The current hype about building massive generative AI models with massive hardware investment is just one aspect of AI. This episode of the Tech Field Day podcast features Frederic Van Haren, Karen Lopez, Marian Newsome, and host Stephen Foskett taking a different perspective on the larger world of AI. Our last episode suggested that AI as it is currently being hyped is a fad, but the bigger world of AI is absolutely real. Large language models are maturing rapidly and even generative AI is getting better by the month, but we are rapidly seeing the reality of the use cases for this technology. All neural networks use patterns in historical data to infer results, so any AI engine could hallucinate. But traditional AI is much less susceptible to errors than the much-hyped generative AI models that are capturing the headlines today. AI is a tool that augments our knowledge and decision making, but it doesn’t replace human intelligence. There is a whole world of AI applications that are productive, responsible, and practical, and these are most certainly not a fad.
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Look Beyond the Hype: AI is Real!
The current hype surrounding massive generative AI models and the substantial hardware investments they require is just one facet of the broader AI landscape. While the media often focuses on these large language models and the billions of dollars spent on supercomputers to support them, AI encompasses much more than this. The reality is that AI is not a fad – it is a multifaceted tool that is rapidly evolving and finding practical applications across various industries.
AI can be divided into two main phases: training and inference. The training phase involves using extensive datasets and significant computational power, often requiring numerous GPUs, to build models. This phase is typically handled by a few large organizations with the resources to manage such complexity. On the other hand, the inference phase, where these models are applied in real-world scenarios, is less resource-intensive and more accessible to consumers and enterprises. This division highlights that while the development of AI models may be complex and resource-heavy, their application can be straightforward and widely beneficial.
The demand for AI is driven by consumers and enterprises seeking to simplify and enhance their operations. This demand ensures that AI is not a passing trend but a technology with staying power. However, the term “AI” is often used as a catch-all phrase, leading to confusion about its true capabilities and applications. For instance, generative AI, which includes models like ChatGPT, is just one type of AI. These models can produce impressive and convincing outputs but are also prone to errors and “hallucinations”—generating incorrect or nonsensical information based on the data they were trained on.
Traditional AI, which has been in use for years in various industries, is generally more reliable and less prone to such errors. Applications of traditional AI include anomaly detection in manufacturing, video analysis in retail, and security. These use cases demonstrate AI’s practical and responsible applications, which are far from being a fad. For example, AI is used in agriculture to monitor crop health and improve yields, a task that does not require the massive computational resources associated with generative AI.
The perception of AI as a fad is partly due to the overhyped and sometimes half-baked applications of generative AI that capture public attention. These applications often promise more than they can deliver, leading to skepticism. However, the underlying technology of AI is robust and continues to mature, offering valuable solutions in various fields. The speed of innovation in AI is accelerating, and while this can lead to unrealistic expectations, it also means that practical applications are continually emerging.
AI is a tool that augments human knowledge and decision-making rather than replacing it. This distinction is crucial for understanding AI’s role in our lives. For instance, AI can assist in generating documentation, analyzing code, or improving search capabilities within an organization. These applications enhance productivity and efficiency without replacing the need for human oversight and expertise.
The trust factor in AI is also significant. As AI becomes more integrated into everyday technologies, it is essential to market and implement it responsibly. This includes ensuring that AI systems are transparent, reliable, and used ethically. For example, non-generative AI systems, which do not generate new content but analyze existing data, are generally more trustworthy and less prone to errors.
AI is not a fad; it is a powerful tool with a wide range of applications that are already making a significant impact. While the hype around generative AI may lead to some disillusionment, the broader field of AI continues to offer practical, responsible, and valuable solutions. As AI technology evolves, it will become even more integrated into various aspects of our lives, enhancing our capabilities and helping us solve complex problems. The key is to approach AI with a clear understanding of its strengths and limitations, ensuring that it is used to augment human intelligence and decision-making responsibly.
Podcast Information
Stephen Foskett is the Organizer of the Tech Field Day Event Series, now part of The Futurum Group. Connect with Stephen on LinkedIn or on X/Twitter.
Frederic Van Haren is the CTO and Founder at HighFens Inc., Consultancy & Services. Connect with Frederic on LinkedIn or on X/Twitter and check out the HighFens website.
Karen Lopez is a Senior Project Manager and Architect at InfoAdvisors. You can connect with Karen on X/Twitter or on LinkedIn.
Marian Newsome is the CEO and Founder of Ethical Tech Matters and a cohost of the Tech Aunties Podcast. You can connect with Marian on LinkedIn. Listen to the Tech Aunties Podcast.
Thank you for listening to this episode of the Tech Field Day Podcast. If you enjoyed the discussion, please remember to subscribe on YouTube or your favorite podcast application so you don’t miss an episode and do give us a rating and a review. This podcast was brought to you by Tech Field Day, home of IT experts from across the enterprise, now part of The Futurum Group.
