The resultant effect of the knowledge society in which we live is that technological development has assumed a faster pace. The result of this is speedy advancement in the global socio-economic cum political system and its numerous paraphernalia. This in turn has impacted human development – the way we live, work, collaborate and socialize—this impact has culminated in the present state of affair in which knowledge doubles every 12hours.
The doubling of knowledge every 12hours has induced a multiplier effect on the fast-paced sphere of technological developments, and the virtuous cycle is complete.
In developing this post, I reasoned that I should provide a kind of bare bone information (or first hand knowledge) to a set of audience who may be interested in a simplified, non tech-language overview of the AI industry. That’s why I’m offering an encapsulation of the technology before presenting the article for the subject matter of this post in the concluding part of this flight.
So, if you are not interested in anything else except the crux of our article, quickly scroll down to the last section of this post to see “THE ULTIMATE INCOME GENERATOR: How AI Can Assist Anyone in Selling Anything of Value”.
But if you need a snapshot of the body of knowledge, then follow me now.
This post is written to deliver basic knowledge on AI and CHATGPT, and how you can use it to generate easy, stable and unceasing flow of income.
By following it you will gain knowledge of AI germane to your quick understanding of how you can transform your economy with the technology as you learn about the flowing areas.
❖ A simplified Meaning and Explanation of AI And CHATGPT
❖ A Brief History, Development and Evolution of AI
❖ Current State of Affairs, Trends And Advancement in AI Industry ❖ Leading Drivers of AI Innovation
❖ Prominent AI Tools
❖ The All Inclusiveness of AI and CHATGPT’s Universal Applicability ❖ Global AI Market Value and Its Economic/transformational Impact ❖ Why You Should Embrace AI
❖ AI Outlook
THE ULTIMATE INCOME GENERATOR: How AI Can Assist Anyone in Selling Anything of Value.
Let’s fly …
1. A Simplified Meaning And Explanation Of AI And CHATGPT
In simple, no brainer definition and, Artificial intelligence, or AI for short, refers to the simulation of human intelligence in machines or computer systems. It involves creating computer programs and explanation algorithms that can perform tasks typically requiring human intelligence, such as problem-solving, learning, reasoning, understanding natural language, recognizing patterns, and making decisions.
Artificial Intelligence AI is divided into two cardinal categories:
a) Narrow or Weak AI: This type of AI is designed to perform specific tasks or solve particular problems. It is specialized and focused on one area, like
image recognition or language translation. Narrow AI is not capable of general intelligence or understanding beyond its specific domain.
b) General or Strong AI: General AI, sometimes referred to as “AGI” (Artificial General Intelligence), aims to possess human-like intelligence and capabilities. It would be capable of learning and understanding across a wide range of tasks, similar to how humans can adapt to different situations and learn various skills.
AI technology is used in various applications today, including virtual assistants, self- driving cars, medical diagnosis, recommendation systems, and more, to enhance efficiency, automation, and problem-solving in different fields.
Some good example of AI models is Google Bard, Microsoft Bing, and OpenAI’s GHATGPT.
CHATGPT is a computer program that can have text-based conversations with people. It’s designed to understand what you say and respond in a way that makes sense, almost like chatting with a smart computer friend. It uses advanced technology to generate human-like text, answer questions, and help with various tasks by understanding the language you use. It’s like having a virtual conversation partner that can assist with information and communication. While CHATGPT primarily interacts through text-based conversations, it can also process and generate
text in various forms, such as summarizing information, composing emails or documents, generating code, and even translating text into different languages. So, while text-based interaction is CHATGPT’s main function, it can be used for a wide range of tasks that involve working with text and language. CHATGPT is an AI model developed by an organization called OpenAI. OpenAI is a research institute and company that focuses on developing artificial intelligence technology, including the GPT (Generative Pre-trained Transformer) models like CHATGPT.
2. A Brief History, Development And Evolution Of AI
AI’s history is marked by cycles of enthusiasm and skepticism, but recent advancements have brought it into the mainstream, where it plays a significant role in shaping the future of technology and society.
- Early Concepts of AI (1950s-1960s): The idea of artificial intelligence started as far back as the mid-20th century during which time] computer scientists and researchers began exploring the possibility of creating machines that could mimic human intelligence. Early AI efforts focused on symbolic reasoning and problem-solving.
- The Dartmouth Workshop (1956): The term “artificial intelligence” was coined at the Dartmouth Workshop in 1956. This workshop brought together pioneers in the field to discuss and advance AI research.
- Symbolic AI (1960s-1970s): AI research primarily revolved around symbolic AI during this period. Researchers developed programs that used symbols and rules to perform tasks, like playing chess or solving mathematical problems.
- AI Winter (1970s-1980s): Progress in AI slowed down due to high expectations and limited computing power. This period became known as the “AI winter” as funding and interest in AI research decreased.
