Generative AI has huge potential, but it also faces problems. If generative AI creates information that is not factually accurate in response to a user request – resulting in so-called hallucinations – it can have a big impact on users. Relying on large language model (LLM) training data on its own is not enough to prevent […]
Streamlining Your Data Needs for Generative AI
Companies are investing heavily in AI projects as they see huge potential in generative AI. Consultancies have predicted opportunities to reduce costs and improve revenues through deploying generative AI – for example, McKinsey predicts that generative AI could add $2.6 to $4.4 trillion to global productivity. Yet at the same time, AI and analytics projects have historically […]
Running Generative AI in Production – What Issues Will You Find?
As your data projects evolve, you will face new challenges. For new technology like generative AI, some challenges may just be variations on traditional IT projects like considering availability or distributed computing deployment problems. However, generative AI projects are also going through what Donald Rumsfeld once called the “unknown unknowns” phase, where we are discovering […]
Getting Ahead of Shadow Generative AI
Like any new technology, a lot of people are keen to use generative AI to help them in their jobs. Accenture research found that 89% of businesses think that using generative AI to make services feel more human will open up more opportunities for them. This will force change – Accenture also found that 86% […]
How To Build Autonomous Agents – The End-Goal for Generative AI
There are lots of numbers being thrown around about the potential of generative AI (GenAI). From trillions of dollars added to the global economy, to significant percentages of work being driven by GenAI, the big picture looks great. But turning this potential into reality is where the hard work starts. Autonomous agents are software programs […]