I have been posting a lot to address the narrative around 'AI is replacing Data Science' and whether you said it, or you're a data scientist or worse, masquerading as one; this is for you. Sharing my knowledge and experience with data and AI thrills me, as I know firsthand how it can change the way businesses plan strategies that lead to success and revenue. However, individuals using AI are now building scripts using prompts that mimic data science workflows. What used to ta

Of course, when I learned that OpenAI has been considering launching the PhD Level Agent at $20,000 a month, I thought, "Hey, that would be a nice salary to have for a PhD graduate like myself". After all, AI has been promoted as cheaper than humans, which doesn't sound correct for doctorate holders - FYI. But seriously: What is a PhD? It is NOT experience - or at least not just. Spending 10 years doing the same thing over and over again or being led by your leaders' vision

At the risk of sounding like a broken record, the GenAI business model is out-of-this-world genius. A technology that impersonates humans, leading people to question whether the tech is sentient. A tool marketed as a superpower employee in place of a team, at the price of one individual. But is it? I want to share facts with you and, if you are in an influential position, guide you on how to direct conversations in AI. In the end, it boils down to a business decision. First

You read that correctly, I got a personal Claude Pro subscription. Back in 2022, when ChatGPT was launched, subscriptions were cheap. Nonetheless, I held back from getting a personal subscription because most of my GenAI use was work-related, and work offered a secure subscription. Until very recently, I had little use for GenAI, not other AI techniques. I write all my content, and use Grammarly to check my grammar and typos. I have a subscription for Grammarly Premium and in

I always check privacy settings and share content I am comfortable with. However, in today's digital era, some things are embedded in our ways that it is hard to always catch yourself before posting. Social media filters are popular because they can make you look different (I didn't say - beautiful!) or for fun. I also see parents post photos with their kids, except they put a sticker on their children's faces or some other filter in their genuine attempt to protect their chi

The title itself should indicate what inspired this article. Movies like "The Conjuring" or "IT" can give you goosebumps and may also encourage you to conduct a little more research before buying a house or moving to a small town. However, other movies such as "M3GAN" and "Companion" display a new dimension of horror. In both cases, the intent behind the AI remains noble. The robots were programmed to provide a solution for parents or individuals. Curiously, the movies projec

AI is often misunderstood and frequently mistaken for automation. When discussing AI, one usually thinks about having the AI perform tasks that would otherwise be done manually. However, AI is not automation, although it can be combined with tools to enable such capabilities. Automation tools are designed to perform tasks automatically, eliminating the need for human intervention. Nevertheless, a human would need to set up such a process. For example, an individual who receiv

A dark cloud is hovering over Artificial Intelligence (AI) technology and brings with it a storm of ethical concerns about human rights and societal sustainability. But is AI the problem Media from Wix. In this article, I aim to convince you that ethical issues surrounding AI existed before the rise of language models. Nonetheless, they are enhanced with AI scalability. But should we blame the technology or the behaviour with which the technology is used? I hope to convince y

In April, I was promoted to Mother, and amid the joy that my child brought to my world, I couldn't help but notice the vast amount of data collected about the baby and how I consented to its collection for the baby's good. You read that correctly. The Author's photo was traced by the Author using Procreate. **Image cannot be distributed or used to train models. When the baby was born, the hospital took note of a bunch of parameters. All parameters were, in my honest opi

Alan Turing is a famous machine learning and artificial intelligence (AI) contributor. In a recent book I have been reading, "The Quest for Artificial Intelligence", the author refers to Alan Turing's 1950 literature paper, "Computing Machinery and Intelligence", which addresses some of the critics of machinery intelligence. Of course, as a scientist, I read it thoroughly. Here is my opinion on the matter. Link to Image Source Licence. The paper starts with a section called "

Everyone wants to use AI, but very few try to understand it. Even fewer want to understand it, and most ask AI to explain itself (as if the AI will know it is wrong). To understand AI and consequently comprehend its reliability, ethics and anything associated with it, such as data privacy and copyright infringements, one must understand Science. I am not saying you should understand every theorem, lemma or corollary. However, you need to understand and acknowledge what the fi

Design by Geoff Sence: Portfolio When I started my data science career, I quickly learned that the eight years I spent understanding the techniques, theorems, lemmas, corollaries and the laws of mathematics and physics were well spent. Nonetheless, as I began adapting my skills to the industry's data science realm, I quickly started having "nightmares", metaphorically speaking. I had no industrial experience when I started my first job in data, so I took online courses to ca

Designer: Geoff Sence Artificial Intelligence (AI), which includes machine learning and deep learning, is a technique that uses a wide range of computation and statistical power to extract information from large datasets. Depending on the problem, this can then be used for prediction. The above paragraph may sound impressive and may charm or mislead people into thinking that anyone using these models is somewhat of a genius. With the advancements in AI, anyone can use this mo

For those in the European continent, most conversations are dominated by the football championship, Euro 2024. Whatever team each of you reading this article supports, let's discuss a potential future where your country's team or favourite team (there is no judgment here), is made up of ten robot players and one robot goalkeeper. I am not saying this is a possibility... but it seems that in our race to replace the human factor in most human interactions with AI, then I do not

This is my journey, and what I am about to share is by no means obligatory to those wanting to get involved in data science. However, I am telling my story to share how becoming a data scientist is about understanding the techniques that you work with. I guess one could say that my journey started from primary school with mathematics. The subject was intuitive to me and I found it comforting. In my free time, I used to solve puzzles or watch my father solve an engine enigma a

Data privacy is often considered a phenomenon for Big Tech companies. People think that only tech companies are at risk of breaching data privacy because that is what we are learning from social media. One need only speak to another person to know how poorly data privacy literacy is shared amongst private citizens. Design by Geoff Sence From personal experience, I once brought an individual's attention that their camera was breaching my data privacy rights. They explained, th

Many posts online are saying that: a Data Scientist's role is obsolete or can be classified as Analyst or Engineer. Some claim that this role was overhyped and that data scientists would ultimately move on to specialise in analysis or engineering. Design by Geoff Sence. Saying this means that one missed the word that explains the role of a data scientist: Science Science is a word that has been largely misunderstood. Britannica defines Science as the knowledge about or study

The title alone may have your head spinning because we are more familiar with the notion of Quality over Quantity. Image designed by Geoff Sence. Of course, data science is not an exception, but to a certain extent, it may be. The quality of the data is imperative for machine learning models and AI. As I shared in previous articles, data scientists spend most of their time looking at the dataset and identifying some of the most common obstacles, such as: missing data outliers

There is a data reaction. Design by Geoff Sence AI brought about a lot of controversy. AI companies argue that #AIforGood will improve productivity and performance, and regulations may stifle advancement and experimentation. Conversely, ethical arguments advocate for guidelines and regulations to ensure that AI technology safeguards fundamental human rights such as privacy and protects against misuse and misinformation. One thing that both parties agree on is that when AI is

Bias in the data is one of the many issues revolving around data science and AI. I believe the community accepted this as one of the items to check for when assessing the data quality. But what is it, and what gives rise to a bias? More importantly, do we always need to eliminate it. In this article, I intend to explain bias and share an unpopular opinion that: To get a good model, sometimes you need to keep that bias! The reason I say this begins with the mathematical defini