Applications of generative AI for publishers

Rather, organisations will need to be able to choose the right model for the right job. Then, customers will need to be able to securely customise these models with their own data. Generative AI tools not only produce written language and images, but also churn out computer code. Goldman Sachs is conducting a “proof of concept” for assisted coding tools powered by generative AI. That’s likely in part because AI is a catch-all phrase for cognition-like capabilities , including everything from computer vision and natural language processing to deep learning and neural networks.

Generative AI refers to a category of artificial intelligence techniques and algorithms that are designed to generate new data or content that is similar to what it has been trained on. Examples of generative AI include image and video synthesis, text generation, music composition etc.

To read more, please download this free white paper. In 2022, Thomson Reuters created an AI platform to speed its machine learning innovation by implementing common data and model governance, and to standardize its model release process. Even as industry peers JPMorgan, Citigroup, Deutsche Bank, and Bank of America have reportedly blocked their employees from using generative AI, Goldman Sachs is putting the technology in the hands of its programmers to determine its early value. CIO Marco Argenti explains that while it wouldn’t be wise to immediately trust all important processes to AI, it’s imperative that businesses try to envision its potential.

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The potential of generative AI in revolutionising the UK’s social care sector is immense. By enhancing personalisation, improving resource allocation, and enabling proactive care, AI is promising a future where social care is more efficient, effective, and person-centred. As we continue to navigate this new frontier, the goal must be to harness the power of AI to enrich the lives of those who rely on social care, never losing sight of the human element that lies at the heart of this vital sector. In the realm of elderly care, AI has made it possible to generate predictive models that assess risks such as falls or health deterioration.

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January then saw a US class action against three AI image generators alleging copyright violations. This was followed shortly by proceedings brought by Getty Images in the UK and US against the creators of Stable Diffusion. Between them these lawsuits raise questions regarding the genrative ai use of training data protected by copyright to train AI systems and the relationship in, in copyright terms, between the training data and outputs from generative AI systems. In May 2022, most of us were unaware of the potential of generative Artificial Intelligence (AI) tools.

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Generative AI and the need for human expertise

We’d seen AI generated content in presentations, but they always seemed to recycle the same examples. Generative AI is also having a transformative impact on the delivery of mental health services. AI-based chatbots can generate empathetic responses to individuals seeking mental health support, providing immediate and non-judgemental assistance. While these tools cannot replace professional psychological help, they can serve as a valuable first line of support, accessible anytime and from anywhere.

The immense potential of Generative AI lies in its ability to solve pervasive problems across industries, paving the way for unprecedented efficiency, accuracy, and innovation. Unsurprisingly financial services (FS) organisations are moving quickly to harness this potential as users or developers of such tools. Many are trying to understand what this technology really is, what it can and can’t do and how it might be useful for them.

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