Introduction
Artificial general intelligence (AGI) refers to machines that can understand and learn any intellectual task that a human can. AGI is considered the holy grail of artificial intelligence – a single system that can match or exceed human intelligence across a wide range of capabilities.
While we don’t have human-level AGI yet, researchers have made major strides toward this goal. In this article, we’ll explore 10 exciting examples that showcase the potential of artificial general intelligence. Read more about Artificial general intelligence (AGI)
 |
| Advanced AI systems aim for broad general intelligence that rivals human cognition. This image depicts an artificial neural network which allows AI models to process and learn complex patterns underpinning thought and behavior. |
1. Self-Driving Cars
Self-driving car technology relies on artificial intelligence to perceive the environment, interpret situations, and make decisions while driving. Companies like Waymo, GM Cruise, and Tesla are developing AGI that can handle diverse traffic situations using sensors, maps, and navigation programs. Their goal is to eventually create entirely autonomous vehicles that are safer and more convenient than human-operated cars.
2. Robot Dexterity
Robots are getting increasingly adept at human-like manipulation tasks. For example, OpenAI’s humanoid robot hand can solve a Rubik’s Cube, indicating advanced sensory perception, planning, and control algorithms. Similarly, industrial robots are gaining the dexterity needed for delicate surgery applications. As robot intelligence advances, we may see them perform complex dexterous functions better than humans.
3. Game-Playing AIs
Game-playing AIs demonstrate the ability to excel at complex strategy challenges. The AI system AlphaGo developed by DeepMind famously defeated world champion Lee Sedol at the game Go in 2016. This complex board game has far more potential move configurations than chess, requiring exceptional intuition, creativity, and foresight to master. By combining neural networks with tree search algorithms, AlphaGo attained Go skills rivalling seasoned human players.
More recently, DeepMind’s AlphaStar AI defeated two professional StarCraft II players in 2019. This fast-paced video game demands dynamic problem-solving skills to manage resources, coordinate troop positioning, and anticipate opponent moves. AlphaStar’s adaptive play and skills transfer across multi-agent matches exhibit hallmarks of general intelligence.
These game-playing AIs highlight how machines can independently develop mastery and strategy expertise to outperform specialized human talent. Their capacity to conquer games of sophistication through practice and simulated trial-and-error exemplifies the ingenuity artificial general intelligence aims to achieve across many domains.
4. Natural Language Processing
From chatbots to voice assistants, natural language processing (NLP) AI interacts with humans using speech or text. Today’s NLP models can hold conversations, answer questions accurately, summarize long articles, and generate readable content on various topics. While still imperfect, their linguistic skills are rapidly advancing thanks to innovations in neural networks.
5. AI Assistants
Digital assistants like Siri, Alexa, and Google Assistant showcase multi-domain intelligence – they can set alarms, control smart devices, provide information, and more using AGI techniques like intent recognition and task routing. As algorithms and data sets expand, virtual assistants are becoming capable personal aides.
6. AI-Generated Media
AI synthetic media models can generate realistic images, videos, audio, and text. For example, GitHub’s Copilot tool can autocomplete code, Anthropic’s Claude can write persuasive essays, and DALL-E 2 creates original digital art. While concerning if misused, these models display the breadth of abilities that artificial general intelligence aims to achieve.
7. Predictive Analytics
Companies utilize AI predictive analytics to forecast sales, detect fraud, anticipate mechanical failures, and more. These narrow applications still demonstrate how artificial intelligence can comprehend multivariate data sets similar to humans in specialized domains when given the right inputs and training.
8. Drug Development
AI holds promise to accelerate the lengthy process of discovering and testing new medicines. AI drug discovery platforms like Exscientia use simulations and biological data to identify promising compounds and ensure clinical trials are as targeted as possible. With its cross-disciplinary learning capacity, AI can integrate chemistry, genomics, and patient data to enhance how researchers invent and validate new treatments.
9. Medical Diagnosis
AI imaging tools show potential for more accurate diagnosis and treatment planning. By assessing scans and health records, these systems can provide radiologists and doctors with clinical decision support, increased detection of abnormalities, risk assessments for conditions, and suggested treatment pathways. With further medical training, such AI could one day operate in versatile diagnostician roles.
10. Financial Trading
Automated AI trading platforms parse diverse market data, news, and sentiment signals to independently execute lucrative trades. Although specialized, these adaptive programs display the reasoning and predictive capabilities that could eventually lead to artificial general intelligence exceeding human financial experts when given sufficient data.
Conclusion
While still narrow by comparison to human cognition, these examples exhibit domains where AI is developing elevated generalization, reasoning, and learning skills. As researchers connect narrow applications, enhance computational power, and curate bigger data pools, AI systems are expected to handle intellectual challenges as flexibly as humans can. We are still years away from human-level AGI, but the examples above provide a glimpse of the ambitious goals within reach.
