Natural language processing ( NLP ) is so embedded into our daily lives we hardly notice it . When you use Alexa , you are conversing with an NLP machine and when you type into a chatbot NLP technology takes charge to support your query . The list of things this technology is used for is almost endless .

NLP market size The NLP market is fast expanding . According to the research firm , MarketsandMarkets , the NLP market will grow to USD 35.1 billion by 2026 from 11.6 billion in 2020 .

Adopting this technology with caution Although it is clear that this technology is here to stay , and brings a significant amount of benefits to the organisations that embrace it , technologists need to make note of some drawbacks when adopting this technology . An important consideration for practitioners is the choice of natural language . Most models are good at the English language while performing below par in several other languages .

With this technology permeating throughout society , it is clear it is going nowhere any time soon and as it grows in magnitude and significance , considerations around language and efficiency need to be made .

� DEEPMIND Following a successful 2021 , DeepMind is now moving into the world of NLP with the creation of its AI algorithm that can perform a wide range of language tasks and claims to be better than any existing similar software .

� NVIDIA Leading graphics chip company NVIDIA has been named as a top AI stock to watch in 2022 since it has taken advantage of the AI boom . NVIDIA ’ s graphics cards could someday be supplanted by more specialised processors designed for AI .

� AI GOVERNANCE Technology experts predicted that 2021 would mark the year of AI governance . However , the Carnegie Council for Ethics in International Affairs stated that AI systems and algorithmic technologies are being embedded and scaled far more quickly than existing governance frameworks are evolving .

� TRUE ARTIFICIAL INTELLIGENCE Elwin Loomis , Head of Digital of Bremer Bank argued that our current artificial intelligence is not really intelligent . By terming the technology we have as ‘ intelligent ’, this creates a false narrative and underestimates the work needed to materialise the ‘ real ’ AI .

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