It’s no secret: quantum computing has been poised to be “the next big thing” for years. But recent developments in the quantum ecosystem, including major investments by companies such as IBM, Google, Microsoft and others, are the best indicators that now is the time to begin preparing for potentially viable quantum applications—and to identify where and when to most effectively use them.
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.
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?
In today’s fast-paced digital landscape, organizations need cutting-edge technology to stay ahead of the competition. One such technology that has revolutionized the field of knowledge-based computing is Wolfram|Alpha, a platform that fundamentally transforms how knowledge is presented, acquired, developed and managed. Wolfram Consulting Group has helped large corporate clients deploy custom versions of Wolfram|Alpha to unlock a world of possibilities for their customers.
Few recent technological innovations have generated as much enthusiasm as generative AI. Wolfram has been at the front of this profound transformation, as demonstrated with the integrations of its technology stack with new LLM-based offerings such as OpenAI’s ChatGPT, Microsoft’s Bing Chat and Google’s Bard. By combining Wolfram’s broadly recognized expertise in computation and computational knowledge with these leading generative AI platforms, we are giving an early glimpse of the expanding range of possible applications for your business and engineering challenges.