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Have you heard of Generative AI? If you’ve been anywhere on the internet recently, the answer is likely a resounding “yes.” Since ChatGPT took the world by storm in late 2022, Generative AI (or GenAI) has been at the center of the conversation across many institutions, from creative to legal. But with all the noise surrounding this revolutionary new technology, it can easily be misunderstood.
How is GenAI different from traditional AI?AI itself has been associated with the rise of machine learning– the process of using computers to build models that give data-based predictions on things like price inflation or the most profitable new brand to acquire. Meanwhile, GenAI uses data to create something entirely new: images, text, code, and much more.
Why is everyone talking about GenAI? Artificial Intelligence breakthroughs have been steadily happening for years, if somewhat in the background of everyday life, like Google DeepMind solving a decades-long problem by predicting protein structures in 2020. Many of these AI achievements have been momentous, so why has GenAI caused a much greater commotion? Perhaps because GenAI is at our fingertips, ready to appeal to our senses, not just our logic, which has made an immediate and lasting impact on us. Generated images of politicians being arrested or pious religious figures sporting puffy ski jackets are undoubtedly memorable.GenAI-produced content is spreading all over the internet, and the technology is currently being integrated into healthcare, finance, retail, and creative fields, the latter not without controversy. But as other seemingly inescapable trends have petered (see Web3 and the Metaverse), one can wonder whether this is just another NFT-like fad or actually here to stay. For experts at fifty-five, the answer is clear: GenAI is with us for the long haul.
If we can trace the history of traditional AI back to Alan Turing and his seminal “Imitation Game” paper in 1950, GenAI is not that much younger; ELIZA, the first natural language chatbot, was developed in the 1960s at MIT by Joseph Wizenbaum. While these innovations were technically GenAI, outside of the small scope of research projects, the technology required too much data and computational resources to ever be possible. Then came the 2000s, with vast amounts of data and data-based decision-making, followed by the 2010s, with improved computing capabilities that collided with broader accessibility (think cloud computing) and better machine learning models like VAEs and GANs. The latter changed the game by pitting generated data against real data over and over until the machine couldn’t differentiate what was real and what wasn't. With immense computing power, vast amounts of data, and models that can find relationships between variables that humans couldn’t even imagine, the perfect storm was upon us.
In the public eye, the real breakthrough came in the second half of 2022, with the successive releases of MidJourney, Dall-E 2, and, of course, ChatGPT, to name but a few. After the initial novelty wore off in early 2023, the focus turned to how we could use these tools to better our careers and lives. Most eyes immediately turned to creative industries, where GenAI is seen as a huge opportunity but also a big point of contention, as seen in the ongoing actors and writers strike in the United States. This will be a big test of how generative AI fits into our society, for better or worse. Yet creative applications are but a fraction of what GenAI can do – it can be used in other practical ways. GitHub Copilot generates code, for instance, potentially saving hundreds of man-hours for developers, while Aragon can generate LinkedIn-ready headshots from personal selfies, making career building more accessible to all.The marketing technology industry is by far the most enthusiastic early adopter of GenAI, with customers more at ease with the technology than any other, allowing for more room to grow and experiment.At fifty-five, as true data experts, we start by analyzing our clients’ data maturity and organizational needs and develop tailored GenAI solutions from there. While most were just finding their feet with GenAI projects, our martech innovations teams developed tools like BigQuery Assistant, which empowers users to explore data using their own natural language (no need for SQL knowledge), or our GenAI-powered Media Taxonomy Manager, which can detect errors in media campaign taxonomy and propose corrections that can lead to more accurate media reporting.
Over the next few years, fifty-five predicts that GenAI will pop up in change management, product recommendation improvements, data intelligence, and content production, to name just a few, but this evolution is going to take more than just good ideas. It’s going to take good execution. Using public models is one thing, but how will your organization integrate your own unique data and needs to maximize the potential of AI? How will you do this safely and ethically? Organizations need clear plans with expertise around fine-tuning, prompt engineering, and governance. To avoid getting lost in a rather crowded landscape, expertise is crucial. At fifty-five, we strive to reconcile client needs with efficient technology in all its forms, and we partner with them throughout the process for seamless adoption. Plus, finding the right GenAI solution for your needs is hardly buying into the hype blindly: Acumen estimates that by 2032, the GenAI market will be worth over 110 billion dollars. Bloomberg puts it closer to 1 trillion dollars.If you want to know more about how fifty-five can help you integrate GenAI applications that best match your needs, please fill in our contact form for more details.
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