After hearing countless people make these unfortunate errors when talking about AI, I thought I would write this in the hope of helping future generations avoid spreading more misinformation. Here are five common misconceptions about generative AI.

Myth #1: Microsoft Owns OpenAI

First up on our list of misconceptions is the idea that Microsoft has OpenAI in its back pocket. This one pops up more often than the sun itself.

• While it's true that Microsoft and OpenAI have been cosying up in a partnership that's as significant as finding a compatible USB port on the first try, Microsoft doesn't "own" OpenAI.🤝
• Think of their relationship more like Batman and Robin; they complement each other's strengths and share adventures, and occasionally, Microsoft lends OpenAI its magnifying glass (in the form of Azure's computational prowess) to advance their research.
• If you have been following the news, you would know that Microsoft is investing in other AI companies besides Open AI.💰

Myth #2: AI Can Think

Hold on there, science fiction fans. While AI tools can process information and even generate creative text formats, they are not sentient beings with their inner monologues (at least for now!).

• It is more like highly advanced calculators, albeit ones that can write a convincing Shakespearean sonnet.
• Remember back in school when you were developing a least squares fit curve, in very simplified terms that is what AI is doing to try and predict the best outcome to impress you!
• However, it is important to appreciate that there is a possibility that this is very similar to how our brains function - but so far nothing has been proven yet.🧐🧬

Myth #3: AI Hallucination is Bad

Now, this one gets interesting. AI "hallucination" refers to when they generate outputs that are “factually incorrect” or “nonsensical”.

• While it's important to be aware of this limitation and use outputs responsibly, it doesn't necessarily mean it's "bad." In fact, they are often what makes AI so fascinating.
• In fact, in some use cases, this is a “feature” and not necessarily a “bug”. Think of tasks that require rareness and imagination such as generating paintings, poems, songs etc. You would agree that these tasks would benefit from more "hallucinations" right??🎵📝🖼
• Okay, I will admit that I never gave this a thought until I heard Sam Altman hint at it in a recent interview with Trevor Noah - Great observation, Sam!
• Just remember, treat AI outputs like a creative writing exercise – double-check your facts before hitting publish.✅📝

Myth #4: AI is ML

Saying AI is ML is like saying a car is an engine(metaphorically true, but not technically accurate)

• Machine Learning (ML) is a subset of Artificial Intelligence (AI) which is a subset of Data Science.🧮➡️🤖
• Think of the relationship between AI and ML as the relationship between a computer and a calculator. AI is the computer, while ML is the calculator.
• However, it should be noted that modern Generative AI tools like ChatGPT make use of Deep Learning, which is an advanced version of ML that relies on Neural Networks.

For those who do not know, Artificial Intelligence(AI) is a broad term used to describe the ability of machines to perform human-like tasks which is considered to make them “intelligent” e.g. generating speech, recognising images, writing poetry etc.

Myth #5: AI Was Invented in November 2022

While the recent popularity of tools like ChatGPT might make it seem like AI is a brand-new invention, the truth is, that it has been bubbling away in research labs for decades.

• It is reported that the idea of AI has been around going back to the mid-20th century. The term “Artificial Intelligence” was first coined by John McCarthy in the 1950s at the Dartmouth conference where the core mission of the AI field was defined. This mission was “to proceed based on the conjecture that every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it.”
• The journey of AI from then to now has been a rollercoaster ride with periods of intense interest and funding (AI summers) followed by periods of disappointment and lack of funding (AI winters). ☀️ ❄️ Despite these ups and downs, AI has made steady progress over the years.🎢
• From the rule-based systems of the 1970s to the machine learning algorithms of the 1980s and 1990s to the deep learning algorithms that are popular today, AI has come a long way. It has permeated every aspect of our lives, from the way we communicate to the way we work, play, and express our creativity.
• So, while it may seem like AI is a product of the 21st century, its roots go much deeper. It is a testament to the vision of the early pioneers and the relentless pursuit of knowledge by countless researchers and engineers around the world.
• The recent popularity of tools like ChatGPT is a testament to the continuous evolution and application of AI, not its inception.🔄

Stay tuned for Part 2 of this myth-busting adventure, where we'll tackle more misconceptions and explore the exciting future of generative AI!