At the 2024 Consumer Electronics Show (CES), we attended the panel 2024: The AI Inflection Point – Entertainment, Internet & Media, which explored the current state of artificial intelligence (AI), its impact on businesses, and the potential it holds for the future. The experts were unanimous in their belief that 2024 marks a crucial inflection point for AI, ushering in the third wave of transformative technologies.
The panel identified three waves of AI tech:
Analog–to–digital content:
The first wave set the stage for digital transformation, pitting incumbents against newcomers. The implications were profound, as industries grappled with the shift from analog to digital content.
Introduction of deep learning:
The second wave showcased the power of deep learning, exemplified by IBM’s Watson conquering Jeopardy. This phase laid the groundwork for the current state of AI.
Generative AI:
The third wave focuses on the ability to analyze vast amounts of unlabeled data. Models trained with enormous datasets enable GenAI to perform a multitude of tasks exceptionally well. The emphasis moving forward is to better integrate data to tailor AI models to specific use cases.
From hype to reality
As of this year, GenAI has transitioned from the peak of hype in 2023 to a reality-driven state. This shift demands trust, as businesses look for ways to integrate AI into their core operations. Contrary to fears of job replacement, AI is becoming a tool integrated into workflows, augmenting human capabilities rather than replacing them.
The media space has experienced rapid development. Panel experts cited approximately 1800 companies involved in GenAI, ranging from established giants like Adobe to startups like Runway that are revolutionizing video editing.
Companies are also using GenAI to bridge the knowledge gap between data scientists and front-end business users, enabling more informed decision-making. Uncovering these use cases is driving this third wave.
Challenges and opportunities we’ll be tackling in 2024
- Data transparency: Pending legislation in 2024 emphasizes the need for transparency in AI models’ training processes. Bigger models are no longer blindly accepted as better; trust hinges on understanding how the model has been trained. This is driving the need for a “nutrition label” of sorts for data used in the model.
- Security concerns: The dark side of AI emerges as bad actors exploit GenAI for negative purposes. Companies must guard against code hiding in models, waiting to be activated for malicious intent. Opportunities will arise for companies specializing in data cleanliness, similar to the rise of virus protection companies decades ago.
- Digital twins: Combining new technologies, digital twins offer innovative opportunities. In manufacturing, digital twins allow for real-time monitoring and decision-making, knowing with incredible accuracy the moment quality begins to drift. But with digital twin technology, privacy concerns arise when it comes to who has access to these digital replicas, such as a digital twin of your home that is produced from existing smart home equipment (i.e., robot vacuum maps).
As we navigate the third wave of AI, the panel agreed, businesses must embrace GenAI with trust and transparency. The potential for positive change is immense, but so are the challenges. By understanding the current landscape, we can better prepare for the transformative journey that lies ahead.
For more insights touched on by this panel, check out the analysis of CEO perspectives on AI at IBM.com.
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