topics in technology
Often, it’s assumed us tech folk have dominion and understanding of every realm in the tech industry, from those not in the industry, whether this is fact or fiction. You may have developed the flexibility to at least be conversant in most things tech.
As by reading this blog you are likely considering which sector to make your million’s in let’s review some of the next big if not already ‘topics in tech’, this article will be the first in the series and cover adaptive AI.
adaptive ai
Firstly, is there a difference between Adaptive AI and AI. Well ‘yes’ AI as is often referenced, refers to generative AI which is basically an instruction based AI e.g. produce/generate this task or result within these prescribed boundaries/tolerances whereas adaptive AI is more like a nested loop of AI learning on the job and even changing the boundaries to achieve the result.
Adaptive intelligence allows systems to learn and evolve from new data over time. They adjust their actions based on changes in their environment. Artificial intelligence, in contrast, operates based on predefined rules and algorithms.
In its current format Adaptive AI is particularly useful in Finance due to the often-fast paced change within in markets, Manufacturing for cost saving optimizations, Edtech for reactive differentiation (not so much presently employed) and healthcare software development and analysis. In the private sector, we will see more analysis on patient data to provide more timely interventions, we may even predict this could be a healthcare add on in insurance companies or medical institutes in the not-so-distant future (Hence paying for its own R&D). For Manufacturing JIT (Just in Time) production could utilize predictive models and algorithms to entice a customer/client toward a purchase using some form of direct marketing offer or habit analysis and prepare the item accordingly this would extend to supply chain mgt for B2B. In other areas such as anomaly detection and fraud prevention due to the real-time versatility.
The industry value of AI is projected to rise by 13x over the next 7 years, which is good news for AI-oriented businesses in 2024 (Something to consider). It is also forecast in AI stats that Adaptive AI models will outrun their competitors by at least 25%.
Where to start then in the world of adaptive AI, dependent on your needs you may consider a hybrid solution or a bespoke approach. A hybrid solution would leverage several AI’s/LLM to achieve your aims and may be a good prototype approach.
the process
The first stage of implementing adaptive AI is to define the problem and the goals of the system. Starting by identifying the main tasks and subtasks that the system needs to perform, the desired outcomes and metrics of success, any constraints or requirements of the system, and the potential risks and challenges of the system.
An adaptive learning interpretation example, but still very much generative: https://github.com/sagefy/sagefy