Such is the complexity of natural human language, it took the loveable eco-friendly but rusty droid character WALL-E more than 700 years on this planet to develop intelligible human language. That’s because there’s unstructured data to contend with as well as formal rules that have too many exceptions (I’m looking at you I before E expect before C). Ripe with nuances, real-world context, and sometimes unfortunate double meanings, natural human language has been near impossible for computers to understand and mimic in a way that truly makes sense.
Open AI ChatGPT and Google Bard
Fast forward to 2023 and it’s no longer science fiction. This year, it’s been impossible to avoid the buzz around adaptive and generative Artificial Intelligence in the form of the interactive conversational model from ChatGPT and Google Bard. Adaptive AI works by continuously retraining its models to automatically learn and adapt based on new experiences. Generative AI uses neural network models to form something new.
With ChatGPT and Google Bard based on the GPT natural language processing framework, these AI tools have overcome the substantial challenge of natural human language. By exploiting sophisticated algorithms, these tools consider not just the individual words in a sentence, but the grammatical structure, syntax, and context as well.
These natural language processing models can be used in chatbots and virtual assistants running on 5G to understand and respond to user queries. As AI has advanced in gargantuan leaps and bounds, you can expect more meaningful responses and consequently more satisfying customer experiences. They can also be used to perform sentiment analysis, analysing customer feedback for sentiments or emotions.
Adaptive Artificial Intelligence
Not surprisingly, global spending on AI is set to skyrocket. According to a forecast from the International Data Corporation (IDC), its Worldwide Artificial Intelligence Spending Guide predicts global spending will reach $154 billion in 2023, an increase of 26.9% over the amount spent last year.
As always, companies that are slow to adopt new technology – in this case natural language processing AI – have the potential to be left behind. With rapid advances in adaptive and generative AI, IDC’s report points to exciting AI use cases, technology, industry uses, and geography perspectives.
That said, when it comes to AI and any fast-emerging technology, it’s always important to remember that when things work in new ways they also break in new ways. And one of the pesky failings of Google Bard and ChatGPT to date is the hefty number of inaccuracies served up in the content generated. There’s also the potential for plagiarism and infringing intellectual property rights without the right checks and balances in place. And as ever with the creative process, you need to remember, rubbish in leads to rubbish out. By that I mean AI tools learn from existing data so it’s likely tools will replicate existing biases or misinformation in what is produced, so it needs to be scrutinised by experienced eyes. So, use natural language processing AI to augment human abilities in creating content and the writing process, not to replace them.
There’s significant value in taking advantage of these tools to automate repetitive tasks, provide personalised recommendations, and make data-driven decisions with immediate potential from using it to enhance customer service agents and optimise sales process recommendations.
With businesses ever more reliant on technology to communicate and perform tasks, don’t wait 700 years to explore how 5G can underpin your adoption of shiny and hard-working AI tools in your business.
