Generative AI will be a Game Changer and Suck millions of Jobs By Success Guru Professor Dr Alok Chandra

Generative AI will be a Game Changer and Suck millions of Jobs By Success Guru Professor Dr Alok Chandra

There is going to be massive layoff in world. Presently lay off is only the beginning. I believe that 99% of software and repetitive jobs position will soon become obsolete. Software giants I believe like Infosys, TCS, and Wipro might face south wind. According to experts, the disruption caused by artificial intelligence will be very significantly visible in another two years or so, therefore it's imperative that we prepare for this new IT order.

 Generative AI like ChatGPT will be used in the same way that we use Google now. A brand-new chatbot with artificial intelligence called Chat-GPT has swept the internet by storm. The term AI combined with machine learning has made way for fresh branding strategies. The accuracy of predictions will increase, offering businesses considerably stronger power. This shift would be facilitated by ChatGPT, eliminating the need for Google.

The emergence of generative AI has the potential to fundamentally alter the commercial landscape. This technology has the potential to disrupt industries and the way businesses are run, since it enables the generation of fresh content by learning from current data. Generative AI has the ability to boost efficiency and productivity, cut costs, and provide new development prospects by making it possible to automate numerous jobs that were previously performed by people. As a result, companies who are able to use technology well are probably going to have a big competitive edge.

Though Not perfect but it is overwhelmingly impressive.

Products like ChatGPT and GitHub Co-pilot, are taking technology into domain which  once thought to be reserved for humans. With the  help of generative AI, software’s can now impressively exhibit creativity.

It will be a fantastic tool for resource management, governance, and oversight. Data engineering, energy optimization, ESG, sustainability, and SDG coding, Regular communications, SCM, mobility, project and programme monitoring, and spatial-temporal-socio analysis and health & medical. When compared to ChatGPT-3, current software is substantially slower.

Modern language model called ChatGPT was created by Open AI.  It is a variation of the GPT (Generative Pre-training Transformer) paradigm, which produces text that resembles human speech by training on enormous amounts of text data. A sizable corpus of literature, including books, papers, and conversations, is used to train the model, which discovers linguistic patterns and links. In various aspects, ChatGPT-3 differs from earlier AI platforms. The size of the model is one of the primary variations. With 175 billion parameters, ChatGPT-3 is an extremely big language model compared to earlier models. As a result, it can comprehend and produce writing at a level that is more human-like.

It can also carry out tasks that earlier models couldn't, such as question answering, summarising, and sentiment analysis.

Additionally, ChatGPT-3 is made to be more durable and contextually aware, enabling it to manage discussions that are more complicated and nuanced while still comprehending the context.


It is a machine learning model that has been taught to anticipate the subsequent word in a string of words based on the context of the preceding words. It does, however, have certain restrictions. For instance, it is restricted to the knowledge that it was educated on since it cannot access the internet or other external information sources. Since we lack the requisite first-hand experience or preconceived notions, we must rely on the wealth of information readily available online. This is because it is a machine learning model and hence cannot think or feel in the same way that humans do. It is not susceptible to manipulation since it lack the human faculties of belief, emotion, and opinion.


ChatGPT-3 has been put to good use by a number of different businesses and organisations. For instance, Open AI has collaborated with other organisations like Microsoft so that their Azure AI and Language Understanding services may make use of ChatGPT-3. Replika, Hugging Face, and are just a few of the firms whose products were created using GPT-3.

OpenAi’s DALL-E is a deep learning model designed to create digital pictures based on textual cues. OpenAI's DALL-E, an image-generating system that employs a modified version of GPT-3,

OpenAI has built a fantastic search engine for aggregating test data and generating on-the-fly solutions. I expect Chat GPT to have more layers as text data processing is increasingly sophisticated, but typically 3 layers are thought to offer excellent results, especially with mathematical problems depending heavily on uncertainty in probability.

Coding and programming software-based solutions account for the bulk of expected use. At some point in the future, Chat GPT will serve as a central hub for all the resources and applications that may be used to solve any problem. It will function as the equivalent of Google for coders.

The search engine's associated links come up next. It will take some time before we know how successfully it can mine and aggregate findings to an acceptable standard. However, I do not think that this is going to take too much time.

The predictive analysis of its data set is robust. Fast and accurate AI is available here. I find it to be an efficient tool for use in Decision Support systems and risk-based forecasting.

Some examples of how businesses might benefit from software like ChatGPT include:

Translated from the Language: Finishing the Text Starter for a Discussion: Summarization: Examining Opinions Handling texts, text mining, and related processes Information sharing, simultaneous translation, and international dialogue. Methods within the law, help with homework, Sample questions and answers for a certain exam, Method for Inquiry Collecting information Conceptualizing potential marketing materials, creating software programmes Aspects of the sales procedure are becoming automated. Providing support once a sale is made Delivering individualised guidance, automating procedures to save time and effort. The process of onboarding new customers is simplified by the use of language translation, better customer loyalty and retention through increased consumer involvement.

The service industry has a lot of room for growth, especially in customer service.

Content creation for marketing, social media, and technical sales (containing text, photos, and video); development of business-specific virtual assistants (e.g., for the retail sector). Operations, or the process of creating to-do lists in preparation for carrying out a certain job effectively. Information technology/engineering: coding, documenting, and inspecting. The risk and legal departments are responsible for addressing difficult inquiries, researching extensive volumes of legal material, and putting together and evaluating yearly reports. Research and development (R&D) aims to speed up the process of finding new medicines by increasing our knowledge of illnesses and uncovering new chemical compounds.

Developers and researchers in the field of software have sped up their formerly laborious code-writing processes. The exact same code that automated chat services can generate in under a minute.

The GPT-3 technology developed by OpenAI has the potential to revolutionise the fields of science and computer science. We can generate code snippets, do easy tasks, and get guidance on more sophisticated coding projects—all with the help of GPT-3. Human evaluation and supervision are still essential for ensuring high-quality results in both research and coding.

The corporate world is headed for a major shakeup in the next year or two because of ChatGPT, which has enormous potential and will revolutionise the way we do business. In next one or may be two year’s Chat GPT will revolutionise and will come out as a game changer.