Currently many specialists (or dilettantes, including those writing on AI in media) are considering Artificial Intelligence and Machine Learning (and in general, data based techniques) as the same thing (or almost). Do you agree? What can history of its development tell us about the content of that concept?
Rey Segundo Guerrero-Proenza ,
Those who equate machine learning with AI do not have knowledge of what the two concepts are.
The field of AI "predates"(see next paragraph) machine learning and machine learning is considered only one aspect of AI. Due to the particular point in time AI was conceived it inherited a strong logical focus from the logical empiricists. Within AI the symbolic processing paradigm took hold due to its manipulation through logical formalism. The field was also conceived to include research into sensor data acquisition and actuator outputs.
Even as AI has its "birth" at the Dartmouth conference in 1956, the field of neural networks already was being studied( McCulloch and Pitts work is dated 1943). Though it was still very reliant on modeling through logical symbolism ("on" "off" processing ) of digital circuits. The field progressed until the XOR problem sent NNs into hibernation and resurrected with the addition of hidden layers and backpropagation (mid 80s). Still, at the time, processing more than one hidden layer was computationally prohibitive. It was not until the resurrection of the stacking of multiple layers with efficient algorithms in the start of this century (and the development of GPUs) that it has been possible to carry ML at scale. Notwithstanding, the AI field has a rich area of symbolic processing and input /output integration techniques that should not be swept aside due to a fad of ML's recent development. Else, they will commit the same mistake of the past of focusing on only one aspect of AI and slowing down progress in the field.
Rey Segundo Guerrero-Proenza Artificial intelligence (AI) and machine learning (ML) are concepts that are similar but not identical. AI is a broad concept that encompasses a wide range of technologies and tactics aimed at mimicking human intelligence in robots. Applications include natural language processing, computer vision, and expert systems.
Machine learning (ML), on the other hand, is a subset of AI that focuses on developing algorithms and models that can learn from data and make predictions or judgements without being explicitly programmed.
A historical examination of the evolution of AI can serve to uncover the concept's substance and how it has grown through time. AI has a lengthy history, extending back to the 1950s, when pioneers like Alan Turing and John McCarthy suggested the notion of building intelligent robots.
Initially, AI research concentrated on developing "expert systems" capable of mimicking the decision-making abilities of human specialists in certain subjects. This method was based on the concept of "good old fashioned AI (GOFAI)," which sought to recreate human intelligence by hand coding rules and knowledge into machines.
This strategy, however, proved to be restricted, and in the 1980s and 1990s, the emphasis turned to more data-driven methodologies, notably ML. This is when machine learning techniques like decision trees, neural networks, and support vector machines were created.
With the availability of enormous amounts of data and the development of strong computer resources, the focus of AI research has switched to deep learning, a kind of machine learning that employs deep neural networks to learn from data.
To summarize, artificial intelligence (AI) is a broad term that has evolved through time and encompasses a wide variety of technologies and methodologies. ML is a subfield of AI focused on creating algorithms and models that can learn from data. A historical examination of the evolution.
Hi Friends
Maybe glance at Alan Turing's test for an AI which was influential in the early days -- in the UK and well beyond.
Also THE LOGIC THEORIST and THE GENERAL PROBLEM SOVER, both Newell, Shaw. Simon
And THE GRAPH TRAVERSER by myself and Donald Michie which was a very different re-conception of the GPS. See my list of publications here on RG for GT reference.
These came before the age of expert systems.
Best James
I agree with James Doran , Rey Segundo Guerrero-Proenza , and Qamar Ul Islam . Thanks for the detailed answers! I would like to bring to your attention a picture that illustrates the coordination between AI and ML as well.
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