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This one is a no-brainer. We’ve had ChatGPT, Google Bard and god knows what else has come out of the woodwork in the past month. So what is Natural Language Processing (NLP) and why did I mention ChatGPT and Google Bard?
NLP is the process of helping computers understand text data. Learning a language is already difficult for us humans, so you can imagine how difficult it is to teach a computer to understand text data. NLP uses various techniques such as Sentiment Analysis, Named Entity Recognition, Summarization, Text Classification, Lemmatization/stemming, and more.
ChatGPT and Google Bard are Large Language Models (LLM), deep-learning algorithms that can read, recognise, summarise, translate, predict, and also generate text. With this, they can predict future words and have a conversation with the user as if it was talking to a human. Learn more about LLMs here: Learn About Large Language Models.
ChatGPT and Google Bard seem to be competing with one another to see who will have the last laugh as the best large language model chatbot out there. This will mean that AI systems will become more adept at understanding and generating human language, requiring NLP to be at the forefront of this fight.
As we see a rise in chatbots, for example, ChatGPT and Google Bard. We know that they will not stay limited to only being able to return text. OpenAI announced that ChatGPT-4 is a multimodal model that will offer completely different possibilities – for example, videos, images, etc.
OpenAI’s DALL-E can create realistic images/art just by using a description in natural language. We should have seen it coming that OpenAI was planning to make ChatGPT-4 multimodal. Learn more about ChatGPT-4 here: GPT-4: Everything You Need To Know.
With that being said, sooner or later people will have a single model or chatbot that can answer their questions, create content, produce images, and more.
Imagine having a chatbot that can do exactly what you want. An AI system that is completely catered to you by having learnt the way you speak, the kind of questions you ask, the interests you have, etc.
We’re very much dealing with in on social media channels, for example, Instagram, and TikTok – where your data is being recorded to improve the recommendation system. With that being said if you have a tool that understands you as an individual, your preferences, behaviour, and needs – would this essentially eliminate the need for human interaction?
Taking into consideration everything that I stated above, it will be a bit silly to say that sooner or later these AI systems and tools will be a part of our everyday work life. I’m not sure about you, but a lot of my colleagues are already using chatbots such as Google Bard to help them create job specs. Regardless if it’s the use of large language models or computer vision – AI will start to be a core part of work environments and processes.
There were times and still are when people were nervous and anxious about the use of AI. Due to the hype around it, and continuous investment and research going into it – more and more industries will adopt AI to improve these industries.
The financial industry has been using AI to help with fraud detection, anti-money laundering processes, and investment management. They might look into using chatbots to deal with an applicant’s whole process, lowering their cost and tasks.
In the healthcare industry, machine learning algorithms are already being used to predict patient outcomes, help with the diagnosis of diseases, and assist in surgical procedures. Again, we’re looking at ways the healthcare industry can be improved.
This also accounts for AI continues to grow in the autonomous sector. Self-driving cars, robots, and drones will continue to grow and improve to the point that we may see a major fall in the need for humans.
Let’s face it, we’re dealing with a high amount of workload in the majority of countries, with some dealing with unfortunately low salaries. If these roles were passed onto AI systems, robots, etc – would that be so bad? It’s hard to tell because with anything good – there has to be a bad, right? Let me know what you think in the comments.
Learn more by reading: The Future of Work: How AI is Changing the Job Landscape
Up until now, the AI industry has had very little governing, ruling or constraints. It’s basically been a wild west.
However, in recent years we’ve already seen some changes being made due to the rise of artificial intelligence. For example, the European AI act with the possibility that it may be considered a gold standard. Learn more about it here: European AI Act: The Simplified Breakdown.
In 2022, lawmakers and regulators worked hard to make sure things were going to change for the world of artificial intelligence in the year 2023. Lawmakers are finishing up amending the European AI Act mentioned before, which already had banned AI systems and fines in place in the initial drafts.
AI will continue to spread globally, and with that happening – governments, regulations, lawmakers, etc will have to work extra hard to stay focused on ensuring that AI systems are ethically correct, are not biased, are fair, and ensure customer privacy.
I can imagine everybody has their own thoughts and opinions of what they expect to happen in the next decade. I personally focused on these because it will also take a while before laws are put in place before AI systems can really become a part of our everyday personal and work lives.
Let me know what you think will happen with AI in the next decade in the comments
Nisha Arya is a Data Scientist, Freelance Technical Writer and Community Manager at KDnuggets. She is particularly interested in providing Data Science career advice or tutorials and theory based knowledge around Data Science. She also wishes to explore the different ways Artificial Intelligence is/can benefit the longevity of human life. A keen learner, seeking to broaden her tech knowledge and writing skills, whilst helping guide others.