Learn about the latest advances in Artificial Intelligence and the importance of analyzing large amounts of data throughout 2021.
- We are currently living in one of the times of greatest growth in artificial intelligence.
- AI is an unstoppable technology that, shortly, will directly impact each of our decisions.
Artificial Intelligence since its inception, sixty years ago, has not had an easy development, with many “hype” periods followed by very low moments. However, we are currently experiencing one of the times of greatest growth. This boom occurs mainly thanks to the availability of large amounts of data ( big data ), graphic processing (GPU), and tensor processing.
AI is being a multiplier lever in technological progress in our increasingly digital and data-driven world. This is because everything around us today, from culture to consumer products, is related to some intelligence product.
Advances in AI in the field of semantics
One of the biggest advances lately has been in the area of semantics. In this field, a new generation of transformative language models is creating new use cases. Among these advances, the most important has been that of the Open AI company. Its new GPT-3 Natural Language Processing model is made up of algorithms capable of recognizing data and learning through examples.
This new semantic intelligence makes it possible to assess similarities between texts, classify them or even generate them according to the examples provided. This intelligence is still abstract since it does not allow us to understand what it is doing or saying, as people do. Along these lines, AlphaGo is developing algorithms that are trained with a large number of human behavior functions. And, too, Waymo, Uber, and Lyft are developing new imitation learning techniques and reverse reinforcement learning instead of rules.
Facebook has launched its next-generation open-source chatbot. Blender Bot has been developed with various conversational skills such as empathy, knowledge, and personality. This chatbot has improved decoding techniques. It incorporates a novel mix of skills and a model with 9.4 billion parameters, which is 3.6 times larger than the current largest system. The key to this chatbot is the combination of a special approach with state-of-the-art skills and strategies. Its result is so superior that not even human evaluators can deny its great capacity.
Another important advance is in the training of Edge devices. These devices could have a profound impact on next-generation AI applications, such as healthcare or 5G. The recent acquisition of ARM by Nvidia will accelerate this innovation.
Cloud technologies and Artificial Intelligence
Native cloud development becomes an essential tool when a company wants to be data-driven. In this way, the technological model to be implemented is based on a hybrid cloud architecture powered by MLOps and Kubernetes, being able to scale profitably. Thus, cloud technologies will facilitate easy ML deployments. This will imply a greater demand from data scientists towards more complex areas that require machine learning systems.
This medium-term move towards cloud solutions with self-adjusting machine learning models can make AI become a “commodity”, moving towards decision science.
The evolution of Artificial Intelligence: the science of decision
Therefore, artificial intelligence is evolving from data science to decision science. Data science aims to find models that have metrics that measure, for example, precision. If we apply the science of decision, we will get much more value.
This new concept of decision science will allow us to develop simulation models with different types of actions and even carry out these actions or carry out simulations with “what if” criteria. In these new models, reinforcement learning algorithms will become very important.
Other applications of AI in 2021
Another field that needs a new approach to Artificial Intelligence would be that of engineering applications. Models based on machine learning are being adopted by more and more industries, so engineers will need a “reskilling” to know how to apply these models and, above all, to have confidence in their results and automation.
Finally, a fundamental area will be the development of artificial intelligence models that are based on responsible ethics. On the one hand, data privacy should be reflected in the companies’ strategy, respecting regulatory ethics and ensuring the privacy of their results. And, on the other hand, ensure that their Artificial Intelligence models do not present biases that may discriminate or not contemplate all possible cases.
In conclusion, I can only say that Artificial Intelligence is an unstoppable reality. Shortly, it will be part of the lives of all of us and will directly impact each of our decisions.