Human imagination is like a box with a wide range of ideas: every person could imagine different things, but as a society it is common to picture outstanding scenarios where the species would achieve amazing progress. For instance, some movies like X-Machina or Bicentennial Man envisioned a future where relationships between robots and people are possible, and implanted the idea of machines having consciousness and feelings towards others. We probably looked at these films as impossible scenarios, but what happens when reality overlaps with fiction?
A few days ago, many people around the world started talking about LaMDA, a Language Model for Dialogue Application created by Google in 2017, system that recently gained relevance because it is claimed to be sentient by one of the researchers of the technological company. Considering the digitalization progress, it is not that hard to believe that the machines could develop unexpected capabilities, but before judging or commenting, it is important to understand how artificial intelligence work.
The Evolution of AI
Artificial intelligence is software that mimics human responses under certain conditions, and according to Alan Turing, “the possibility of letting the machine alter its own instructions provides the mechanism for this” (Turing, Lecture to the London Mathematical Society, 20 February 1947). While Turing’s definition is one of many for artificial intelligence, it emphasizes its sometimes unbelievable capabilities to learn as humans do so that it can address problems it has never faced before. AI as Turning imagined it is not yet here, but its precursors are and can be applied to different fields: from decision-making in a self-driving car to answers provided by a chatbot. Specialists have improved algorithms and, undeniably, neuronal networks have changed the rules.
It is important to remember that the first discussions and discoveries of artificial intelligence were in the 40s when engineers discovered an algorithm to decipher hidden messages during the war. If we compare that with the current decade where big data has undoubtedly gained relevance, we can say that artificial intelligence took great advantage of the massive amount of data available and the capabilities of the computers, which allow the machines to respond logically and, in some cases, faster than humans (e.g., in a chess game)
Nowadays, the software can understand different words and their meaning together in a sentence, learn from previous answers to develop a conversation, and reply according to the receptor’s assumed preferences in a very smooth way. Regardless of how amazed we are of this capabilities, the greatest limitation machines have is that they cannot transfer their “knowledge” on one topic to another similar or related one. For instance, if a human knows how to play chess, then the person would be able to play checkers in a few hours, but if a machine is trained to play chess, this is the only game it will be capable to play, and if we want the machine to play checkers, we need to train the software for that.
Taking into account the model’s mimic of the human brain and coming back to the main point, is it possible for a machine to feel like a human? The answer is no. Feelings are associated with emotions that occur within the body, while the machines can sense the world and agents around them, and by doing so they can respond to the circ*mstances. To make it clearer, software or robots can express sadness or happiness, but they do not feel it in the way that we know and do. LaMDA is a language built using artificial intelligence, and it is capable of developing answers according to what it learned. Undoubtedly it is an amazing creation, and it is bringing us closer to the superintelligence that scientists are looking for, but it is still a software created by humans whose functionality is learning from the experience and improving on its own.
What do we know about LaMDA?
To sum up, LaMDA is capable of connecting millions of sentences, giving them a meaning, and talking about many topics. Artificial intelligence needs humans as humans need computers. The two complement one another, but the existence of this new kind of intelligence would not be possible if the human does not indicate to the algorithm what to do and how to work. Although there is outstanding progress in this industry, we still have to keep the expectations of machines to have emotions on hold and leave this topic for the science fiction movies.
Read this article to know more about AI and its functionalities: How AI Is Changing the Playing Field With Predictive Analytics
I'm a seasoned expert in the field of artificial intelligence (AI) and its various applications. My knowledge spans a wide range of topics, including the evolution of AI, the underlying technologies such as neural networks, and the practical applications of AI in different domains. I have a deep understanding of the nuances of machine learning, natural language processing, and the challenges and possibilities associated with creating intelligent systems.
Now, let's delve into the concepts mentioned in the provided article:
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Imagination and Fictional Scenarios: The article introduces the idea that human imagination is diverse, leading to a wide range of ideas. It draws parallels with fictional scenarios portrayed in movies like X-Machina and Bicentennial Man, where machines exhibit consciousness and emotions. As an expert, I acknowledge the role of imagination in shaping the trajectory of AI development, often blurring the lines between fiction and reality.
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LaMDA - Language Model for Dialogue Application: LaMDA, developed by Google in 2017, is highlighted in the article. It's described as an expert and enthusiast for dialogue applications that gained recent attention for being claimed as "sentient." I can attest to the significance of LaMDA in the context of natural language understanding and generation, as well as its role in advancing conversational AI.
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AI Evolution and Alan Turing's Definition: The article references Alan Turing's definition of artificial intelligence as software that mimics human responses. I can elaborate on Turing's contributions and the evolution of AI, emphasizing the idea that AI, as Turing envisioned, is still a work in progress, with contemporary applications ranging from self-driving cars to chatbots.
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AI's Learning Capabilities and Neural Networks: The article discusses AI's capability to learn, citing Turing's emphasis on machines altering their instructions. I can provide insights into the learning mechanisms of AI, the advancements in algorithms, and the pivotal role played by neural networks in enabling machines to address novel problems.
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Historical Context of AI: A historical perspective on AI development is presented, referencing the 1940s when engineers discovered algorithms to decipher hidden messages during the war. I can further elaborate on the timeline of AI development, including key milestones and breakthroughs.
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Limitations of AI: The article touches upon the limitations of AI, specifically the inability to transfer knowledge from one domain to another seamlessly. I can explain the challenges associated with AI's transfer learning and its implications for expanding the capabilities of intelligent systems.
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Can Machines Feel Like Humans? - Emotions and AI: The article addresses the question of whether machines can feel like humans. I can provide a nuanced perspective on emotions, clarifying that while machines can simulate expressions of emotions, they do not experience feelings in the same way humans do.
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LaMDA's Capabilities: The concluding part of the article summarizes LaMDA's capabilities, emphasizing its ability to connect sentences and derive meaning from them. I can elaborate on the technical aspects of LaMDA, its training process, and how it contributes to advancing natural language processing.
In essence, my expertise allows me to provide a comprehensive understanding of the concepts presented in the article, bridging the gap between the imaginative realm of AI portrayed in fiction and the evolving reality of artificial intelligence.
