Hugging Face CEO Predicts: Six Major Transformations in the AI Industry in 2024!
On November 27th, 2023, Clement Delangue, CEO of Hugging Face, the world’s largest AI open source community, made six predictions for the development of the AI industry in 2024：
These predictions reveal the huge changes that AI technology will bring in 2024, which will have an impact beyond the AI industry and touch all aspects of various fields.
The First Wave of AI Companies Facing Shutdowns
Regarding the first prediction, the sudden departure of OpenAI’s founder has sparked attention and speculation. Clement later clarified that this prediction referred to himself.
Similar situations have occurred before. Jasper AI, once valued at over $1.5 billion, faced negative news in July, including layoffs and an 80% valuation drop. As the “founder of the shell GPT”, Jasper AI’s experience raised concerns about companies relying solely on OpenAI technology.
Despite OpenAI’s powerful technology, creating independent value is now crucial for these companies in the competitive AI industry. Especially after OpenAI’s GPTs launch, AI companies relying on its technology face more challenges.
In this context, Clement’s prediction seems more accurate. If these companies can’t create independent value, a future from a $1 billion valuation to bankruptcy or a low-price acquisition isn’t unimaginable.
This also reminds the AI industry that, in this rapidly evolving field, genuine value and continuous innovation are essential for competitiveness.
Open Source or Closed Source
The AI community is witnessing a growing debate between open-source and closed-source approaches. As technology advances, this controversy is expected to escalate, becoming a key discussion point for industry leaders, open-source AI firms, researchers, and users.
In early 2023, a Google engineer shared a surprising viewpoint, suggesting that OpenAI and Google lacked strong competitive barriers, with open-source AI emerging as a major contender. This sparked widespread discussion and prompted a reevaluation of the ascent of open-source models.
Meanwhile, emerging open-source models claim to rival or even surpass GPT-4 in various domains, signaling a swift rise in the open-source community’s influence within the AI industry.
Closed-source developers argue that distinctions between open and closed models may take 3–5 years to fully manifest due to the financial and time-intensive nature of closed-source model development.
Looking ahead, open-source and closed-source models will coexist, fostering technological advancements through collaboration and competition. Determining the more advantageous development direction necessitates a comprehensive evaluation of technological progress, business models, and user needs.
Of course, we can collectively observe whether this prediction will materialize in 2024.
AI — Driven Scientific Research
AI is reshaping scientific research by revolutionizing the pace and methods of inquiry. In fields like life sciences, astronomy, and physics, machine learning algorithms play a pivotal role in pattern recognition and analysis of vast datasets.
This broad application accelerates scientific advancements, allowing quick analysis of intricate data, uncovering patterns, and offering profound insights. These insights have the potential to foster new scientific breakthroughs, driving progress in related fields.
The Energy and Environmental Costs Caused by AI
Musk’s first-principle thinking prompts a rethink on AI industry energy efficiency.
In a podcast, Musk stressed the need for proportional consideration of intelligent output and energy efficiency, noting substantial room for improvement in current Transformer models and highlighting AI’s high energy dependence.
Research by Alex de Vries at Vrije Universiteit Amsterdam predicts AI server clusters may consume 85 to 134 terawatt-hours annually by 2027.
International reports emphasize AI’s potential resource pressure, projecting its 2027 energy consumption to match Argentina, the Netherlands, or Sweden’s annual electricity usage — equivalent to 0.5% of global energy demand.
This figure has raised awareness that, despite the unprecedented intelligence and convenience brought by AI technology, its high energy consumption may have a significant impact on global resources.
In the future, the sustainability and environmental impact of AI technology will become one of the industry’s focal points, seeking to balance technological advancements with sustainable resource utilization.
AIGC Flooded the Media
Today, AI generation technology for videos and images is advancing at an astonishing pace. In the past year or two, AI-generated content has surged, with a DreamWorks co-founder anticipating a 90% cost reduction in the animation industry within three years.
This forecast underscores AI’s potential in animation creation, revolutionizing a traditionally capital-intensive industry. The significant reduction in costs will enable more creators and teams to venture into animation creation, democratizing the industry.
AI-generated videos, akin to popular short clips, are gaining global traction. These videos, tailored to user demands, drive video creation towards personalization and innovation.
Despite democratization’s benefits, challenges arise. Originality, creativity, and content quality remain paramount in video creation. Balancing cost-effectiveness with maintaining high-quality content is a challenge for the animation industry.
In conclusion, AI’s role in video and image generation is propelling the animation industry into a new era, unlocking possibilities for creators and audiences alike.
AI Will Impact the Labor Market
The impact of AI on the job market is a debated topic, but Hugging Face’s CEO predicts a potential solution. Encouraging more participation in open-source AI development could create jobs, filling the gaps left by AI-replaced roles.
AI’s rapid progress not only captures the attention of the tech industry but is also expected to reshape the nature of existing professions, potentially causing a decline in some traditional industries.
Automated workflows will replace routine jobs, reducing positions, particularly in low-skilled sectors. To mitigate the risk of structural unemployment, society needs to assist the unemployed in adapting to the demands of emerging industries through training and education.
AI’s development creates demand for tech professionals — data scientists, engineers, and algorithm experts. Furthermore, AI will give rise to a range of emerging industries, such as robot manufacturing, autonomous driving, and AI healthcare, thereby creating more relevant positions.
However, the future is unpredictable, and miracles that resolve all issues might occur. Therefore, proactive preparation is essential to prepare for transformative changes in the future labor market.
