What is Generative AI?
Generative artificial intelligence (AI) encompasses algorithms, like ChatGPT, designed for producing diverse content forms such as audio, code, images, text, simulations, and videos. Recent advancements in this field hold the promise of fundamentally transforming our approach to content creation.
Generative AI systems fall under the broad
category of machine learning, and here’s how one
such system—ChatGPT—describes what it can do:
Ready to take your creativity to the next level?
Look no further than generative AI! This nifty form
of machine learning allows computers to generate
all sorts of new and exciting content, from music
and art to entire virtual worlds. And it’s not just for
fun—generative AI has plenty of practical uses too,
like creating new product designs and optimizing
business processes. So why wait? Unleash the
power of generative AI and see what amazing
creations you can come up with!
Generative AI systems
GPT stands for generative pretrained transformer
What are ChatGPT and DALL-E?
ChatGPT
This is why ChatGPT—where GPT stands for generative pretrained transformer—is currently capturing significant attention. Functioning as a free chatbot, it can generate responses to nearly any question posed to it. Developed by OpenAI and released for public testing in November 2022, it has swiftly gained recognition as the premier AI chatbot. Its popularity is evident, with over a million users signing up within just five days. Enthusiastic users showcase the chatbot's capabilities in producing computer code, college-level essays, poems, and even decent jokes.
Notwithstanding the admiration from some, there's a segment of individuals in various content creation professions, from advertising copywriters to tenured professors, who are apprehensive about the impact of ChatGPT. While there is a prevailing fear associated with ChatGPT and AI in general, it's important to acknowledge that machine learning holds immense potential for positive contributions. Over the years, widespread adoption of machine learning has demonstrated its impact across various industries, achieving notable milestones in areas like medical imaging analysis and high-resolution weather forecasts.
McKinsey survey shows that AI adoption has more than doubled over the past five years, and investment in AI is increasing apace. It’s clear that generative AI tools like ChatGPT and DALL-E (a tool for AI-generated art) have the potential to change how a range of jobs are performed.
What kinds of problems can a
generative AI model solve?
You may have noticed that generative AI tools, such as ChatGPT, are capable of generating an endless stream of entertainment. Beyond personal use, there's a clear business opportunity. Generative AI tools excel at swiftly producing a diverse range of credible written content, adjusting in response to feedback to better suit the intended purpose. This has far-reaching implications across various industries, from IT and software companies benefiting from AI-generated code to organizations seeking effective marketing copy to revolutionising legal landscape. Essentially, any entity requiring clear written materials stands to gain. Generative AI can also be leveraged to generate more technical content, like higher-resolution versions of medical images. The time and resources saved in this process empower organizations to explore new business opportunities and create additional value.
It's worth noting that developing a generative AI model is a resource-intensive endeavor, making it a feasible option only for the largest and most well-resourced companies. For companies looking to harness generative AI, there's the choice of using pre-built models "out of the box" or fine-tuning them for specific tasks. For instance, if you need slides prepared in a particular style, you could instruct the model to "learn" headline writing norms based on slide data, then provide it with the necessary information to generate appropriate headlines.
