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Preparing for a Future with Generative AI

Insights (4)

In an economic environment where costs are rising, businesses are searching for new ways to improve margins, ideally by increasing productivity while lowering costs at the same time. Generative AI is offering a quickly growing toolbox for enhancing efficiency and reducing operational expenses with relatively low targeted investments. For example, AI tools can be used to process large amounts of documents, images or video content as well as to automatically generate new content at high quality.

It is not difficult for organizations to develop a multitude of ideas of how to put generative AI to work—indeed, the potential seems almost unlimited. But developing a comprehensive AI strategy for a business is a big challenge at a time when foundational technologies appear to evolve on a weekly basis.

The generative AI ecosystem is moving at a breathtaking speed, with new players arriving daily and established players at risk of disappearing. Big, commercial large language models (LLMs) are leading the scoreboards, but smaller and open-source models, including those with commercially viable licenses, are catching up quickly. The cost structure of operating LLMs is currently dominated by a scarcity of specialized hardware for AI clusters, with delivery times of a year or more for large customers. Selecting the right set of tools from an avalanche of unproven and quickly changing open-source projects is another considerable challenge.

It seems hard to pick the right combination of tools, AI models and technology suppliers for long-term tech investments, especially for organizations (including large, established consulting firms and IT service providers) that lack the expertise to implement generative AI. So what is a safe approach to creating an AI strategy if you do not want to miss out on this exciting technology, while hedging your bets and minimize your risk?

Wolfram Consulting Group can help companies to navigate this quickly transforming landscape by beginning with carefully selected and sharply focused use cases, avoiding the pitfalls of premature and costly investments. By rapidly developing prototypes for the most promising application areas, clients can gain experience and build the expertise and confidence to develop a longer-term generative AI strategy in preparation for more profound and transformative changes.

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A Data-Driven Approach to Multichannel Online Marketing

Client Results (6)

AGM, a globally operating digital marketing agency, develops advertising strategies and executes online marketing campaigns for its customers from a broad range of sectors. Their challenge was to determine the best possible allocation of marketing funds among multiple online channels, optimizing the overall effectiveness and return of investment of its marketing campaigns.

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Optimizing Wind Farm Operations and Maintenance with Discrete-Event Simulation

Client Results (6)

Offshore wind is one of the most important sources of renewable energy and a key area of interest for one of Wolfram Consulting Group’s clients. To get a complete understanding of the multitude of factors that contribute to the technical and financial performance of a wind farm, our client’s challenge was to design and develop a complete software package for modeling offshore wind operations.

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LLM EdTech Will Accelerate Progress in Education

Insights (4)

Why has progress in education been generally slow—at least as measured by standardized international student assessments—compared to the rapid advances in technology over the past two decades? Why have learning management systems (LMSs), ubiquitous access to mobile devices and the availability of vast knowledge resources on the web contributed little to close the education gap between students from both higher- and lower-income backgrounds?

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Applying Natural Language Processing to Automate Pharmacy Processes

Client Results (6)

A major US-based pharmacy chain needed to reliably automate the process of converting doctors’ prescriptions to standardized printed labels that are attached to customers’ prescription medicines. The doctors’ notes, written in expert English abundant with idioms and conventions used in medical practice, amounted to more than 100 million unique strings of text to be processed as a data stream with minimal latency at tens of transactions per second.

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