What Is Artificial Intelligence?
As opposed to the intelligence of humans or other animals, artificial intelligence (AI) is the intelligence of machines or software. Founded as an academic discipline within computer science in 1956, AI has been a research subject and a source of technological innovation for decades.
While AI-based tools have been around for quite some time, the next generation of technologies is challenging our understanding of learning and cognition, according to researchers at Microsoft Research.
In 1950, British mathematician Alan Turing published a seminal paper considering artificial intelligence, posing the question: Can machines think?
According to Turing, his ‘machines’ would be capable of making decisions, observing the results of their behaviours, learning by rewards and punishments, obeying commands, thinking, writing, and remembering. The test proposed by Turing – the Imitation Game – measured an AI system’s ability to imitate human behaviour.
Turing predicted that by 2000, an interrogator would not have more than a 70% chance of making the correct identification after five minutes of questioning. Although more than two decades late on the prediction, OpenAI’s GPT-4 and Google’s LaMDA have beaten Turing’s imitation game. The two LLMs have since sparked debate on new tests to test AI intelligence.
How Is AI Different From GenAI & Other AI-Based Tools
Artificial intelligence (AI) encompasses all intelligent systems and machines that mimic human capabilities, including learning, problem-solving, and decision-making. On the other hand, generative AI (GenAI) and other AI-based tools are all subsets of AI.
There are also differences in terms of functionality and data requirements. While AI analyses and responds, GenAI creates new things. As such, AI needs extensive, clean and specific data for specific tasks, while GenAI thrives on vast, general datasets. By learning on large datasets, GenAI algorithms can ‘learn’ how to make connections between data points (words, for instance) and generate humanlike responses.
Other AI-based tools address particular use cases by using technologies that enable AI. For instance, a meeting assistant (Firefly) is an AI-based application specialising in natural language processing (NLP) and text-to-speech automation.
What Are Some Of The Common Applications Of AI?
AI has rapidly evolved to capture several critical aspects of our day-to-day lives. AI is commonly used in:
- Ecommerce
- Personalised Recommendations: AI-based tools can analyse user behaviour and preferences to suggest relevant products, which can help an ecommerce platform boost customer engagement and sales.
- Dynamic Pricing: Based on demand, competitor analysis and other factors, AI algorithms adjust product prices in real time. Flipkart and Amazon, along with other major ecommerce players, use AI-based models to implement dynamic pricing.
- Healthcare & Medicine
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- Medical Diagnosis: AI algorithms analyse medical images and data to assist in diagnosis, disease progression prediction, and personalised treatment plans.
- Drug Discovery and Development: AI accelerates drug discovery by analysing vast datasets of molecules and predicting potential candidates for further research.
- Robot-assisted Surgery: AI-powered robots assist surgeons with increased precision and minimally invasive procedures, leading to faster recovery times.
- Customer Service & Support
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- Chatbots And Virtual Assistants: AI-powered chatbots handle basic inquiries and provide 24/7 customer support, freeing human agents for complex issues. Many customer-facing startups in India have introduced AI-based chatbots, leaving human agents for situations where AI can’t help.
- Sentiment Analysis And Feedback Management: AI tools can be used to analyse customer feedback and reviews to identify trends and improve customer satisfaction.
- Transportation And Logistics
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- Route Optimisation And Traffic Management: AI algorithms optimise delivery routes and predict traffic patterns to improve logistics efficiency and reduce congestion. Several logistics startups in India are now using AI-based route optimisation to deliver goods faster and more efficiently.
- Autonomous Vehicles: Self-driving cars and drones powered by AI are revolutionising transportation, aiming for safer and more efficient travel.
- Predictive Maintenance For Vehicles: AI tools can be used to analyse car sensor data to predict potential problems and schedule preventive maintenance, ensuring safety and reducing breakdowns. Major carmakers like BMW are already offering AI tools for predictive maintenance.
- Entertainment And Media
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- Content Recommendation: AI algorithms are used by just about every streaming service to personalise movie, music and book recommendations based on user preferences and viewing history.
- Special Effects & Animation: AI tools are regularly used to create realistic special effects and animation in movies and video games.
What Are Some Of The Concerns Regarding AI?
While AI continues to penetrate deeper into our lives, there are several genuine concerns regarding the continued use of AI and its impact on the world.
- Jobs: A genuine consequence of AI-based automation is that it can render human efforts redundant. One of the recent examples is Paytm, which saw hundreds of employees lose their jobs due to the increased use of AI-based tools.
- No Privacy: AI systems rely on vast amounts of personal data, begging the question of privacy in a world where large amounts of user data are being processed by AI for profit-making purposes. This tendency also opens up AI tools to malicious actors, who can attack companies using AI-based tools and steal highly sensitive data.
- Lack Of Transparency: Complex AI algorithms are essentially a ‘black box’, making explaining how they arrive at certain decisions is hard. This lack of transparency can erode trust in AI and lead to unfair or biased outcomes.
- Existential Risks: Experts have raised concerns about the potential for advanced AI to surpass human intelligence and pose an existential threat to humanity.
What Is Artificial General Intelligence (AGI)?
One of the key pursuits of AI research is to develop an artificial general intelligence (AGI), an AI system capable of self-control without human intervention, a degree of self-understanding, and the ability to learn new skills. An AGI system would theoretically be able to solve problems in settings and contexts that were not taught to it while it was being created.
While AI focusses on training software for specific, challenging tasks at human-level performance, AGI envisions a broader intelligence. This theoretical AI wouldn’t need hand-holding for every domain. Just like a human, it could learn and solve problems. In essence, AGI aims to replicate the full breadth of human cognitive abilities, allowing machines to conquer complex tasks across various domains.
If an AGI comes into existence, it could be humanity’s ‘last’ invention. An AGI could help accelerate drug research and cures for diseases like cancer, anticipate and prevent disasters, and help humanity make use of potentially catastrophic technologies like climate engineering and nanotechnology.
