Jayant Swamy

Use Gartner's impact radar for generative AI to plan investments and strategy with four key themes in mind: ? Model-related innovations ? Model performance and AI safety ? Model build and data-related ? AI-enabled applications Explore all 25 technologies and trends. #GartnerIT #GenerativeAI #AI #Artificialintelligence

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Use Gartner's impact radar for generative AI to plan investments and strategy with four key themes in mind: ? Model-related innovations ? Model performance and AI safety ? Model build and data-related ? AI-enabled applications Explore all 25 technologies and trends. #GartnerIT #GenerativeAI #AI #Artificialintelligence

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Use Gartner's impact radar for generative AI to plan investments and strategy with four key themes in mind: ? Model-related innovations ? Model performance and AI safety ? Model build and data-related ? AI-enabled applications Explore all 25 technologies and trends. #GartnerIT #GenerativeAI #AI #Artificialintelligence

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Use Gartner's impact radar for generative AI to plan investments and strategy with four key themes in mind: ? Model-related innovations ? Model performance and AI safety ? Model build and data-related ? AI-enabled applications Explore all 25 technologies and trends. #GartnerIT #GenerativeAI #AI #Artificialintelligence

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Welcoming Snowflake to this LLM race. The Snowflake AI Research Team has introduced Snowflake Arctic, a top-tier enterprise focused LLM that pushes the frontiers of cost-effective training and openness. Arctic is efficiently intelligent and truly open. Arctic uses a unique Dense-MoE Hybrid transformer architecture. It combines a 10B dense transformer model with a residual 128x3.66B MoE MLP resulting in 480B total and 17B active parameters chosen using a top-2 gating.? Link: https://lnkd.in/gW3JpVbq #llms #genai #generatieveai #capgemini #llm?#opensourceai #capgeminiindia #ai?#artificialintelligence?#software #arctic #snowflake #moe ?#leaderboard #benchmark #benchmarking

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“Synthetic respondents are enabling us to create personas that simulate and replicate [human] behaviors with a high degree of fidelity,” says our President of Strategic Analytics & Insights, Ramon Melgarejo. One key use case is as a tool to help focus ideas in the early stages of the innovation cycle. Read more about Ramon's panel session "Does AI Know What We Truly Want? How Synthetic Respondents Are Disrupting Product Innovation" at Fast Company's Innovation Festival 2024. Click here to read the article and learn more about how our innovative application of AI gives market researchers a powerful new tool: https://ow.ly/87Hp30sHnBj #FCIF #TheFullView

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One of the best things about GoldenSource’s partnership with Snowflake is the ability it gives us to bring new innovations to our customers, fast. I’m very interested in this public version of #SQL #AI assistant, Copilot, from Snowflake, and how it’s going to enhance the functionality of the Mistral #LLM for users. New CEO Sridhar Ramaswamy is planting his flag firmly in the AI space, and - for me, at least - it’s absolutely the right strategy. #DataManagement #CloudData #EnterpriseDataManagement

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Use Gartner's impact radar for generative AI to plan investments and strategy with four key themes in mind: ? Model-related innovations ? Model performance and AI safety ? Model build and data-related ? AI-enabled applications Explore all 25 technologies and trends. #GartnerIT #GenerativeAI #AI #Artificialintelligence

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Use Gartner's impact radar for generative AI to plan investments and strategy with four key themes in mind: ? Model-related innovations ? Model performance and AI safety ? Model build and data-related ? AI-enabled applications Explore all 25 technologies and trends. #GartnerIT #GenerativeAI #AI #Artificialintelligence

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Good takeaways from your post Shanthi Srinivasan! Thanks for sharing. AI Adoption Trends: AI adoption is rapidly increasing, with 34% of organizations already using AI and 22% planning to adopt it this year. Generative AI is also gaining traction. Industry-Specific Use Cases: AI is revolutionizing sectors like fintech, healthcare, and retail with applications such as interactive chatbots, drug discovery automation, and hyper-personalized product descriptions. Cross-Industry Applications: Conversational AI, company-specific large language models, and digital asset management are some of the cross-industry AI applications gaining momentum. Future Predictions: The future of AI includes agentic AI, affordable development of large language models, and a strong emphasis on ethical and responsible AI.

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Data Architecture matters for accessing, transforming, and delivering data-driven insights and experiences. Want a quick primer on Data Mesh and Data Fabric? Below are some resources on Data Mesh and Data Fabric: - Applications of Data Mesh. https://lnkd.in/eAzA4fbs - Data Mesh and Federated Learning. https://lnkd.in/ekdp4ih8 - Data Fabric. https://lnkd.in/ejPfNXPt - Bonus: High Level video from Forrester on Data Mesh vs. Data Fabric https://lnkd.in/eATSrH-S Want to read my post for Marketers related to this topic? https://lnkd.in/edwFm4jR Thoughts on the above? Want to chat? https://lnkd.in/gWQ5v_Mh #TechnicalTuesdays #MarketingAnalytics #DataMesh #DataFabric #ResearchPapers #3StandardDeviations

