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Hey AI Family, happy Friday! Let’s end the work week out strong, just like ChatGPT
Here’s The Breakdown:
💎 𝟛 Tools to Give You The Edge
🚨 𝟚 AI Updates: ChatGPT gets an upgrade & 🌎 largest AI computer
💻 𝟙 Practical Use of AI: Product market fit framework
Let’s jump in!
💎 𝟛 Tools to Give You The Edge
HoppyCopy: Write better email campaigns 10x faster with AI
TweetHunter: All in one AI powered growth tool for Twitter
AI Jobs Board: Find your dream AI job
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🚨 Breaking AI News
Yesterday, ChatGPT released a new beta feature called “Custom Instructions.” It allows users to provide unique preferences and requirements to improve the AI's responses.
ChatGPT will now be able to remember the important details about you without repeating yourself 1,000 times. If you are struggling with ideas of what to put for the instruction, Open AI has found these 6 use cases helpful:
"Expertise calibration: Sharing your level of expertise in a specific field to avoid unnecessary explanations.
Language learning: Seeking ongoing conversation practice with grammar correction.
Localization: Establishing an ongoing context as a lawyer governed by their specific country’s laws.
Novel writing: Using character sheets to help ChatGPT maintain a consistent understanding of story characters in ongoing interactions.
Response format: Instructing ChatGPT to consistently output code updates in a unified format.
Writing style personalization: Applying the same voice and style as provided emails to all future email writing requests." (Use cases are in Open AI's words.)
This is available exclusively for Plus subscribers and you can turn it on by going to settings and go to beta features and toggle it on.
The world's largest AI supercomputer was unveiled today. It’s game changing for the AI industry by being accessible via the cloud so anyone can use its power, not just large corporations.
Developed by Cerebras and G42, it allows single users to set up generative AI model training in minutes, operating up to 20x faster than previous systems.
This new system allows average users harness the strength of interconnected super machines. Their ultimate goal is to have 9 supercomputers talking to each other which is 36 exaFLOPs of computing power. Or 36 quintillion floating-point operations per second.
“To match what a 1 ExaFLOPS computer system can do in just one second, you'd have to perform one calculation every second for 31,688,765,000 years.” Incredible advancement. Learn more here.
🔎Extra Insights🔍
💻 Real Life Use Cases
Chat GPT Prompt: Product market fit framework
Product market fit is extremely important for any business, so it’s imperative to get it right.
Use this ChatGPT prompt to help you find a market fit for your new product.
🔏 Copy and paste the prompt below ⏬
Using the 'Product-Market Fit' framework, please write a marketing campaign outline that demonstrates how our [product/service] is a perfect fit for the needs and pain points of [ideal customer persona]. Identify the specific problems faced by the target market, explain how our product addresses these issues, and provide evidence or testimonials to back up our claims. Emphasize the benefits of using our product and how it can improve the reader's life or business."Here’s a link to the results ⬇️
Daily Definition
Corpus
A 'Corpus' (plural: 'Corpora') in the context of AI and, more specifically, Natural Language Processing (NLP), refers to a large and structured set of texts. It could be composed of anything from a collection of tweets, a library of books, transcripts of parliamentary debates, to archives of newspaper articles.
Why are corpora important in AI? They provide the raw material that AI algorithms learn from. By analyzing a corpus, an AI model can learn about the structure of language, the frequency of different words or phrases, the context in which words are typically used, and even more complex linguistic and semantic relationships.
Example: Suppose an AI model is designed to understand and generate text in English. It could be trained on a corpus comprising various English textbooks, newspapers, websites, etc. The model would learn how sentences are constructed, what words tend to follow others, and all the nuances of the English language. So, when asked to generate a sentence or respond to a prompt, it can produce text that sounds human.
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