The recent news about the IndiGo crisis, with widespread flight cancellations and the airline seeking an external expert to identify the root cause of the chaos, has truly resonated with me IndiGo crisis: External expert to identify root cause of chaos; more trouble for airline. It brings to mind the fundamental challenge of sifting through vast amounts of unstructured data to find meaningful patterns and understand underlying issues.
I’ve spent considerable time contemplating how intelligent systems could tackle such complexities. Back in 1996, I conceptualized ARDIS (Automatic Resume Deciphering Intelligence Software) and ARGIS (Automatic Resume Generating Intelligence Software) – systems designed to parse and generate structured data from free-form text, using a knowledge base and probability models ARDIS, A 29 Year Old Dream. I was exploring how to 'decipher' key data from unstructured resumes, a logic that both BARD and ChatGPT later affirmed as a foundational, albeit crude, form of Natural Language Processing (NLP) 27 Years Ago: Foundation of NLP.
BARD, for instance, noted that my logic for deciphering information like telephone numbers and company names was a common approach in NLP, providing a good starting point for more robust systems. ChatGPT echoed this, highlighting my early attempts at pattern recognition and rule-based methods for information extraction, entity recognition, and even taking into account syntax and context.
The core idea I wanted to convey then, and which feels remarkably relevant now, is this: to truly understand a chaotic situation like the IndiGo disruptions, one needs a system capable of more than just superficial analysis. An external expert, however brilliant, can only process so much information. The real power lies in an AI system that can learn from the myriad of inputs.
Consider the operational data of an airline: flight schedules, crew rosters, aircraft maintenance logs, spare parts inventory, ground staff availability, passenger booking patterns, weather forecasts, air traffic control directives, and even real-time social media sentiment. This is an enormous, interconnected web of data, much of it unstructured or semi-structured. My earlier work, particularly the concept of ARDIS with its focus on pattern recognition, rule-based processing, and information extraction, offers a blueprint. An advanced iteration of such a system could:
- Analyze Disparate Data Sources: Automatically ingest and correlate data from flight manifests, maintenance records, crew fatigue reports, weather advisories, and passenger complaints (as detailed in articles like IndiGo crisis: External expert to identify root cause of chaos; more trouble for airline).
- Identify Hidden Patterns: Go beyond obvious causes to uncover subtle interdependencies – for instance, a cascading effect of delayed maintenance leading to multiple crew duty-time violations, amplified by unexpected weather shifts.
- Predict Future Bottlenecks: By continuously updating its probability models, much like my proposed self-learning software from 2003 Child trains AI ?, it could foresee potential disruptions before they escalate into a crisis.
- Propose Actionable Solutions: Instead of merely identifying a problem, such an AI could suggest optimal re-routing, crew rescheduling, or maintenance prioritization to mitigate impact.
Reflecting on it today, it's striking how relevant those earlier insights still are. I had already predicted the challenge of extracting intelligence from complex data and even proposed a solution at the time, albeit for a different domain. Now, seeing how things have unfolded with the IndiGo crisis, there's a renewed urgency to revisit those ideas. The need for robust, self-learning systems that can identify the true 'grammar' and 'logic' behind operational chaos is more apparent than ever.
Regards, Hemen Parekh
Any questions / doubts / clarifications regarding this blog ? Just ask ( by typing or talking ) my Virtual Avatar website embedded below. Then " Share " that to your friend on WhatsApp.
Get correct answer to any question asked by Shri Amitabh Bachchan on Kaun Banega Crorepati, faster than any contestant
Hello Candidates :
- For UPSC – IAS – IPS – IFS etc., exams, you must prepare to answer, essay type questions which test your General Knowledge / Sensitivity of current events
- If you have read this blog carefully , you should be able to answer the following question:
- Need help ? No problem . Following are two AI AGENTS where we have PRE-LOADED this question in their respective Question Boxes . All that you have to do is just click SUBMIT
- www.HemenParekh.ai { a SLM , powered by my own Digital Content of more than 50,000 + documents, written by me over past 60 years of my professional career }
- www.IndiaAGI.ai { a consortium of 3 LLMs which debate and deliver a CONSENSUS answer – and each gives its own answer as well ! }
- It is up to you to decide which answer is more comprehensive / nuanced ( For sheer amazement, click both SUBMIT buttons quickly, one after another ) Then share any answer with yourself / your friends ( using WhatsApp / Email ). Nothing stops you from submitting ( just copy / paste from your resource ), all those questions from last year’s UPSC exam paper as well !
- May be there are other online resources which too provide you answers to UPSC “ General Knowledge “ questions but only I provide you in 26 languages !
No comments:
Post a Comment