ChatGPT

By Haruna Chiroma

Before the advent of the internal combustion engine, imaging two horses engaging in a conversation about the era of internal combustion engines. One of the horses envisions a transformative job landscape with new opportunities, while the other horse opposes the idea, seeing it as a potential threat to their relevance in transportation and a possible complete displacement from the realm of transportation. Horses have no position in the post internal combustion engine era. That is my prediction for the future of the movie and music industries in Nigeria.

The Nigerian movie industry is notably divided into two main sectors: Nollywood, primarily representing movies from the southern region and Kannywood, which focuses on movies from the northern region.

In the music industry, songs are typically sung in English, Hausa, Igbo, and Yoruba. Both the movie and music industries are currently confronting the looming threat of collapse due to the disruptive impact of AI innovations, inventions, and discoveries.

The process of writing movie scripts by scriptwriters is time-consuming and varies in duration depending on the complexity and proposed length of the film. It can take anywhere from two weeks to three months to complete the initial draft before further refinement. However, with the advent of AI tools like ChatGPT, scriptwriters can significantly enhance their productivity. By utilizing ChatGPT, writers can expedite the scriptwriting process, potentially reducing the time required from months to just one or two days for complex movie scripts.

The movie industry is on the verge of collapse in the near future with the emergence of generative AI tools capable of generating video from written text. In the near future, traditional methods of movie production may become obsolete. Instead of the laborious process of location shooting, hiring actors, coordinating camera movements, applying makeup, arranging logistics, etc. a movie script written by scriptwriter can simply be fed into a text-to-video tool converter. This innovative technology will then generate a movie video representation of the script, revolutionizing the way movies are created. The tool comes equipped with video editing features, enabling users to fine-tune the video to match their requirements. The process that involves many people with different expertise working from different perspective may likely require between 2 – 3 people instead of the large number of people required in the traditional process of movie production.

Recently, OpenAI unveiled Sora, a text-to-video conversion tool, garnering widespread attention from mainstream media. This development prompted a filmmaker in Hollywood, Tyler Perry to suspend his 4 years $800 million planned movie production studio expansion arguing that Sora will eventually impact every aspect of the movie industry and jobs in the entertainment industry.

In an intriguing development, yet another valuable AI tool for video translation has emerged. This tool enables users to translate their videos into different languages such as Dutch, French, Arabic, Swahili, Chinese, Malay, and more. By doing so, the movie video creators can extend their reach beyond Nigeria and cater to audiences across Africa, Europe, and Asia, thereby expanding their potential viewer base to a larger and more diverse audience.

A deepfake movie can be produced by using the faces of renowned movie stars from both Kannywood and Nollywood, eliminating the need for these actors to physically appear in any physical location. The movie developer only requires the consent of the actors to use their faces in the deepfake video, adhering strictly to ethical guidelines in the creation of deepfake content. With these permissions in place, a movie can be crafted featuring the prominent actor(s) as the central characters, offering new possibilities in cinematic storytelling.

These emerging concepts pose a significant challenge to the movie industry, making it increasingly difficult for the traditional model to sustain itself. This trend mirrors the significant decline or almost collapse witnessed in industries such as landline telephones, photo shops, and magnetic tape, suggesting that the movie industry may face a similar fate of eventual collapse to the changing landscape.

Already the adult content industry is facing tough competition from deepfake adult videos generated by AI tools. Recently, several dedicated platforms have emerged, exacerbating challenges for the traditional adult movie sector. These platforms are attracting millions of visitors, with one particularly renowned platform drawing over 17 million viewers monthly. Typically, the platform features short deepfake adult content videos as teasers, enticing viewers to access the full content elsewhere.

While the short videos span various platforms, the primary one serves primarily for advertising and provides links to other platforms where complete videos are available for purchase.

The proliferation of deepfake adult videos has led to a surprising revelation: these videos are not freely accessible but are instead sold in dollars, accepting payments via credit cards, debit cards, or cryptocurrency. This burgeoning industry has now become a multimillion-dollar enterprise. For anonymity and ethical reasons, I intentionally omitted specific platform names to prevent further traffic influx.