- Expert Systems (1980s): AI research saw a resurgence in the 1980s with the development of expert systems. These systems used knowledge-based approaches to solve specific problems, such as medical diagnosis and financial analysis.
- Machine Learning (1990s-Present): The focus shifted to machine learning and neural networks. Researchers developed algorithms that allowed computers to learn from data, leading to advancements in areas like natural language processing, computer vision, and speech recognition.
- Deep Learning (2010s-Present): Deep learning, a subset of machine learning, gained prominence with the use of deep neural networks. These networks, particularly convolutional neural networks (CNNs) and recurrent
neural networks (RNNs), revolutionized tasks like image recognition and language processing.
- AI in Everyday Life (Present): AI is now integrated into many aspects of daily life. Virtual assistants like Siri and Alexa, recommendation systems on platforms like Netflix, self-driving cars, and medical diagnosis tools are examples of AI applications.
- Ethical and Societal Concerns (Present): As AI has become more powerful, concerns about its impact on privacy, bias, job displacement, and ethical issues have gained attention. Efforts are underway to address these challenges.
- Future Directions: AI continues to evolve rapidly, with ongoing research in areas like reinforcement learning, generative models (like GPT-3), and AI ethics. The future promises even more advancements in AI technology and its integration into various industries.
3. Trends And Advancement In AI Industry
AI is the rave of the moment in almost all spheres of personal and business progress.
It has dwarfed expert projections by becoming amenable to human existence-driven adoption that has portrayed it as the phenomenon of the time.
AI’s accessibility and adoption is bigger than that of the internet and Google in the 80s and the 90s when assessed within the same duration AI attended this mileage. This makes AI the next best thing.
Generative AI has taken the world by storm. It’s gone viral on social media and attracted billions of dollars in investment, with companies like Google and Microsoft scrambling to integrate these technologies into their products.
Current state of affairs, trends and advancement in AI industry are simply spectacular.
The ongoing democratization of AI, which means that AI tools and capabilities are becoming more accessible and affordable for everyone, regardless of their technical skills or background.
This is enabled by the emergence of no-code and low-code platforms, as well as apps that provide AI functionality with a click of a mouse.
The explosive growth of generative AI (gen AI), which refers to AI tools that can create new content, such as images, text, music, or code, based on existing data or user input.
Gen AI tools have been widely adopted by individuals and organizations across various sectors and regions, and are expected to disrupt and transform many industries.
The increasing investment in AI by governments and businesses, which reflects the recognition of the value and potential of AI for economic growth, social good, and innovation.
Worldwide, spending on AI technology will top $500 billion in 2023, according to IDC research.
Moreover, 40 percent of respondents in a McKinsey survey say their organizations will increase their investment in AI because of advances in gen AI.
The shifting talent needs and workforce effects of AI, which pose both opportunities and challenges for employers and employees. AI is expected to create new jobs and roles, as well as eliminate or change existing ones.
The steady adoption and impact of traditional AI capabilities, such as computer vision, natural language processing, speech recognition, and machine learning. These technologies have become embedded in many aspects of our society and lives,
from chatbots and virtual assistants to automated industrial machinery and self- driving cars.
Some AI tools like CHATGPT- 4 can now see, hear, and can even speak.
4. Leading Drivers In AI Innovation
Expectedly, AI innovation space is host to some of the world acclaimed ICT organizations. Here are a few of the frontlines companies and what they are acclaimed for.
a) Google: Google has been at the forefront of AI research with projects like DeepMind and the development of TensorFlow, an open-source machine learning framework.
b) OpenAI: OpenAI is known for its groundbreaking work in natural language processing and AI research, including the creation of models like GPT-3 and GPT-4.
c) Microsoft: Microsoft has been heavily investing in AI, with initiatives like Azure AI and the development of conversational AI technologies, such as the Microsoft Bot Framework.
d) Facebook (now Meta Platforms, Inc.): Facebook has been active in AI research, particularly in areas like computer vision, and has contributed to projects like PyTorch.
e) IBM: IBM’s Watson has been a pioneer in AI applications, especially in healthcare and business analytics.
f) DeepMind: Acquired by Google, DeepMind has made significant contributions to reinforcement learning and AI for healthcare.
g) Amazon: Amazon Web Services (AWS) offers a range of AI services, and the company has invested in AI for customer recommendations and logistics.
h) Baidu: A leading Chinese tech company, Baidu has been involved in AI research, particularly in autonomous vehicles and natural language processing.
i) Tesla: Tesla is known for its AI-driven advancements in autonomous driving technology.
j) NVIDIA: NVIDIA specializes in AI hardware, providing GPUs that are widely used in training deep learning models. It also specializes in the production of accelerated computing platforms that enables high-performance computing for AI application.
k) Builder.ai, a company that leverages AI to help anyone build software without coding or technical skills
