The world of artificial intelligence (AI) is buzzing with excitement and anticipation. New breakthroughs like ChatGPT have captivated the public’s imagination, but what does the future hold for AI in terms of practical applications and real business success? Are we on the cusp of a true paradigm shift, or will AI remain a sporadic phenomenon overshadowed by the noise? To understand where AI is heading, we can draw valuable lessons from the preceding step-change advance in technology: the Big Data era.
The exponential increase in online traffic can be traced back to the late 1990s and early 2000s when the internet was widely used. This flurry of online activity resulted in a deluge of log data, which may be used to learn more about user habits and the efficiency of software. It soon became clear that these logs were of great help in determining the root causes of software failures and the motivating factors behind desired behaviors like completing a purchase.
As the internet continued to expand, the volume of log files grew exponentially. Many recognized the potential of this data, but the question remained: could we effectively analyze and extract sustainable value from it, especially when the data was scattered across various ecosystems?
One company that successfully harnessed the power of big data is Google. Its search engine consistently delivered excellent results, building trust among users. However, Google’s ability to provide search at scale and develop additional products relied on the monetization enabled by Adwords. Today, we take for granted the ability to find information in seconds, receive turn-by-turn directions, collaborate on documents, and store data in the cloud — all made possible by Google’s data-driven approach.
Google’s success story paved the way for other industry giants, such as IBM and Snowflake, who built successful empires by helping organizations capture, manage, and optimize data. What initially seemed like a confusing mass of information ultimately yielded tremendous financial returns. AI must follow a similar path to unlock its full potential.
The emergence of generative AI models has ushered in a new era in the field of artificial intelligence. Thanks to big data, vast amounts of natural language text, like English or Chinese, are available for analysis. Researchers have developed software capable of reading and learning from this text, culminating in the arrival of ChatGPT in late 2022. This breakthrough has sparked curiosity and even led some to wonder if machines have finally come alive.
We find ourselves at a pivotal moment in the history of technology, one that may have profound implications for humanity. However, the current hype surrounding AI mirrors the initial excitement of the Big Data era. The key question we must address is: How can AI deliver sustainable business outcomes and bring about a genuine step-change?
To achieve workable AI, we must focus on three essential elements: generative AI models, building trust, and developing killer applications that provide tangible value.
Generative AI models are unique in their wildness and present challenges due to their unexpected behavior. Unlike traditional procedural software, we can’t simply fix bugs or tweak code. These models are built by other software, comprising countless equations that interact in ways beyond human comprehension. We don’t always know which weights between neurons need adjustment to prevent undesirable outcomes.
Improvement in generative AI models comes through feedback and continuous learning. Vigilance in monitoring data quality and algorithm performance is crucial to prevent hallucinations that might alienate potential customers in high-stakes environments where financial decisions are made.
Trust is essential for businesses to fully embrace AI. Governance, transparency, and explainability are key factors in fostering confidence. Real regulation, with teeth, must be in place to ensure companies can understand AI’s actions and address any missteps effectively. Industry leaders have begun taking steps to create guardrails, but the rapid adoption of smart regulation is needed.
Furthermore, any media generated by AI, whether text, audio, image, or video, should be clearly labeled as “Made with AI” when used commercially or politically. Consumers deserve to know the origins of such content, and this labeling practice would provide transparency and manage expectations. Surprisingly, many AI-generated products may exceed consumer expectations in terms of quality.
Numerous companies have emerged, offering applications of generative AI across various domains, from marketing collateral creation to music composition and even drug discovery. The simple prompt of ChatGPT has the potential to surpass the search engine of the Big Data era. However, the true power of AI lies in exploring other applications that can revolutionize user experiences and business performance.
Finding these killer apps will require experimentation and a focus on creating a step-change platform. Companies that succeed in this endeavor will break through innovation barriers, continuously building trust in their AI models while developing powerful applications with sound monetization strategies.
Just as big data went through the noise and nonsense cycle before finding its true value, AI will likely experience a similar journey. While it may take time and iterations, focusing on the tenets of workable AI will propel this discipline forward. By embracing generative AI models, building trust through regulation and transparency, and developing killer applications, businesses can unlock the transformative potential of AI.
Florian Douetteau, CEO of Dataiku, emphasizes the importance of these principles. As the AI landscape evolves, it is crucial for organizations to navigate this new frontier strategically and embrace workable AI solutions that align with their business objectives.
The AI revolution is upon us, and the practical applications of workable AI hold immense promise for businesses across industries. By drawing on the lessons learned from the Big Data era and leveraging generative AI models, building trust, and developing killer applications, businesses can position themselves at the forefront of this technological shift.
As AI continues to evolve, it is crucial for organizations to stay informed, adapt to emerging trends, and embrace the potential of workable AI. By doing so, they can unlock new opportunities, improve operational efficiency, and create transformative experiences for their customers. The future belongs to those who are willing to embrace the power of workable AI and leverage it to drive their success.
First reported on VentureBeat