This discourse underscores a poignant observation: the inevitability of the movie industry’s potential decline due to the transformative impacts of AI research. In January of this year, a deepfake pornographic image featuring a celebrity, Taylor Swift surfaced on various social media platforms. The video quickly gained traction on X (formerly Twitter), spreading rapidly like wildfire and amassing over 47 million views in less than 24 hours. Despite ethical considerations, many X users shared the video extensively before it was eventually removed and searching for the image was blocked by X. I foresee the collapse of the adult content industry in the next 3 years with the deepfake videos taking over.

In the music industry, numerous AI tools for music generation are currently in various stages of development, testing, or initial release. For example, MusicLM, an AI tool developed by Google, is designed for composing music and has shown promising capabilities in generating music.

Currently, an advanced version called MusicFx is undergoing testing in Google’s test kitchen before its public release. Users can simply prompt ideas into the music tool, and it will automatically compose the music. This advancement suggests that the future of music composition may require fewer people, as one individual can prompt the tool with ideas to generate music without the need for multiple collaborators.

Another tool is Suno V3, it generates music from text easily. Therefore, the music industry is at the verge of facing stiff competition and eventual collapse of the industry from these revolutions from AI.

Haruna Chiroma, Ph.D. Artificial Intelligence University of Hafr Al Batin, Saudi Arabia, freedonchi@yahoo.com.

By Bilyamin Abdulmumin

While toggling between TED videos, my mouse hovered over a talk titled “Can AI Catch What Doctors Miss?” which I decided to watch. The talk was given by a revered Cardiologist, Eric Topol. He espoused the possibility of AI surpassing expert physicians. To lend credence to his argument, he showed a picture of a retina to which he posed a question: can retina experts identify the gender by merely looking at this retina? He then replied that the expert chance of getting it correctly is only 50 per cent, while AI has an impressive chance of 97 per cent. So he argued if an AI could have such high precision compared to humans, how about relying on them to spot some diagnoses doctors have been missing? Dr Topol buttressed the idea with real examples.

A six-year-old boy suffering from an undiagnosed disease would shuttle between 17 experts, but for three years, his condition could not be diagnosed. So a decisive inspiration came to his mum, and she decided to consult ChartGpT by describing all the signs and symptoms she observed from the boy, and within a blink of an eye, the AI would successfully diagnose the condition:  “occult spina bifida”. After the doctors worked on the result, the boy became “perfectly healthy well”.

Topol finally closes his remark by recounting his conversion with an apprenticeship student one day after seeing patients together. He reflects the student how lucky he was to practice during an AI era, as he will connect with patients in a  way they could only imagine: the help of getting assistance for diagnosis.

This talk reminds me of my own mental note about ChartGPT—the prospect of the chatbot against the then-savior software like Grammarly, Quibolt, Google, etc.

Just as the advent of the phone rendered a plethora of gadgets obsolete—such as cameras, wristwatches, calendars, radios, recorders, calculators, tape players, speakers, torchlights, TVs, etc—the introduction of ChatGPT is poised to usher in a similar transformation. ChartGPT can make many tools redundant, including Grammarly, Quillbot, Turnitin, Google, Wikipedia, Britannica, and many more.

Crafting error-free text was a significant challenge for young writers: the intricacies of grammatical structures were daunting, especially for us bilingual individuals. But the advent of Grammarly, then, was revolutionary. With Grammarly, writers found relief from the hassles of English grammar intricacies. They could focus on generating a draft, confident that Grammarly would do the rest. But now, ChartGPT, in a similar vein, emerges as a game-changer.

Quillbolt is a six of one and a half dozen of another with Grammarly.

The quest for originality is paramount, mainly when composing a manuscript where maintaining a high degree of uniqueness—often limited to around a few per cent—is crucial. Authors submitting manuscripts endure a nerve-wracking moment as their work undergoes scrutiny through Turnitin software, hoping for a positive outcome. But with the introduction of Quillbot, much of this drama was alleviated. However, ChartGPT takes this capability to another level.

