Industry executives and experts share their predictions for 2024. Read them in this 16th annual VMblog.com series exclusive.
AI in 2024: 5 Predictions on the Immediate Future of the AI Revolution
By Kjell Carlsson, head of AI strategy, Domino Data Lab
2023 will likely go down in history as the first year of the AI revolution. New Generative AI discoveries, models, and offerings are appearing daily and nearly every major organization now has an imperative to drive transformative impact with AI. While the long-term effects for humanity will remain shrouded in mystery for decades to come (don’t expect Artificial General Intelligence any time soon), many near-term consequences are straightforward to predict. Based on conversations with leading enterprise AI teams, expert data scientists, industry observers, and triangulating across the latest market developments these are our predictions for AI in 2024.
1. Predictive AI Strikes Back: Generative AI sparks a traditional AI revolution
The new hope around GenAI drives interest, investment, and initiatives in all forms of AI. However, the paucity of established GenAI use cases, and lack of maturity in operationalizing GenAI means that successful teams will allocate more than 90% of their time to traditional ML use cases that, despite the clear ROI, had hitherto lacked the organizational will.
2. Malignant GenAI Misinformation is Meh: Deepfakes for fraud and election misinformation don’t destroy society
Yes, scams are more convincing, fraud cases rise, and fake news proliferates. However, after some high-profile cases, in 2024 we’ll see that behaviors shift, skeptical individuals recognize the new tell-tale signs and institutions find easy fixes to protect their businesses. Voters are so entrenched in their political affiliations that few will be swayed by the news anyway. Human behavior, it turns out, is amazingly consistent.
3. GPUs and GenAI Infrastructure Go Bust
Gone are the days when you had to beg, borrow and steal GPUs for GenAI. The combination of a shift from giant, generic LLMs to smaller, specialized models, plus increased competition in infrastructure and also quickly ramping production of new chips accelerated for training and inferencing deep learning models together mean that scarcity is a thing of the past. However, investors don’t need to worry in 2024, as the market won’t collapse for at least another year.
4. Forget Prompt Engineer, LLM Engineer is the Least Sexy, but Best Paid, Profession
Everyone will need to know the basics of prompt engineering, but it is only valuable in combination with domain expertise. Thus the profession of “Prompt Engineer” is a dud, destined, where it persists, to be outsourced to low-wage locations. In contrast, as GenAI use cases move from PoC to production, the ability to operationalize GenAI models and their pipelines becomes the most valuable skill in the industry. It may be an exercise in frustration since most will have to use the immature and unreliable ecosystem of GenAI point solutions, but the data scientists and ML engineers who make the switch will be well rewarded.
5. GenAI Kills Quantum and Blockchain
The unstoppable combination of GenAI and Quantum Computing, or GenAI and Blockchain? Not! GenAI will be stealing all the talent and investment from Quantum and blockchain, kicking quantum even further into the distant future and leaving blockchain stuck in its existing use cases of fraud and criminal financing. Sure, there will be plenty of projects that continue to explore the intersection of the different technologies, but how many of them are just a way for researchers to switch careers into GenAI and blockchain/quantum startups to claw back some of their funding?
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ABOUT THE AUTHOR
Dr. Kjell Carlsson is the head of AI strategy at Domino Data Lab where he advises organizations on scaling impact with AI. Previously, he covered AI as a Principal Analyst at Forrester Research where he advised leaders on topics ranging from computer vision, MLOps, AutoML, and conversation intelligence to next-generation AI technologies. He has spoken in countless keynotes, panels, and webinars, and is frequently quoted in the media. Dr. Carlsson is also the host of the Data Science Leaders podcast and received his Ph.D. from Harvard University.
