How is AI Transforming Money Making? Explore the 4 Directions

Author(s): UPDF

Originally published on Towards AI.

Large language models have emerged as transformative tools with extraordinary capabilities. Nowadays, you can barely see a field where AI hasn’t found its application. From content creation and customer service to data analysis and software development, AI has become a necessary tool for organizations seeking to optimize business. This article aims to discover these models’ diverse use cases and directions in making money.

A Comprehensive Overview of AI Large Models and Their Common Use Cases

Large Language Models are advanced artificial intelligence (AI) systems that understand and generate human-like text. These innovative computer programs learn a lot from many different types of information to understand language well.

Unlike older recurrent neural networks (RNN), transformers handle input sequences all at once instead of one by one. This parallel processing capability lets data scientists use GPUs to train transformer-based language models, which makes the training process much faster.

Top LLMs Models

Here are some of the most essential large language models currently in use. They specialize in natural language processing and significantly impact how future models are designed.

● GPT-4: This LLM is the newest and most significant model in OpenAI’s GPT series, launched in 2023. Like its predecessors, it uses transformers, but with a much higher number of parameters, over 170 trillion. Unlike the earlier versions, GPT-4 is a multimodal model that can understand and create language and images.

● PALM: The Pathways Language Model (PALM) is a big 540 billion parameter transformer-based model by Google, and it’s the brain behind the AI Chatbot Bard. It was trained using Google’s special machine-learning hardware. This LLM is good at figuring out things like coding, sorting information, and answering questions by breaking down complex tasks into simpler ones.

● BERT: Google introduced BERT in 2018 as a family of large language models (LLMs) based on transformer architecture with the ability to transform data sequences. This LLM was initially pre-trained on extensive data and later fine-tuned for tasks such as natural language inference with 342 million parameters.

● Claude: Claude Large Language model (LLM) by Anthropic is designed for constitutional AI. This means it follows principles to ensure the AI assistant it powers is helpful, safe, and accurate. Anthropic uses Claude for two main products: Claude Instant and Claude 2.

Here is a chart representing the accuracy of prompt responses of different LLM models. You can observe this chart to get an idea about their accuracy.

Use Cases of Large Language Models

Numerous use cases for Large Language Models (LLMs) in AI cover a broad range. We are still exploring the possibilities and applications of LLMs in our work, but some everyday use cases include the following.

● Analysis of Sentiments: Some LLMs analyze text sentiments, aiding organizations in data collection, feedback summarization, and rapid identification of improvement areas. Grammarly’s “tone detector” is such an example that utilizes AI for sentiment evaluation in content.

● Coding and Development: AI, like GitHub Copilot and Amazon’s CodeWhisperer, automates code completion and has caused concern among developers about job security. Also, MDN’s AI Help feature can be employed to enhance development skills.

● Moderation of Content: These models play a crucial role in moderation on social media platforms, identifying and removing offensive content like hate speech and inappropriate media. Hubspot’s AI content moderation feature is an example of this capability.

● Chatbot Service: LLMs are essential in developing customer support chatbots for effective communication and assistance. Salesforce is an example of a company providing such services.

What Future Holds for AI LLM Implementation in Various Industries?

Gradually, LLMs are approaching human-like capabilities with a rapid success rate. This indicates a growing interest in robot-like LLMs that mimic and sometimes surpass human brain performance. Here are some reflections on the future of LLMs:

● Transformation of Workplace: LLMs are composed to be transformative in the workplace, like the impact of robots on repetitive manufacturing tasks. They will likely streamline monotonous and repetitive tasks, customer service chatbots, and basic automated copywriting.

● Synthetic Data Training: Researchers are actively developing large language models to generate synthetic training data. In a recent study, Google researchers built a large language model capable of crafting questions and fine-tuning itself using curated answers. It will lead to new state-of-the-art performance in various language tasks.

● Conversational AI enhancement: AI in LLMs is expected to significantly enhance the performance of automated virtual assistants like Alexa and Siri. This improvement will empower these virtual assistants to better understand the intent and respond to more complex commands. By doing so, it contributes to a more natural and sophisticated user experience.

● Sparse Expertise: A sparse expert model is a concept where a model can activate only the necessary parameters to respond to a specific prompt. LLMs with over 1 trillion parameters, like Google’s GLaM, are considered sparse models. Forbes reports that GLaM uses two-thirds less energy for training than GPT-3 and outperforms it on various natural language tasks.

Which Fields Remain Untouched by AI Development?

We adapt to an AI-centric lifestyle in almost every personal and professional field. However, there are some roles that provide support, service, or comfort through subjective experiences or conversations. So, this section will talk about some of those roles and jobs AI can’t replace.

1. Artistic Performance

AI will never be able to take over roles in the performing arts. The unique expressions, agility, and precise movements exhibited by professional dancers and theater artists cannot be replicated by AI. Tasks like directing a play or choreographing a performance are beyond AI’s current capabilities. The same applies to performers like magicians, acrobats, and circus artists.

2. Management and Leadership

Managers and leaders evaluate market trends and long-term business strategies in any organization. Their decision-making process involves analyzing numerous factors, assessing risks, and making choices that align with the organization’s objectives. So, it requires emotional intelligence to achieve a balance between impartial decision-making and the overall well-being of the company.

3. Counselling

Counseling and therapy-related fields remain irreplaceable by AI for valid reasons. These activities require empathy, active listening, and a deep understanding of human emotions. While AI can contribute to predicting disorders, tailoring therapies, and offering immediate support, the role of counseling remains beyond AI’s reach.

