Generative AI: A World of Opportunities with OpenAI
What is Generative AI?
Generative AI refers to AI algorithms, such as ChatGPT and DALL-E, that generate or create an output that could be a text, photo, video, code, data, or 3D rendering – from the data they're trained on.
How can your business benefit from Generative AI?
OpenAI creates plenty of growth opportunities for businesses willing to embrace innovation. From cost savings and efficiency gains to improved customer experiences and more effective marketing strategies, generative AI can build shortcuts to solving your top challenges.
Generative AI tools produce content in seconds rather than days, content that can be further refined, fact-checked, and personalized. It also has far-reaching implications for industries such as IT and software, where AI-generated code instantly offers accurate, ready-to-use results.
Reid MengeManaging Director, BlackRock Generative AI is the most revolutionary technology since the internet - and it’s here now.
You can even use it to create more technical documents, such as higher-resolution renditions of medical images, saving time and resources and freeing up employees to pursue new business opportunities.
Without any doubt, generative AI will transform the workplace by automating routine tasks, creating new job roles, improving decision-making, and enhancing the customer experience.
Marketing and media are already feeling the impact of generative AI. Gartner expects:
By 2025, 30% of outbound marketing messages from large organizations to be synthetically generated, up from less than 2% in 2022.
By 2030, a major blockbuster film to be released with 90% of the film generated by AI (from text to video), from 0% in 2022.
But the potential of generative AI expands beyond marketing and media, with use cases in drug design, material science, chip design, synthetic data, and part design.
What you need to consider
Just like with any other innovation, generative AI requires us to proceed with caution, as there are still plenty of unaddressed practical and ethical issues, such as:
Confident generation of inaccurate information
Ineffective filters for inappropriate content
Systemic biases
Non-reflected individual company norms and values
Debatable intellectual-property questions
By being aware of the practical and ethical implications of generative AI you can maximize its benefits and build a competitive edge in an increasingly data-driven world.
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