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Meet with ZS at #InformaticaWorld24 to learn how we are enhancing enterprise data management and leveraging gen AI. Book a meeting here: https://bit.ly/3Ub3x0P #datagovernance #datamanagement #artificialintelligence #AI

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When you work within the Department of Defense's PPBE process, there is an important question you always have to ask: "What Year Are We Talking About?" It is easy to get confused between the plans for FY26 and the execution of FY24. And dealing with the frantic MAJ without asking what Fiscal Year he means...that can lead to chaos. #militarylife #governmentwork #pentagon

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Unlocking the Power of Large Language Models: A Guide for Executives As artificial intelligence continues to evolve, Large Language Models (LLMs) are transforming the way we interact with language. In this article, we'll explore the significance, characteristics, applications, limitations, and future implications of LLMs. Why LLMs Matter LLMs are a type of AI that enables computers to understand, generate, and process human language. This technology has far-reaching implications for businesses, governments, and individuals alike. By grasping the fundamentals of LLMs, executives can unlock new opportunities for innovation, efficiency, and growth. How LLMs are Trained LLMs are trained on vast amounts of data, often consisting of billions of parameters. This massive scale enables them to learn complex patterns and relationships in language, allowing them to generate human-like text and converse with users in a natural way. Key Characteristics of LLMs LLMs possess three key characteristics that make them so powerful: Scalability: LLMs can process vast amounts of data, making them ideal for large-scale language-based applications. Contextual Understanding: LLMs can comprehend the nuances of language, including context, tone, and subtlety. Generative Capabilities: LLMs can generate text, summaries, and even entire conversations, freeing humans from mundane tasks. Applications of LLMs LLMs are being used in various applications, including language translation, text summarization, chatbots, and content generation. These applications have the potential to revolutionize industries such as customer service, marketing, and education. Limitations of LLMs While LLMs hold tremendous promise, they're not without limitations. Key challenges include data quality and bias, as well as computational resource and energy consumption. It's essential to address these limitations to ensure the responsible development and deployment of LLMs. The Future of LLMs As LLMs continue to evolve, they'll have a profound impact on society. They'll enable more efficient communication, automate routine tasks, and unlock new opportunities for creativity and innovation. However, it's crucial that we address the limitations and challenges associated with LLMs to ensure their responsible development and deployment. Book an appointment https://lnkd.in/e2HAD4ug #LargeLanguageModels #LLMs #ArtificialIntelligence #NaturalLanguageProcessing #AI #MachineLearning #Innovation #Technology #Business #Leadership #ExecutiveInsights

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Use Gartner's impact radar for generative AI to plan investments and strategy with four key themes in mind: ? Model-related innovations ? Model performance and AI safety ? Model build and data-related ? AI-enabled applications Explore all 25 technologies and trends. #GartnerIT #GenerativeAI #AI #Artificialintelligence

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Use Gartner's impact radar for generative AI to plan investments and strategy with four key themes in mind: ? Model-related innovations ? Model performance and AI safety ? Model build and data-related ? AI-enabled applications Explore all 25 technologies and trends. #GartnerIT #GenerativeAI #AI #Artificialintelligence

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Did further deep-dive research with George Gilbert on Metadata & the next Intelligent Data Platform: ?? Data Management Evolution: Data management has shifted toward centralized consolidation, separating computational power from storage, leading to more efficient data handling. ?? AI-Powered Integration: AI and metadata integration face challenges in creating a coherent knowledge graph, but it streamlines complex processes like ingestion, transformation, and pipeline creation, ensuring consistency. ?? Network Effects: Unifying metadata throughout the data lifecycle enhances its quality, delivering effective data integration and management. ?? 360-Degree Views: Advanced entity resolution capabilities provide accurate 360-degree views of customer data, critical for maintaining quality and consistency. ?? Stakeholder Empowerment: AI-driven metadata management supports diverse users, from engineers to analysts, helping them make informed decisions and automate tasks. ?? Future Innovations: The continued integration of AI into metadata management drives innovation, aiming to build intelligent platforms, data products, and apps, empowering organizations to maximize the value of their data. ?? Check out the insights from Gaurav Pathak VP, Product Management AI & Metadata, at Informatica https://lnkd.in/gNzy_2QR Stay tuned as we evolve the reference architecture for the next Intelligent Data Platform together! #DataManagement #Metadata #AI #DataIntegration #DataPlatform #ETL #NoETL #PushDown #Cubes SiliconANGLE & theCUBE John Furrier David Vellante https://lnkd.in/gP6AM5Md

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Learn how technology leaders are stepping into a new era of health equity with the help of AI and ML: https://gag.gl/PKvMfJ. ?? Tech is closing the gap in social determinants of health (SDOH) by helping us understand and address the non-medical factors that influence health outcomes. ?? With new diagnosis codes focused on SDOH, healthcare providers can now offer personalized care like never before, giving a complete picture of patient health beyond the clinical data. ?? By embracing AI and ML, healthcare organizations are not just treating symptoms, they’re transforming lives and considering the whole person. #HIT #healthcare #SocialDeterminants #SDOH #PatientCare #Innovation

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