Data to Intelligence

Developing data technologies for artificial intelligence

Our team has been developing data technologies for artificial intelligence (AI) since 2000, a year before we applied for our first patent of a standardized approach for automated Data Integration and Consolidation. Since then, team members have been named inventors of twenty-one United States patents and three current US patent applications.

Technology that will deliver true AI.

Today, computers are highly proficient at collating very large amounts of information as input and regurgitating it as elegant output. But we still can’t be confident that the output has integrity, that it is factually accurate. It’s still the case that rubbish in often delivers rubbish out. Whether we can describe what we have today as artificial intelligence is not just a matter of semantics. What we have is certainly based on clever algorithms (a set of actions or steps followed to solve a problem) developed by a human or derived by a computer, but the quality of the output is often only as good as the quality of the input. The anecdotal tales of ChatGPT creating misinformation is testament to that. We say that today we have artificial plagiarism (AP) rather than artificial intelligence (AI). We also say that if a system cannot recognise misinformation, then it is not intelligent.

It's worth noting that in 1970, AI pioneer Marvin Minsky told Life Magazine, “In from three to eight years we will have a machine with the general intelligence of an average human being.” [Source]

On 29 August 2023 it was reported, “Chat-GPT is “much smarter” than the average human with an estimated IQ of 155, says former Google executive Mo Gawdat.” [Source]

We say that AI isn’t here yet.

World thought leaders in cognitive AI.

Around 2016, IBM referred to its “Watson” AI platform as a cognitive computing system.  [Source] We believe that the emerging technologies of cognitive computing systems will address the information integrity issues that currently have AI thought leaders worried. Like IBM, we believe that there will be two types of cognitive computing system, Symbiotic and Autonomic, where Symbiotic refers to “human and software agents that are designed to collectively perform cognitive tasks such as decision-making better than humans or software agents can unaided.” [Source].

We refer to symbiotic cognitive computing systems as cognitive AI”, and we believe that such human/machine interaction will dominate the AI landscape wherever information integrity and important decisions are essential requirements.   

Cognitive AI will be achieved when it can be demonstrated that a computer system can collaborate with humans to understand, by itself, what it is processing and how it has arrived at a conclusion, the way a human being does. That is when computers will become closer to mimicking human intelligence, able to distinguish, by themselves, between fact and fiction, what is known and unknown. That is the point when humans and computers will intelligently collaborate, rather than compete.

Cognitive AI will not be a threat to humans because it will address the shortcomings of current technologies by being fact based, knowledge rich, collaborative with human experts, and (hence) well-reasoned. For computer systems, it will herald the dawn of the getting of wisdom.

Computer Reasoning, the next big step.

Since 2012, we have been developing techniques and inventing new patented technologies necessary for cognitive AI. In more recent years, we have become a world thought leader in combining Machine Learning and Knowledge Engineering, and we are now ready for our next big initiative.

The next step on the path to true artificial intelligence is the expected advance of computer reasoning technologies. Without a doubt, the most important, and likely the last major challenge for AI delivery, is to use a mix of known techniques in a new way to develop cognitive AI that will mimic aspects of human reasoning necessary to distinguish fact from fiction.

Cognitive AI will combine:

  • information consolidation
  • machine learning
  • knowledge engineering
  • computer reasoning

to truly advance human endeavour like no other technologies before it.

It will fundamentally change the world delivering better outcomes based on faster access to knowledge and logical prediction. In collaboration with human endeavour and superior human judgement, cognitive AI will massively improve the allocation of resources in health, education, commerce, and invention.