The Future Landscape of Artificial Intelligence
Admin / August 31, 2023
The artificial intelligence (AI) revolution is upon us, and companies must prepare to adapt to this change. It is important to make an inventory of the current skills within the company to identify which additional skills the employees need to learn. The company does well in developing an AI strategy to outline the areas where AI is most effective, whether in a product or a service. Failing to act inevitably means falling behind. The training should include an introduction to AI, its capabilities, and its shortcomings (AI is only as good as its training data). This article gives a view of the current state of AI and what lies ahead.Artificial intelligence found its purpose in 2012 when AlexNet won theImageNet challengewith a 16.4% overall error rate, compared to over 26%. The ImageNet challenge is a collection of 1.4 million images in 1000 categories, such as dogs, cars, plants, etc. A neural network is the internal engine of all artificial intelligence technologies. The neural network is said to be based on the way the human brain functions; however, this is far from the truth. Brains are way more complicated and efficient than neural networks. Brains have awareness, imagination, inventiveness and creativity, all missing in neural networks. Brains are also dynamic, consisting of specialized cells called neurons.Neural networks have grown from a few million to nearly 200 billion parameters. Each parameter must be computed, causing an increasingly great demand for high-performance computing resources and energy. Artificial intelligence programs have beaten humans at chess and in the more complicated game of Go. Programs such as ChatGPT can weave exciting stories and answer complex questions. Training a large network can take months on powerful servers with hundreds of thousands of processors.The increase in computational resources has made new AI tools and neural networks possible. However, the neural networks responsible for all these impressive results are unaware of what they are doing. There is no awareness, just computation.