Generative AI – What is all the Hype about?

The world as we know it has changed and is changing rapidly. The 4th Industrial Revolution or 4IR brought with it a new spin on how we interact with one another. The Covid pandemic helped speed up many of the intended consequences of 4IR. Digital Transformation (DX/DT) has become a buzzword echoing the changes taking place across businesses in all industry sectors. Along comes Artificial Intelligence or AI, which has been around for some considerable time (circa 1956) but not fully understood (not yet) and yet to be fully ‘exploited’.

Emerging technologies pressure leaders to invest early to gain an advantage over competitors. With the period of greater economic uncertainty, we are currently facing, post-Covid, coupled with civil unrest, regional military conflicts in many areas around the globe and the pressures on cost containment, business leaders are faced with how do we do more with less?

The Digital Age has brought with it many advantages. Digital Transformation (DX/DT) is rapidly transforming businesses from manually driven and human-dependent to automated processes with humans focusing on more important and strategic tasks. Digital Transformation has impacted industry sectors from education to financial services, retail, healthcare and manufacturing. The 4th Industrial Revolution or 4IR has certainly ramped up the Digital Age's impact on the life we know.

Artificial Intelligence or AI is gaining ground fast across all industry sectors. The speed of adoption is surprising to skeptics who doubt the value that AI brings. To understand the AI landscape and what AI has to offer (thus far), let us look at the types of AI that exist.

No matter what, the subject of AIs will dominate the public discussion for the foreseeable future.
Bill Gates, March 2023.        

source: gatesnotes.com

AI can broadly be segmented into three main categories. AI can be viewed through different sets of lenses based on technologies, functionalities or capabilities. Weak/Narrow AI (also called Traditional AI) is a type of AI that can only perform specific tasks (e.g., facial recognition, internet searches, or driving a car), Other examples include voice assistants like Siri or Alexa, recommendation engines on Netflix or Amazon, or Google's search algorithm. These AIs have been trained to follow specific rules, do a particular job, and do it well, but they do not create anything new. Strong AI is a type of AI that can perform any task that a human can. Strong (General) AI is capable of broad human-like cognitive capabilities, enabling it to tackle new and unfamiliar tasks autonomously. This type of AI has the capacity to recognize, assimilate and utilise its ‘intelligence’ to resolve any challenges presented without human interaction or guidance. Strong/General AI is and can revolutionise many aspects of our lives.

Then we have Superintelligent AI. This is the future form of AI where machines surpass human intelligence, across creativity, general ‘wisdom’ and problem-solving. There are great concerns about how Superintelligent AI is going to evolve and whether man or humanity will be ready for this.

Generative AI is a subset of AI. So, where does Generative or Gen AI fit in?

Generative AI or Gen AI is a type of narrow AI that is the next generation of artificial intelligence. It is a form of AI that can create something new. The AI creates something new from the piece of information you gave it.

Gen AI has received loads of attention lately. This is mainly due to its technology that can produce various types of content including text, audio, images and synthetic data. You may ask what is synthetic data? Synthetic data as the name implies is information that is artificially manufactured/created as opposed to real data that is generated by real-world events. It is created using algorithms and often used as stand-in data sets for production or operational data to validate mathematical models which are in turn used to train machine learning (ML) models. Machine learning is a subset of AI. ?

Gen AI has been around for many decades; from the 1960s when Chatbots were introduced. When the generative adversarial networks, or GANs were introduced some 10 years back, Gen AI gained attention. Gen AI could create convincingly authentic images, videos and audio of real people. Gen AI enables computers to generate content based on a set of AI and Machine Learning (ML) algorithms applied to vast data sources.

This recent attention is driven by the simplicity of new user interfaces for creating high-quality text, graphics and videos in a matter of seconds.

GANs is an ML model in which two neural networks compete against each other using deep learning methods to become more accurate in their predictions.        

Gen AI has gained traction rapidly with many businesses adopting Gen AI in some form. The adoption is in the early stages. We are witnessing varying levels of disruption across businesses from organisations structures, and products to workers. The impact and disruption is undeniable. We are witnessing businesses in the process of building the required infrastructure, cloud expertise, and data-enabled capabilities and upskilling the workforce to be Gen AI-ready/enabled. A strong business foundation is a pre-requisite to capitalise on GenAI. Gen AI is not only and all technology.

Using Gen AI is becoming easier with time as the earlier versions of Gen AI require a deep understanding of special tools and coding (programming languages) like Python. Gen AI pioneers are developing better user experiences that let you describe a request in plain language. Gen AI starts with a prompt that could be in the form of a text, an image, a video, a design, musical notes, or any input that the AI system can process. Gen AI algorithms return new content in response to the prompt.

Gen AI is not only disruptive and evolutionary. Gen AI developers are continually exploring new and better ways to improve existing workflows to take advantage of the technology behind Gen AI. Gen AI offers many benefits that include the automating manual process of writing content, summarising complex information into a coherent account, intelligent email responding simplifying the content creation process and technical query responding. ?

Gen AI is by no means the silver bullet or that Knight in Shining Armour. Gen AI is still being understood with ongoing development through the journey of discovery. The use of Gen AI can be challenging when assessing the biases of original sources; identifying the source of the content is not always possible; results can gloss over bias, prejudice and hatred which is a serious challenge and concern over AI generally.

Generative AI offers immense benefits to businesses regardless of the industry sector the business operates. By adopting Gen AI technologies businesses stand to gain a major productivity boost across multiple areas. Developing and implementing Gen AI technology for digital business transformation requires a thoughtful and deliberate approach. It is not a pure IT matter but an integrated business approach that requires the buy-in from the C-suite downwards.

Developing and implementing generative AI technology for business transformation requires a thoughtful and deliberate approach. The identification of tractable use cases is the starting point of this journey. The solution that is sought must be useful, bring value and have identified success measures; what you cannot measure you cannot manage. The success metrics will measure the business impact which could be tied to areas of customer service, business efficiencies, financial benefit and most recently sustainable outcomes (ESG).

The streamlining of high-volume tasks that take time is key to this initiative as this will help unlock value coupled with accessing information that is in ‘big data’ to unlock the economic benefit that the data holds. Tasks and jobs performed by people need to be evaluated to assess whether some of these can be transformed by Gen AI. It has been proven that successful Gen AI implementations within businesses tend to embed themselves into the existing customer and employee workflows; i.e., they integrate into existing structures and are not standalone.

To fully harness the potential of Gen AI, businesses need to review their operational, technical and data infrastructures. This is important as understanding how these operate and are maintained with the impact of AI will ensure that the business only uses the correct quality of data to inform its models.

Keeping the adoption of Gen AI simple is the secret. Avoid unnecessary complexity as this will speed up adoption over months and not years. This would make the adopting of Gen AI a moment in technology history whose benefit and significance will be felt and appreciated quickly.

Gen AI’s progress is remarkable. The adoption of Gen AI should be carefully planned so as to ensure that biasness, the use of poor data and incorrect algorithms are avoided. Widespread disruption of Gen AI may take some time, but its impact is undeniable. Humanity should never be at the mercy of technology or intelligence that is perceived to be at the level/higher of the human, when it does arrive, yes when it arrives.

We are at a disruptive time in the history of humanity when technology promises many benefits through the advent of AI and specifically Gen AI. The benefits of Gen AI are many. All disruptive technology always has a dark side. We should tread carefully to ensure that we capitalise on the benefits of Gen AI for the improvement of life as we see it currently and how this disruptive technology can benefit future generations.

Sources:

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·?????? IBM

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·?????? MIT