A mere decade ago, the idea that Google, with its dominance in information retrieval, could be overshadowed by a newer invention would have seemed far-fetched. Enter ChartGPT, and suddenly, the status quo is challenged.

While platforms like Wikipedia and Britannica offer ready-made articles, ChartGPT takes interaction to a whole new level. It doesn’t just provide answers; it collaborates with users to deliver precisely the information they seek.

Another hassling undertaking is programming. Coding used to be akin to a jewel in the crown or an elusive skill that felt like searching for a needle in a haystack. Few possessed the ability, and its intricate, time-consuming nature made those with such expertise exceptionally rare. However, for the proud coding masters, ChartGPT has emerged as a liberator. It can unravel the complexities of coding and teach it in a non-specialist manner. With ChartGPT, the once formidable barriers to coding knowledge are dismantled.

As Professor Topol reflected, I have also been in awe of ChartGPT transformations. Encountering it during my student years feels like a true blessing. Its impact on reshaping the educational landscape, especially in 2023, is remarkable. Being a student at this transformative juncture allows me to witness and reflect.

For optimal utilization of ChartGPT, however, a strategic approach should be involved. One has to initiate one’s efforts by crafting a draft before turning to AI for assistance. For instance, when comparing a request for a 250-word article on climate change without a draft to someone who provides a 50-word draft for improvement, the latter receives a more refined result. For even finer results, breaking down tasks into smaller components yields superior outcomes.

The same thing applies to coding with ChartGPT. If you ask ChartGPT, for instance, to generate a code for a specific task, there’s a likelihood that it might not run perfectly, leaving some details for you to fill in. However, if you start by writing your own code, even if it doesn’t run initially, and then turn to ChartGPT for assistance, it can swiftly identify and correct the errors.

Bilyamin Abdulmumin is a doctoral candidate in Chemical Engineering at ABU Zaria, a public affairs commentator, and a science writer.

By Ismail Ismail Tijjani

Large Language model (LLM) is a subset of Generative AI that focuses on generating human-like text based on the input it receives. Evidence shows how good it is in generating creative text formats, like poems, code, scripts, musical pieces, emails, letters, etc. Chatgpt plays a significant role in bringing LLMs to wider public attention, though it wasn’t the first one. I will use Chatgpt throughout this article because of its popularity, though there are other popular ones like Gemini, Bard.AI, LaMDA and much more.

Let me provide a very simple description of how ChatGPT works. Just imagine you enter a library and ask the librarian a question. The librarian will first try to understand your question and then scan the shelves, looking for books they think might contain your specific answer. Using their records and expertise, they connect related stories from different books and give you the best possible answer. This is what ChatGPT does in a few seconds.

ChatGPT underwent training using an extensive and diverse internet dataset, which covered a wide spectrum of content ranging from different subjects, styles, and perspectives. Its core skill lies in tranformer architecture, a neural network which is primarily designed for language processing to encode an input text, analyze its structure and meaning, and decode it to produce an output by predicting the most likely next word in a sequence.

Certainly, the introduction of new technologies often sparks heated debates. Critics often strive to oppose and even reverse these advancements. However, their efforts typically falter in the end. Some critics may genuinely misunderstand the technology, while others, perhaps a majority, are driven by the pursuit of publicity rather than accurate assessment.

ChatGPT wasn’t an exception. When it was launched in October 2022, some people argued that it would make students lazy, lead to job loss for editors, result in high plagiarism, breach copyrights, steal people’s data, exhibit sentiment, intentional bias, spread disinformation, create deep fakes, and much more. We will discuss some of these concerns below. Some of the allegations are true and have already been addressed, while others are false.

ChatGPT lacks the ability to discern whether information is biased, disinformation or false. It operates based on its programmed structure and produces results accordingly. OpenAI, the creator of ChatGPT, has taken measures to enhance the model. Although the technical details haven’t been disclosed, it likely involves implementing guardrails and filtering mechanisms to address accusations of misinformation, bias, falsehood and more.

