Olga Ivankov In the last few years, there’s nothing that has captured the imagination and spurred innovation quite like Artificial Intelligence (AI). From its conceptual origins in the early 20th century to its current status as a cornerstone of modern technology, AI’s journey is fascinating. In this article, we talk about the top AI trends in the industry that you should watch out for in 2024. We will also talk about a brief history of modern AI which traces its roots from the theoretical frameworks laid by pioneers like Alan Turing.
How it Started?
All of it begins in the 1950s, a decade marked by the birth of AI as a distinct field of study, where the term itself was coined and the foundational goals were set. Then comes the 60s and 70s, where early enthusiasm faced the harsh realities of technological limitations, leading to the first of the infamous AI Winters.
As we move into the 1980s and 90s, we witness the resurgence of AI, fueled by the advent of expert systems and the paradigm shift towards machine learning and data-driven approaches. The triumphs of IBM’s Deep Blue and Watson herald a new age where AI begins to challenge and outperform human intelligence in specific domains.
The 21st century ushers in an era where AI becomes intertwined with our daily lives. The 2010s, in particular, are a testament to the rapid advancements in deep learning, leading to revolutionary applications from autonomous vehicles to AI assistants that have become household staples. Yet, as we step into the 2020s, the narrative of AI takes a conscientious turn, emphasizing ethics, fairness, and the need for governance in a world increasingly driven by intelligent machines.
A Brief History and Journey Of AI
- 1950s: Birth of Artificial Intelligence
- 1950: Alan Turing proposes the Turing Test to evaluate a machine’s ability to exhibit intelligent behavior equivalent to, or indistinguishable from, that of a human.
- 1956: The term “Artificial Intelligence” is coined at the Dartmouth Conference, marking the official birth of the field. Participants, including John McCarthy and Marvin Minsky, are optimistic about the future of AI.
- 1960s-1970s: Early Enthusiasm and First AI Programs
- Early 1960s: Development of AI programming languages like LISP (created by John McCarthy in 1958) and Prolog.
- 1966: ELIZA, an early natural language processing program, is created at MIT by Joseph Weizenbaum, demonstrating the superficial ability of computers to understand human language.
- Late 1960s: AI research is heavily funded by the United States Department of Defense and becomes a major focus in computer science.
- 1970s-1980s: AI Winter and Expert Systems
- 1970s-1980s: Two major “AI Winters” occur, periods marked by a lack of funding and interest in AI research, due to inflated expectations and subsequent disappointments.
- 1980s: A revival in AI interest and funding, driven by the commercial success of expert systems, which are AI programs that mimic the decision-making abilities of a human expert.
- 1990s: The Rise of Machine Learning
- 1997: IBM’s Deep Blue defeats world chess champion Garry Kasparov, showcasing the potential of AI in specific domains.
- Late 1990s: The focus in AI shifts towards data-driven approaches, and machine learning becomes increasingly popular.
- 2000s: Big Data and Advanced Algorithms
- 2006: The term “deep learning” is introduced to the AI community by Geoffrey Hinton, marking a renewed focus on neural network research.
- 2011: IBM’s Watson wins the game show “Jeopardy!”, demonstrating advanced natural language processing and analytics.
- 2010s: Deep Learning Breakthroughs and Mainstream AI
- 2012: AlexNet, a deep neural network, wins the ImageNet Large Scale Visual Recognition Challenge, significantly reducing error rates in image classification and revolutionizing the field.
- 2014: Google acquires DeepMind; subsequent development of AlphaGo, which defeats world champion Go player Lee Sedol in 2016.
- Late 2010s: AI becomes a mainstream technology, with virtual assistants like Siri, Alexa, and Google Assistant becoming household names.
- 2020s: AI Ethics and Advanced Generative Models
- 2021: Introduction of GPT-3 by OpenAI, an advanced language model capable of generating human-like text.
- 2023: Increased focus on AI ethics, fairness, and governance as AI technologies become more pervasive in society.
- 2024: Development and widespread use of more sophisticated and specialized AI models tailored for specific industries and applications.
Top AI Trends of 2024
In 2024, AI has come a long way and it is inching towards becoming mainstream. There are multiple innovative trends to watch out for.
Customized Generative AI Models
2024 marks a shift towards customized AI models, especially in specialized fields like healthcare, finance, and legal sectors. Unlike the one-size-fits-all approach of earlier models like ChatGPT, these tailored models are designed to meet specific industry needs. This customization allows for improved performance and enhanced security and privacy. For instance, a healthcare AI model can understand complex medical terms, offering more accurate diagnoses and treatment suggestions. Companies are now investing more in developing these niche models to provide better, more specialized services.
