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- AI Brew: Your Weekly Dose of AI Caffeine! โ๐
AI Brew: Your Weekly Dose of AI Caffeine! โ๐
Your weekly AI Caffeine shot, tailored to fuel captivating AI discussions with your clients, boss, colleagues, friends, and family (and discreetly show off your expertise) โ๏ธ๐ง
๐ This week's AI Brew summary:
AI Spotlight on ๐: ChatGPT-4 Plugins
Real-Life AI Stories ๐ค
AI Jargon Buster ๐คทโโ๏ธ
Cool Corner ๐: Coca-Cola
Poll of the Week ๐ณ๏ธ: Are you using ChatGPT at work?
AI Spotlight ๐: ChatGPT-4 Plugins
ChatGPT-4 is an incredible language model, but it does have its limits. It can only use the information it learned during training, which means it can miss out on real-time, personalized, and specific data. That's where ChatGPT-4 Plugins come in!
These plugins will expand ChatGPT-4's abilities to access fresh, up-to-date information beyond its training data. Don't believe us? Check out this tweet from Sam Altman! ๐ฒ
we are starting our rollout of ChatGPT plugins.
you can install plugins to help with a wide variety of tasks. we are excited to see what developers create!
openai.com/blog/chatgpt-pโฆ
โ Sam Altman (@sama)
5:12 PM โข Mar 23, 2023
Real-Life AI Stories ๐ค
๐ฉโโ๏ธ AI Detects Breast Cancer 4 Years in Advance - Revolutionary Advancement in Early Diagnosis!
๐ Levi's and Lalaland.ai Team Up to Boost Diversity and Sustainability Using AI Models ๐ฑ
AI Jargon Buster - Large Language Models
LLMs, or Large Language Models, are advanced AI systems that can understand and generate human-like language by breaking down language into smaller units and analyzing their relationships. Chat GPT is an example of an LLM that can generate text in response to a given prompt.
When you ask Chat GPT , "What's the weather like today?," this is how it generates a human like response:
Tokenization: it takes your question, "What's the weather like today?" and breaks it down into smaller units of meaning called tokens, like "weather," "today," and "like."
Encoding: It uses word embeddings to convert each token into a numerical representation that can be processed by the model.
Processing: It, then, uses its deep learning architecture to process the encoded tokens and generate a response. It analyzes the relationships between the tokens and predicts the most likely next word or sequence of words based on its training data.
Decoding: It converts the numerical representation of the generated response back into human-readable text.
Response Generation: Finally, it puts together the tokens in a way that sounds natural and coherent, and produces a response that sounds like something a person might say. In the case of the weather question, it might say "It looks like it's going to be sunny and warm today, with a high of 80 degrees."
I found this video really helpful to understand how ChatGPT works:
Cool Corner ๐
This weekโs award goes to โยป Coca-Cola's new AI platform, "Create Real Magic." The platform is only available until March 31, so don't miss your chance to create something truly magical.
Poll of the Week ๐ณ๏ธ
๐ง Got a question or an AI topic you'd like us to cover? Email me at [email protected]
Hope you liked your cup of AI Brew - Share AI Brew with friends and family who might enjoy a weekly dose of AI caffeine! ๐ฅณ



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