Skip to main content

AI - looking beyond the marketing hype

 Technology is changing very rapidly. Every few decades we might see disruptive technologies which might have a huge impact on our society. Artificial Intelligence is such a technology which can improve the quality of our lives in a positive way. I am sure that in our lifetime we will see its incredible impact on various areas of our lives.

Many months ago everyone was behind crypto, “bit” or blockchain. It seemed like almost everyone was trying to create all these wonderful products based on blockchain. It is a very good technology but it was overhyped . A lot of people lost their hard earned money due to this hype. 

Now it seems AI has become a buzzword in almost every industry. However, it's crucial to understand that simply appending "AI" to a product or service doesn't automatically make it intelligent or truly embody AI capabilities. I have seen the same company doing blockchain a couple of years back ,now jumping into the AI bandwagon without any investment in any of these technologies. I am getting emails from many vendors mentioning that they have advanced AI software and AI somehow will solve all my problems. Certainly I don't have the services of “Data” from StarTrek to solve the problems but some of the marketing materials I received almost equal the exploits of ‘Data”. Sometimes I wonder if they are creating marketing materials from science fiction or based on any sort of reality. I have seen many company stalwarts mentioning "AI" during their quarterly earnings calls  without any tangible investment in AI, with the only aim to cash in the hype.

AI involves advanced algorithms, machine learning, deep neural networks, and sophisticated data analysis. It goes beyond a mere marketing tactic. AI algorithms possess the ability to learn, adapt, and make decisions based on complex patterns and very large and diverse  datasets. It can recognize patterns, make predictions, and generate insights that humans might miss thus providing tangible solutions. They adapt to changing circumstances and refine their predictions based on new information,  evaluating multiple factors, and making informed decisions autonomously, often outperforming human capabilities.

AI can solve real-world problems if applied properly. This can fuel innovation and will help the human race to make rapid progress. 

While developing such algorithms we also have to prioritize fairness, transparency, and accountability. They uphold ethical guidelines and protect against biases or discrimination. We have to ensure that our own bias doesn't creep into the data model and decisions the algorithm uses for its decision making

Comments

Popular posts from this blog

PDCA & SCRUM (or Agile); Why is it important?

The PDCA (Plan DO Check Act) cycle was made popular by Dr. W. Edwards Deming. This is a scientific cyclic process which can be used to improve the process (or product). This is cyclic in nature and usually time boxed. Plan  This is the first stage of the process. During this step the team discusses the objectives, the process and the clear conditions of exit (conditions of acceptance). This stage sets the measurable and achievable goals for the team. DO Team works together to achieve the objective set in the planning phase. Team works with the set of agreed process. Check Once the implantation is done team regroups and verifies the output and compares it to the agreed conditions of acceptance decided during the planning phase. The deviation, if any, is noted down. ACT If any deviation in planned tasks is observed during the Check stage, a root cause analysis is conducted. Team brainstorms and identifies the changes required to prevent such deviations in future. Team also

Why is potentially shippable product quality important

Agile teams work in iterations. During this period, they are supposed to work on product increments which can be “delivered” at the end of iteration. But how you know that the correct product was delivered? Many teams have different kinds of acceptance criteria and Definition of Done (DoD). But in many cases, this “done” is not the real “done” there might be some testing pending, some integration or review pending or anything else which prevents the actual use of the product increment. Many of these teams will need additional iterations to finish hardening their products. Many teams will implement different types of “gates” or approval steps to move to next stage. The free flow of product will be interrupted. They might end up doing mini waterfall within their agile process. Many don’t even realize this. This results in poor quality and requires additional effort to “harden” the product. Potentially Shippable Product increment The acceptance criteria and DoD should be modified

Product Backlog: Should you write everything in user story format?

I like user stories a lot. They help everyone talk the same language and results in a better product. User story alone does not constitute product requirement. User story is supposed to be a place holder for discussion which should happen between the team, Product Owner and the customer. This discussion result in a common understanding which along with the user story content is the product requirement. This format captures the essence of requirement without confusing the readers User Story is only one of the many different ways in which requirements can be represented. This is not mandatory in any Agile “process”. But many have made this mandatory. I have seen many spending countless hours trying to write the requirements in user story format when they could have easily written that in simple one-line sentence in few minutes.   I have seen team members refusing to even discuss the requirement until product owner rewrote the requirement in user story format. Once I