2024: The Year of Gen AI Integration and Transformative Shifts in Business Practices
As we enter the year 2024, it is clear that the world’s fascination with artificial intelligence (AI) is far from over. The advancements in hardware and software have opened up new possibilities for generative AI, and this year will see a widespread integration of gen AI across all sectors. Businesses are recognizing the potential and necessity of gen AI and are actively seeking to embed these technologies into their processes. This transformative shift signifies a move from tentative exploration to confident application, making gen AI a fundamental business practice.
The Impact of AI-Generated Content
The sheer volume of AI-generated content is staggering. Since 2022, AI users have collectively created more than 15 billion images, a number that previously took humans 150 years to produce. This influx of content will have far-reaching ramifications, fundamentally changing the internet as we know it. Historians will view the internet post-2023 as something completely different from what came before, similar to how the atom bomb set back radioactive carbon dating.
Elevating the Standard for All Players
The expansion of gen AI is not just changing the internet; it is also elevating the standard for all players across all fields. Engaging with gen AI is no longer just a novelty; it has become a competitive advantage. In a survey by YouGov, 90% of workers said that AI is improving their productivity. With the right training, employees can complete tasks faster and produce higher-quality work. However, there are still tasks where AI struggles to match human intuition and adaptability, creating what experts term the “jagged frontier” of AI capabilities.
The Decline in Cost and Rise of Model Development
One of the key factors driving the integration of gen AI is the decline in the cost of training foundational large language models (LLMs). Advancements in silicon optimization have made training LLMs more affordable, and alternatives to industry-leaders like Nvidia are emerging. Additionally, new fine-tuning methods, such as Self-Play fIne-tuNing (SPIN), are leveraging synthetic data to train strong LLMs with less human input.
This reduction in cost is opening doors for a wider array of companies to develop and implement their own LLMs. We can expect to see a surge in innovative LLM-based applications over the next few years. Furthermore, there will be a shift from cloud-reliant models to locally executed AI, driven by hardware advancements and the untapped potential of raw CPU power in everyday mobile devices. Small language models (SLMs) will also become more popular, as they are lighter in weight and tailored to specific industries or use cases.
The Rise of Large Vision Models and Large Graphical Models
In 2024, the spotlight will shift from LLMs towards large vision models (LVMs) and large graphical models (LGMs). LVMs tailored to specific image domains, such as semiconductor manufacturing or pathology, show significantly better results than generic LVMs. These models excel in computer vision tasks like defect detection or object location. On the other hand, LGMs stand out in their ability to analyze time-series data, offering fresh perspectives in understanding sequential data often found in business contexts.
Ethical Considerations and Challenges
As gen AI becomes more integrated into business practices, ethical considerations become paramount. Regulation is necessary to prevent past mistakes and negative externalities. However, it may take time to go into effect, leading organizations to take the lead in the regulatory charge. The issue of copyright is also a pressing concern, as AI-generated content raises questions about intellectual property rights.
The Intersection of AI and Geopolitics
The year 2024 is also significant in terms of geopolitics, as it intersects with the biggest election year in human history. AI technology has the potential to interfere with elections through the creation of deepfake videos and the spread of disinformation. The challenge lies in distinguishing authentic content from synthetic and addressing the biases that can influence human perception.
Conclusion
2024 marks the year when gen AI is applied in real, tangible ways. The integration of gen AI across all sectors signifies a transformative shift in business practices. While there are challenges and ethical dilemmas to address, the potential benefits of gen AI are immense. As we navigate this new AI reality, it is crucial to approach it with rigorous ethical consideration and a commitment to responsible implementation. Hold on tight as we embark on this exciting journey into the Year of Gen AI Integration.