Turn AI aspirations into reality

It’s close to two years since the release of ChatGPT unleashed a torrent of eye-popping Gen AI pilots. The initial excitement has given way to a growing sense of exasperation in the enterprise, as firms have struggled to move from proof of concept to production.?

We see this time and again at Thoughtworks. It’s not that people are any less impressed with generative AI technology, but building systems that business leaders feel confident about putting into production is a different story.

In some cases, the opaque nature of how large language models arrive at solutions needs to be addressed. Other companies have found that they need to refine their data platforms and products before unleashing new tools upon them.?

Even so, we’re seeing clients making headway. This marks a watershed moment for Gen AI, where novel ideas mature into value creation. Stay tuned for more.

?? Drive measurable AI success: Make the transition from concept to reality

AI has the potential to revolutionize work, bridge the gap between data to insights, and create new business models. But much of its potential remains unrealized. This white paper explores how to tap that potential.

?? Large language model evaluation: A key to GenAI success

Large language models (LLMs) are at the forefront of innovation, particularly in the realm of generative AI (GenAI). Yet, as organizations race to adopt these models, a significant challenge emerges — evaluating whether these LLMs are performing as intended and avoiding undesirable outcomes. Read on to discover how organizations can harness LLMs effectively.?

?? Using AI for requirements analysis: A case study

Leveraging GenAI to create high-quality user stories can lead to shorter lead times and higher quality for requirements analysis. Read this case study to find out how we validated this hypothesis.?

?? Using AI to unleash the potential of preclinical data

Accelerating the way Bayer’s scientists worked with preclinical data to make it more convenient for researchers to find the insights they need. Read the case study here.

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