For students and researchers, ChatGPT will serve just like an advanced internet search engine that will generate output after going into multiple webpages, saving time and stress hopping between sites. It will in no way make students lazy, However, some concerns related to students’ use will be discussed in a later article.

Its ability to remember previous prompts, though impressive, doesn’t imply sentience. It’s merely a clever technique within its architecture. This raises separate questions about the path to achieving true artificial general intelligence (AGI), discussed in my previous article. It is only a technique in tranformer that makes it capture it.

The impact of ChatGPT on jobs is a complex and nuanced issue with both potential downsides and upsides. While some job losses are inevitable, they will likely be offset by the creation of new ones. Adapting to this changing landscape through education, reskilling and responsible policymaking is key to ensuring a future where AI benefits everyone.

Despite the evident improvements seen since ChatGPT’s initial release, OpenAI must continue to dedicate significant resources to refining its model. This is crucial not only to mitigate legal risks but also to enhance its accuracy and reliability for responsible public use. While striving for absolute perfection is unrealistic, reaching a consistently high level of trustworthiness should be a priority. Additionally, users must be mindful of the model’s limitations and exercise critical judgment, fact-checking, and verification before relying on its output.

AI is here for good. Innovation often sparks a variety of perspectives, and AI is not an exception. Some people believe that AI has the potential to solve some of the world’s most pressing problems, such as poverty, hunger, climate change, corruption and disease. Others are concerned about the potential for misuse, such as the development of autonomous weapons systems or the use of AI to manipulate people.

AI is not like any other innovation we have seen before in the history of humankind. It is among the most powerful of all, and it is likely to be among the last innovation that we ever need.

AI is already making significant positive impacts in various industries, such as healthcare, finance, retail, manufacturing and many others. Of course, like any industry, there may be individuals with malicious intent in the AI sector who are willing to exploit it for negative purposes. For example, I recently came across a women-uncovering app with high precision that raised concerns. However, the actions of these individuals should not lead to the shutdown of the entire industry.

We don’t shut down the arms and weapons industry because of terrorists, the financial industry because of fraud, the biotechnology industry because of bioweapons or social media because of misinformation and hate speech. Instead, we regulate them by establishing governing bodies to oversee their operations and foster collaboration between top companies, stakeholders, researchers and the government to develop effective solutions. This approach will also be applied to AI.

Our primary focus should be on humanity. It is crucial for everyone to actively participate and collaborate in order to develop effective solutions that will propel us and the industry forward as a unified whole.

Path to Artificial General Intelligence (AGI) 1: the year 2023 stood out as an exceptional period in the AI industry, marking a significant moment when the masses truly connect with the essence of AI.

AI has been around for years, primarily utilized in backend functions like relevance ranking, personalization, spam detection, and more. ChatGPT was the remarkable innovation that astonished the world, revealing the true potential of AI. While it may not have surprised researchers who had already witnessed AI capabilities in the lab, its impact on a broader audience is undeniable to the extent that many non technical individuals use the words AI and ChatGPT interchangeably, thinking its same thing.

Other notable innovations in 2023 include Hugging Face, Google Bard, Capcutand many others, all these are great innovations we have seen in 2023.

Are these innovations clearing a path to Artificial General Intelligence (AGI), which informally means machines reaching human-level intelligence? This question remains unclear to researchers, as there are two camps with differing opinions on the matter. Some believe AGI is imminent, while others hold a more skeptical view.

Yann LeCun the chief AI scientist in Meta is among those with skeptical perspective, he believes that Language models like ChatGPT that people are using as an evidence that AGI is imminent are not as smart as a cat which is the truth and believes it will happen in decades or even a century — a point of view that I share.

For machines to achieve true intelligence, they must possess both cognitive and metacognitive abilities. While significant advancements have been made in cognitive AI, bridging the gap to metacognitive intelligence remains the key barrier. Researchers are diligently seeking solutions to overcome this challenge. For machines to be metacognitive intelligent, which necessitates the ability to sense the environment and effectively process and interpret sensory signals. Our discussion was focused on the process of it being intelligent alone, not as intelligent as a human being, which is the AGI. This clearly shows that we are nowhere near AGI.

