Generative AI has made significant strides, but it’s important to remember that we’re still in the early days of its development. A notable milestone was the launch of Chat GPT-3 on November 30, 2022. This event marked a significant step forward in AI capabilities, yet it also highlighted the challenges and limitations that remain.
One intriguing limitation of large language models (LLMs) and AI is their inability to count specific letters in words accurately, such as counting the ‘R’s in “strawberry.” This difficulty arises because LLMs don’t read words as individual letters but rather as tokens. Tokens are chunks of text that can be whole words or parts of words that the model processes. This token-based approach enables the AI to understand and generate text in a human-like manner, but it also leads to challenges in tasks that require precise letter-by-letter analysis.
On social media, it has been pointed out several times, that LLMs like Chat GPT cannot even count the number of the letter R in Strawberry. If you ask Chat GPT something like “how many Rs are there in strawberry?”, it simply replies 2, instead of the correct answer 3. This is because LLMs breaks languages down into tokens rather than letters. And from there, it can predict the next tokens. You can of course get the correct answer by giving some context to the task and guardrails.
One of the most compelling advantages of using AI in content creation is the incredible efficiency it offers. Achieving 95% quality in just 1% of the time traditionally required is a game-changer for businesses. This efficiency means teams can produce high-quality content rapidly, freeing up valuable time for strategic planning and creative endeavors.
The rapid pace at which AI can generate content translates to substantial time savings, allowing businesses to meet tight deadlines without compromising on quality. For instance, marketing campaigns that once took weeks to plan, draft, and revise can now be executed in a matter of days. This speed not only enhances productivity but also provides a competitive edge in fast-paced markets where timely communication is crucial.
Despite its many strengths, AI has a critical flaw: it can generate incorrect information with remarkable confidence. This phenomenon is known as a hallucination. AI can sometimes fabricate facts or present false information convincingly. This isn’t due to any malice or intent to deceive but rather a byproduct of how AI models learn and generate text. They predict and generate text based on patterns in the data they were trained on, which can sometimes lead to confidently presented inaccuracies.
To mitigate the risk of AI hallucinations, it’s essential to provide the AI with clear context, well-defined goals, and strict guardrails. Context helps the AI understand the topic and the nuances of the content it needs to generate. Clear goals ensure that the AI’s output aligns with the intended purpose, while guardrails act as constraints that limit the AI’s ability to deviate from accurate and relevant information. These measures help ensure that the AI produces reliable and factual content.
At Magnity, we prioritize the quality and consistency of our AI-generated content. By using your own content on your own website, we ensure a consistent tone of voice in all our email communications. Additionally, we have an extensive set of writing rules, compliance guidelines, and detailed persona descriptions. These elements work together to significantly improve the quality of the output, ensuring that the content not only meets but exceeds your expectations.
By leveraging these advanced AI techniques and maintaining stringent quality controls, Magnity helps you harness the power of AI while minimizing its pitfalls, ensuring your email campaigns are both efficient and effective.
