Description
Recommender systems for e-business have been expanding during the past years. At the same time, the COVID pandemic showed the importance of efficient Supply Chains. Global actors must master the whole chain: selling a product online, producing a product, storing a product in an optimized warehouse, and delivering the product on time. The consequences, as we have seen, can be disastrous for global actors who do not deliver on time. Managing huge amounts of data, constraints, and micro-decisions in a large supply chain has now become impossible without artificial intelligence. Artificial intelligence itself had to progress to predict sequences of actions and events. Artificial intelligence was not meeting the challenge up to the arrival of the Transformer model first designed by Google in 2017. The old, obsolete, 1980 architecture of Recurrent Neural Networks(RNNs) including the LSTMs were simply not producing good results anymore. In less than two years, transformer models wiped RNNs off the map and even outperformed human baselines for many tasks. This presentation goes to the core of recommender-based Transformers applied to the supply chain. In a world of complexity, only AI-dr…
Description from YouTube. Full content on the video page.
More from Databricks
NewsApache Iceberg V3 on Databricks: From Ingestion to Analytics
The video demonstrates Apache Iceberg v3 on Databricks, showcasing how its new variant column type natively handles semi-structured data and how row-level concurrency enables simultaneous data ingestion and corrections. It also highlights cross-platform data accessibility from open-source Spark via the Iceberg REST catalog, ensuring no vendor lock-in.
NewsDatabricks Genie for Marketing
Databricks' AI BI Genie allows non-technical marketers to converse with their Customer 360 data using natural language, enabling quick insights into marketing performance and campaign optimization. It helps identify issues like audience saturation and recommends budget reallocation by analyzing data and providing reasoning for its suggestions.
NewsGovern MCP servers in Databricks #databricks #mcp #aigovernance
Databricks Unity AI Gateway now governs MCP servers, centralizing their management alongside built-in foundation models and LLMs. This integration allows for easier governance and orchestration of various AI components and agents within Databricks.
NewsHow Suntory Turns Data into Faster Decisions with Databricks
Suntory uses Databricks to integrate diverse datasets, including internal sales, macroeconomic factors, and consumer behavior, into "Project Brain" for faster decision-making and product launches. The company also implements an all-employee upskilling program, "Manabi no Michi," to empower its workforce to leverage AI for improved performance and efficiency.
NewsAIA Group x Databricks: Turning Regulated Data into Real-Time Intelligence
AIA Group leverages Databricks to manage regulated data across 18 markets, addressing challenges like data residency and varying tech maturity with features like Unity Catalog for governance. The platform enables real-time intelligence for investment decisions, fraud detection, and personalized agent coaching, with future plans for conversational analytics and autonomous AI.
TutorialsConnect Google Sheets to Databricks
The Databricks Google Sheets add-in allows users to explore, import, and refresh governed data from the Databricks Lakehouse directly within Google Sheets. It demonstrates how to browse Unity Catalog, select tables or metric views, apply filters, schedule data refreshes, and use direct SQL queries with parameters.