Navigating the AI Landscape: Choosing the Right AI for Your Needs

One of the trending topics in AI is the use of AI to augment human intelligence rather than replace it. According to experts, using AI at a larger scale will add as much as $15.7 trillion to the global economy1. Large Language Models (LLMs) are a type of AI that are currently trained on a massive trove of articles, Wikipedia entries, books, internet-based resources and other input to produce human-like responses to natural language queries2.

If you're looking for a way to improve your business, your productivity, or your creativity, you might be tempted to jump on the AI bandwagon. After all, artificial intelligence is everywhere these days, and it promises to solve all kinds of problems and make your life easier. But before you rush to adopt any AI solution, you should ask yourself two questions: Why do I need AI? And which AI should I use?

Not all AI is created equal, and not all AI is suitable for every task. Some AI systems are specialized and can only perform specific functions, while others are more general and can handle a variety of challenges. Some AI systems are transparent and explainable, while others are black boxes that operate in mysterious ways. Some AI systems are ethical and trustworthy, while others are biased and unreliable.

In this blog post, we'll help you navigate the complex and confusing world of AI, and give you some tips on how to choose the right AI for your needs. We'll also warn you about some common pitfalls and mistakes that you should avoid when using AI, and how to spot the wrong AI that could harm you or your goals.

There are several Large Language Models (LLMs) available today that are used for various use cases. Here are some of the major LLMs and their use cases:

1. GPT-3: GPT-3 is one of the most popular LLMs available today. It is used for generating text, summarization, and translation1. It is also used in chatbots and virtual assistants2.

2. T5: T5 is another popular LLM that is used for text generation, summarization, and translation3. It is also used in chatbots and virtual assistants2.

3. BERT: BERT is an LLM that is used for natural language processing (NLP) tasks such as sentiment analysis, question answering, and text classification3. It is also used in chatbots and virtual assistants2.

4. RoBERTa: RoBERTa is an LLM that is used for text classification, question answering, and language modeling4.

5. XLNet: XLNet is an LLM that is used for text classification, question answering, and language modeling4.

6. GShard: GShard is an LLM that is used for large-scale training of models5.

7. Facebook has recently released LLaMA (Large Language Model Meta AI), a state-of-the-art foundational large language model designed to help researchers advance their work in this subfield of AI1. Facebook also has OPT (Open Parameter Training), which is a platform that democratizes access to large-scale language models2.

8. Google has BARD (Bidirectional Encoder Representations from Transformers AutoRegressive Decoder), which is an LLM that is used for natural language processing tasks such as text generation and summarization3.

The choice of LLM depends on the specific use case. For example, if you want to generate text or summaries, GPT-3 or T5 would be a good choice. If you want to perform NLP tasks such as sentiment analysis or text classification, BERT would be a good choice.