4. Marketing Insights

While AI excels in streamlining data analysis and automating tasks like providing statistics and results, it falls short in handling human emotions. For marketers, decisions often rely on human response more than raw data. Thus, the strategic thinking and creative imagination required to build audience-centric campaigns are not among AI’s capabilities.

AI Involvement to Boost Revenue in Professional and Personal Life

Large Language Models not only made our lives easier in data handling and processing but also gave us a boost in revenue and productivity. In this section, we will highlight some of the prominent involvement of AI in our personal and professional lives:

1. AI in Productivity Tools

A recent Goldman Sachs report suggests that up to 300 million full-time jobs could be replaced by AI-driven applications. However, it also indicates the potential creation of hundreds of new job categories, contributing to a projected 7% annual boost in global productivity over 10 years. This information might seem shocking, especially for those entering the workforce as they navigate career development.

A study was carried out to test the role of AI in boosting employee productivity. The researchers studied the effect of AI on writing, customer support, and programming productivity. You can see the results of this research in the following chart.

UPDF AI is one of the leading tools with AI integration that plays a role in revenue and productivity growth. This AI tool is ChatGPT integrated and can perform several intellectual functions. You can ask any query and get highly optimized and relevant responses. Also, you can handle your important documents and data sets with its data management capabilities. Other than that, you can use its summary and translation functionality to boost productivity.

You also have the option to chat with its GPT-integrated system about any topic in the world. Moreover, with the help of UPDF AI, you can rewrite the content of your document or get the list of main points discussed. It can even help you understand the graphs and tables present in your document. All these functionalities make UPDF an all-in-one productivity tool.

Other than this, AI can also assist a professional in boosting work performance and enhancing the productivity of business. Generative AI can improve the performance of a highly skilled worker by up to 40% compared to those who do not utilize it. Also, a study conducted by the National Bureau of Economic Research (NBER) revealed that the productivity of customer support agents increased by almost 14% through AI tools.

2. AI in Social Media and Entertainment

Artificial intelligence in the Social Media Market is expected to witness substantial growth, with an estimated size of USD 2.10 billion in 2024 and a projected increase of USD 7.25 billion by 2029. Social media has emerged as a primary source of customer intelligence data. The rising number of social media users drives the demand for AI solutions to understand customer preferences.

Furthermore, Large Language Models (LLMs) empower media and entertainment entities not only to develop interactive experiences but also to elevate existing ones. Whether applied in gaming, virtual reality, sports, or interactive advertising, LLMs introduce fresh opportunities for user engagement and revenue generation. Some key players investing in artificial intelligence in sports and other entertainment are represented in the chart below.

Moreover, the market is fueled by integrating artificial intelligence with social media for effective advertising, gaining a competitive edge. Additionally, institutions are heavily investing in banking assistants, utilizing chatbots with AI interfaces to engage with clients. One social media app that uses AI is Snapchat, which serves users with an AI chatbot named “My AI.”

3. AI in Marketing

Artificial intelligence (AI) is anticipated to bring significant transformation to the marketing field, as highlighted in a McKinsey study. The study identifies marketing and sales as the business function with the most effective potential financial impact from AI. This underscores the importance for marketers to leverage AI, as it is a highly influential and transformative technology in the industry.

According to the eMarketer study, AI has deep roots in the marketing industry. The results of this study will clearly shock you. Let’s analyze the results to get a better perspective on the implementation of AI in marketing.

This chart clearly shows that the role of AI is going to be significantly increased in the marketing and advertising fields. One more research predicted that AI in marketing is expected to experience a CAGR of 25.68% from 2023 to 2032, leading to a valuation surpassing 145.42 billion by 2032.

Facebook and Google stand as the most prominent online advertising platforms, providing tools that utilize a combination of audience segmentation and predictive analytics. Another tool is Buzzfeed, which operates as a genuinely AI-driven content platform, employing a strategy-focused approach. A study shows that over 80% of professionals in the industry incorporate various AI technologies into their online marketing efforts.

4. AI in Family Assistant

AI has become integral to numerous everyday applications and tools, such as emails and digital calendars. This discussion will dig into how AI can assist in automating tasks with the appropriate apps and tools. Also, it allows individuals to enjoy more quality time with their families.

Planning meals and grocery shopping often takes time, but AI can simplify the process. Applications like Mealime and Paprika can generate meal plans for your family’s preferences and dietary requirements. AnyList is another app that enables the creation of synchronized shopping lists for the entire family.

As items are used, they automatically get removed from the list. Additionally, you can save favorite recipes and meal plans to streamline future grocery trips. Virtual assistance has become an essential part of modern households. The following graph represents the aspects in which families would like assistance from AI in managing their households.

Other than that, Milo is a company with the goal of serving as an AI copilot for parents. They are actively participating in the beta OpenAI plug-in program alongside well-known entities such as Instacart, Expedia, and OpenTable. Milo’s approach involves combining human expertise with the latest capabilities of LLMs to create an efficient copilot for handling detailed and complex tasks.

Conclusion

After all that discussion throughout the article, we can surely say that AI is going to rule every sector in the near future. It is up to humans how well they adapt to the situation and utilize AI to make money. Several opportunities are up for grabs as the world of technology is changing rapidly. If you want to keep up with technology, you should learn to use AI for money-making.

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Published via Towards AI