AI and Machine Learning Talent Demand
This year, the demand for AI and machine learning talent has skyrocketed. Businesses are looking for professionals who not only understand AI theories but can also apply them in real-world settings. Skills in AI programming, data analysis, and MLOps (Machine Learning Operations) are particularly sought after. This trend reflects the growing integration of AI in various industries, from tech companies to healthcare systems. Educational institutions and online platforms are responding with more courses and programs to train the next generation of AI experts.
AI in Film and Marketing
AI’s influence in the film and marketing sectors has been remarkable in 2024. Companies like Runway are developing generative video models that are getting attention from giants like Disney and Paramount. This technology is revolutionizing how movies are made, from special effects to language dubbing. In marketing, tools like Synthesia are creating AI-generated avatars for advertisements, used by many Fortune 100 companies. This trend shows the expanding role of AI in creative industries, where it’s enhancing the way content is produced and distributed.
AI-Generated Election Disinformation
A concerning trend in 2024 is the rise of AI-generated disinformation in elections. With AI tools becoming more accessible and sophisticated, it’s becoming difficult to distinguish between real and fake content. This has significant implications for politics and public opinion. Countries like Argentina and Slovakia have already experienced the impact of such AI tools in their elections. It highlights the urgent need for better detection methods and ethical guidelines in the use of AI for public information.
AI Governance and Compliance
As AI becomes more prevalent in enterprises, there’s an increased focus on governance and compliance. Organizations are proactively investing in these areas to align with regulations and reduce risks related to data privacy and intellectual property. This trend is a response to the growing complexity of AI systems and their potential impact on privacy and security. Companies are not only looking to comply with current laws but also anticipating future regulations, ensuring their AI practices are both ethical and legal.
Development of More Autonomous Agents
In 2024, we are seeing a move towards more autonomous AI agents. These systems require less human input, understanding and executing tasks based on higher-level instructions. For example, instead of giving detailed commands to an AI for each step, users can now just outline the end goal. This evolution in AI design is making interactions with AI more natural and efficient, allowing for more complex and creative uses in various fields.
Advancements in Multimodal and Open AI Models
Multimodal AI models, which combine different types of data like text, images, and audio, are becoming more common. These models, such as Google’s Gemini, show the potential for AI to understand and interact in more human-like ways. Additionally, the proliferation of open source models is fostering a competitive environment where more advanced and specialized AI tools are being developed. This trend is leading to more innovative and diverse applications of AI across different sectors.
Robots that Multitask
2024 is witnessing an exciting development in robotics, inspired by advances in generative AI. Instead of having robots programmed for singular, specific tasks, we’re moving towards creating general-purpose robots capable of multitasking. This change mirrors the evolution in AI from multiple small models to single, large models like GPT-3, which can handle diverse tasks like solving coding problems or writing scripts. For example, a robot in the future might not just be limited to flipping pancakes but could also open doors, assist in homes, or perform various tasks in industrial settings. This trend showcases the potential for more versatile and adaptable robotic systems, which could revolutionize how we think about automation in our daily lives and industries.
AI Regulation is on its Way
As AI technologies become more integrated into our society and industries, the need for comprehensive AI regulation becomes increasingly vital. In 2024, we are seeing significant movements in this area, with countries like Canada, the European Union, and the United States introducing legislations like the Artificial Intelligence and Data Act (AIDA), the AI Act, and the Algorithmic Accountability Act, respectively. These regulatory efforts aim to address critical issues such as data privacy, fairness, transparency, and the ethical use of AI. This trend indicates a growing recognition of the potential impact of AI on various aspects of society and a concerted effort to ensure its safe and responsible deployment.
Generative AI and Its Controversies
Generative AI continues to stir up controversy in 2024, especially in creative fields. Its ability to generate text, images, videos, and music has raised questions about academic integrity, misinformation, and the displacement of jobs in creative professions. For instance, AI systems created more than 15 billion images last year, surpassing the entire history of photography. This explosion of AI-generated content is leading to concerns about the authenticity of online content and the potential for misinformation. Additionally, there’s growing apprehension about the impact of AI on creative jobs and the reliability of AI systems trained on machine-generated content. This trend highlights the need for a balanced approach to leveraging AI in creative processes, ensuring that it complements rather than replaces human creativity.
Public Perception and Trust in AI
In 2024, the public’s perception and trust in AI are undergoing significant shifts. Research is being conducted to understand the changing attitudes towards AI, its regulation, development, and the perceived economic impacts on individuals and society. For example, surveys across multiple countries are exploring how people feel about AI technologies like ChatGPT and their use by governments. This trend is critical as it influences how AI is integrated into various aspects of our lives and policies. Understanding and addressing public concerns about AI is essential for its ethical and effective adoption in society.