The timeline of AGI is not only a matter of time but rather depends on the speedy research and innovation advancement. Improvement in advanced neural networks, symbolic reasoning, embodied cognition, unsupervised, and reinforcement learning will make a great impact in clearing the path to AGI.

The path to AGI is not a solitary trek for AI researchers. It demands a symphony of minds, where scientists, physiologists, engineers and other researchers from diverse fields join hands in a grand collaborative effort. Only through their combined expertise and tireless dedication can we hope to unlock the secrets of true machine intelligence.

By Muhammad Ubale Kiru

Whether Artificial Intelligence (AI) can surpass human intelligence is a complex and debated topic. Many scientists, AI users, and observers have argued whether what we see in movies regarding AI surpassing human intelligence will come true. I have asked this question several times, and colleagues at work and friends on social media have asked me whether this myth can be true. Since then, I have been gaining momentum, strength, and proof to be able to answer this question.

However, something triggered my urge to share my thoughts on this question today after I received a notification from OpenAI. This company developed the famous ChatGPT, informing users about their new “Terms of Use and Privacy Policy.” One of their newly updated clauses says, “We have clarified that we may collect information you provide us, such as when you participate in our events or surveys.”

The above statement has directly or indirectly revealed that if you agree to use ChatGPT, you must surrender to the fact that OpenAI will collect personal user information for research and training purposes. A non-specialist will not understand the implications or consequences of that. One may think it is an ongoing activity because social media companies like Facebook, X (formerly Twitter), etc.) collect users’ personal information for business and quality assurance purposes.

So, what is the real implication here?

It is simple. AI and machine learning algorithms are like weeds on a plant. They rely heavily on data to learn. The more data they consume, the more intelligent they become. Most of us are already using AI to solve our day-to-day activities and problems. For instance, tasks that used to take me seven days to complete can now be done in 10 minutes. I am handing over my tasks to AI to handle them for me.

Each time I ask AI to handle my task, AI is learning the task more and more. Humans perfect their skills through constant and regular learning. Now, I’m handing over most of my tasks to AI; AI learns while I lose because previously, I learned from my work experiences, and now AI does the work for me. AI is becoming more intelligent and capable, while I am becoming less intelligent and less capable. By the way, I’m not the only one in this mess. Nowadays, even programmers who rely on constant practice to improve their coding skills are also using AI to generate codes or programs that used to take months to complete.

ChatGPT, for example, is used by millions of users daily. When it was first developed, they used random internet data to train its learning models. Now, they are using real-time human input (data) to train the AI. If you look at the core foundation of any AI in the world, it is designed to capitalise on learning from its environment. Our phones are AI-enabled, laptops are AI-enabled, web apps, games, calendars—everything is now AI-enabled. The more we use AI, the more AI learns about us.

Today, your phone keypad knows more about your words and thoughts than you know yourself. As you begin typing, it completes the rest for you. So, with time, your AI-enabled devices would learn more about you than you could ever learn about yourself. Thus, what is left of us if AI has learned everything about us? In Sun Tzu’s book, The Art of War, he says, “Knowing your enemy is akin to winning half the battle. Understanding their strengths and weaknesses provides a strategic advantage that can pave the way to victory.”

The question of whether AI can start a revolution or take over the world, as we have seen in movies, is another debate for another day. The Tesla CEO Elon Musk and AI guru Lex Fridman are among the few people in the world who are always concerned about the potential danger of AI and have continued to call for regulations before AI gets out of hand. The technology has very speedy and staggering growth potential. It is growing at a breakneck pace right now.

To this end, I urge policymakers and regulatory bodies to take necessary precautions before AI gets out of control. AI is undoubtedly powerful, and if unleashed without caution, it can create devastating chaos.

Let me hear your thoughts in the comment box.

(c) Muhammad Ubale Kiru