Table Talk to Data Magic! In our last video, we introduced the basics of setting up table relationships in a simple two-table scenario. But what if your data structure is more complex? In this follow-up video, Zahari Tilev dives into multi-table relationships, explaining how to use context vs. non-context foreign keys to ensure your synthetic data is accurate and meaningful. 🍿 Watch it here: https://lnkd.in/dTuSxg5W We’d love to hear your thoughts—share your feedback or questions in the comments! #SyntheticData #TableRelationships #DataPrivacy #GenerativeAI #GenAI #MostlyAI

Data Scientist Ryan Siegler shares valuable insights into the concepts, methods and optimization of LLMs with multi-modal RAG. Catch up with Ryan and Neil Kanungo in a recent LinkedIn Live event to gain insider knowledge on how LLMs and multi-modal RAG are reshaping the AI landscape and how to avoid challenges that come with it. Watch the full video: https://bit.ly/3WdcBDP #LLM #MultiModalRAG #KX #DataScience #TechTalks #GenAI

Last week's Data Science Summit was a solid deep-dive into real-world AI implementation challenges and successes. The event featured numerous interesting topics and presentations but particularly engaging were the frank round table discussions that tackled interesting topics: organizational readiness for AI, bridging the business-IT communication gap, production models deployment hurdles, and real-world LLM implementation in healthcare challenges. Most valuable for my focus areas were an insightful sessions on Causal ML applications in price management by Artur Machno and Łukasz Frydrych, Dawid Marczak's practical insights on effective AI deployment paths and Michał Gołoś's hands-on approach to Snowflake Dynamic Tables and Cortex AI. The advances in Polish language models development were also impressive. 👏 Thanks to Smith+Nephew for enabling my participation in this insightful event. #DataScienceSummit #DSS24

The "10,000-Hour Rule", claims that the key to achieving world-class expertise in any skill, is, to a large extent, a matter of practicing the correct way, for a total of around 10,000 hours. AI is here to stay, and the use of AI is a learnable and teachable skill. The Question I have for you, is that when will you reach your 10,000 hours? Join us on the 27th of April at 2:30 PM GMT +2 And get to hear some insights we have prepared for you. Register for the webinar: https://lnkd.in/diqpq5sw

Back to the Future at 2024 #DSSATX (Data Science Salon). Day 1. New venue at Oracle this year for this great get together, and LLMs are at the center of the discussion. Highlight from the discussion today came from Hasham Ul Haq at John Snow Labs. He had the best summary of the current state of ChatGPTs I have seen so far..."LLMs are good as an interface but bad at information extraction". He showed the potential for smaller language models (SLMs - which are often a derivative from an LLM) paired with RAG (retrieval augmented generation) and process steps like breaking documents into chunks (to prevent loosing valuable results that can get watered down in a search) and reranking (taking the top results and reshuffling, think of it as a Whiskey like distillation process) to give more accurate results. A step closer to meeting enterprise Machine Learning standards. Compared to available LLMs, he showed a 100x reduction in cost to use the model, a 2-5x improvement in accurate search results, and the ability to trace the answer back to the document and also the specific part of the document for human review (the chunk). Also great to see the panel led by Randi R. Ludwig, and the Generative AI discussion from Fatma Tarlaci, Ph.D. who emphasized the need for responsible AI.

"🌟 Exciting News! DataArt has achieved the ‘Major Contender’ status in Everest Group’s Analytics and AI Services Specialists PEAK Matrix® Assessment for 2024. This recognition is a testament to our unwavering commitment to innovation and client success. Celebrate this milestone with us and explore the details in our press release: https://lnkd.in/dt2r_Afb #DataArt #Analytics #AI #EverestGroup #Innovation #PeakMatrix"