Grote Taalmodellen zijn verbazingwekkend vaardig. Ze vatten samen, vertalen, redeneren en coderen (beter dan ik). Maar in tegenstelling tot mij, zijn ze ook berucht geworden voor het verzinnen van feiten met een angstaanjagend zelfvertrouwen.
Terwijl bedrijven zich haasten om AI operationeel te maken, ontdekken de meesten dat hun data infrastructuur nooit ontworpen is voor autonoom redeneren. Vandaag de dag wordt tot 80% van de AI implementatietijd besteed aan data wrangling en schema alignment, een symptoom van infrastructuren die gebouwd zijn voor opslag, niet voor begrip. Zonder een fundament dat relaties en betekenis vastlegt, blijven agents krachtig, maar blind. Nu AI agents actieve deelnemers worden aan enterprise workflows, evolueren de aard en de schaal van data query's.
Assortment optimization is a critical process in retail that involves curating the ideal mix of products to meet consumer demand while taking into account the many logistics constraints involved. The retailers need to make sure that they offer the right products, in the right quantities, at the right time. By leveraging data and consumer insights, retailers can make informed decisions on which items to stock, how to manage inventory, and what products to prioritize based on customer preferences, seasonal trends, and sales patterns.
MotherDuck extends DuckDB's analytical performance to the cloud with collaborative features, delivering 4x faster performance than BigQuery and cost savings over traditional data warehouses through serverless, pay-per-use pricing. Following the announcement of MotherDuck’s new European cloud region, we were impressed by its performance and attractive pricing. MotherDuck can already be integrated into your gold layers in order to accelerate the serving of data use cases while saving costs at the same time. See performance benchmark.
Assortment optimization is a critical process in retail that involves curating the ideal mix of products to meet consumer demand while taking into account the many logistics constraints involved. The retailers need to make sure that they offer the right products, in the right quantities, at the right time. By leveraging data and consumer insights, retailers can make informed decisions on which items to stock, how to manage inventory, and what products to prioritize based on customer preferences, seasonal trends, and sales patterns.
Neurale meetmethoden voor de evaluatie van machinevertalingen (MT) zijn steeds prominenter geworden vanwege hun superieure correlatie met menselijke beoordelingen in vergelijking met traditionele lexicale meetmethoden.
Discrete choice models aim at predicting choice decisions made by individuals from a menu of alternatives, called an assortment. Well-known use cases include predicting a commuter’s choice of transportation mode or a customer’s purchases.
The abundance and diversity of responses to ChatGPT and other generative AIs, whether skeptical or enthusiastic, demonstrate the changes they're bringing about and the impact they're having far beyond the usual technology circles. This is in stark contrast to previous generations of AI, which were essentially predictive and generally the subject of articles or theses confined to the realm of research and innovation.
In today’s dynamic and ever-evolving tech industry, a career track can often feel like a winding path through a dense forest of opportunities. With rapid advancements in technology, the possibilities are endless, but so are the challenges.
