modeling-data-processing 
O'Reilly on Data
APRIL 30, 2024
Others retort that large language models (LLMs) have already reached the peak of their powers. These are risks stemming from misalignment between a company’s economic incentives to profit from its proprietary AI model in a particular way and society’s interests in how the AI model should be monetised and deployed.
IBM Big Data Hub
MAY 1, 2024
AI tools help users address queries and resolve alerts by using supply chain data, and natural language processing helps analysts access inventory, order and shipment data for decision-making. AI-supported what-if modeling helps develop contingency plans such as inventory, supplier or distribution center reallocation.
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CIO Business Intelligence
MAY 3, 2024
Bala Subramanian, chief digital and technology officer at UPS, sees the company’s foray into generative AI as not only a winner for its customer contact center agents but something to be introduced to other business processes in the near future, he says. The LLM gives agents the ability to confirm all responses suggested by the model.
CIO Business Intelligence
APRIL 29, 2024
Innovation stagnates because specifics defined in the tender process restrain suppliers. Advances in standardized and automated bidding systems aimed at speeding up the supplier selection process often creates an inherent perverse incentive where the buyer gets what they asked for in the bid — not necessarily what they needed.
Speaker: Megan Brown, Director, Data Literacy at Starbucks; Mariska Veenhof-Bulten, Business Intelligence Lead at bol.com; and Jennifer Wheeler, Director, IT Data and Analytics at Cardinal Health
Join data & analytics leaders from Starbucks, Cardinal Health, and bol.com for a webinar panel discussion on scaling data literacy skills across your organization with a clear strategy, a pragmatic roadmap, and executive buy-in. In this webinar, you will learn about: Launching data literacy programs and building business cases.
CIO Business Intelligence
APRIL 30, 2024
Enterprises are moving computing resources closer to where data is created, making edge locations ideal for not only collecting and aggregating local data but also for consuming it as input for generative processes. Transmitting massive amounts of raw data to the cloud can strain network bandwidth. over 2023 2.
AWS Big Data
MAY 1, 2024
To provide a variety of products, services, and solutions that are better suited to customers and society in each region, we have built business processes and systems that are optimized for each region and its market. The platform consists of approximately 370 dashboards, 360 tables registered in the data catalog, and 40 linked systems.
Advertiser: Data Robot
Capitalizing on the incredible potential of AI means having a coherent AI strategy that you can operationalize within your existing processes. The importance of governance in ensuring consistency in the modeling process. How MLOps streamlines machine learning from data to value.
Advertiser: Data Robot
Democratization puts AI into the hands of non-data scientists and makes artificial intelligence accessible to every area of an organization. But in order to reap the rewards that AI offers, it is essential that businesses first address how their organizations are set up, from their people to their processes. Identifying good use cases.
Advertiser: Data Robot
More and more critical decisions are automated through machine learning models, determining the future of a business or making life-altering decisions for real people. But with the incredible pace of the modern world, AI systems continually face new data patterns, which make it challenging to return reliable predictions.
Speaker: Shreya Rajpal, Co-Founder and CEO at Guardrails AI & Travis Addair, Co-Founder and CTO at Predibase
Large Language Models (LLMs) such as ChatGPT offer unprecedented potential for complex enterprise applications. However, productionizing LLMs comes with a unique set of challenges such as model brittleness, total cost of ownership, data governance and privacy, and the need for consistent, accurate outputs.
Speaker: William Hord, Vice President of ERM Services
A well-defined change management process is critical to minimizing the impact that change has on your organization. Leveraging the data that your ERM program already contains is an effective way to help create and manage the overall change management process within your organization. Organize ERM strategy, operations, and data.
Speaker: Dave Mariani, Co-founder & Chief Technology Officer, AtScale; Bob Kelly, Director of Education and Enablement, AtScale
Check out this new instructor-led training workshop series to help advance your organization's data & analytics maturity. Given how data changes fast, there’s a clear need for a measuring stick for data and analytics maturity. Workshop video modules include: Breaking down data silos. Developing a data-sharing culture.
Advertiser: Data Robot
Numerous high-profile examples demonstrate the reality that AI is not a default “neutral” technology and can come to reflect or exacerbate bias encoded in human data. Download this guide to find out: How to build an end-to-end process of identifying, investigating, and mitigating bias in AI.
Advertiser: ZoomInfo
Multiple industry studies confirm that regardless of industry, revenue, or company size, poor data quality is an epidemic for marketing teams. As frustrating as contact and account data management is, this is still your database – a massive asset to your organization, even if it is rife with holes and inaccurate information.
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