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Mar 28, 2022 6 min read

Speed Write Posts for Linkedin Using Genei AI Writing Tool

Wiser! Essay: An easy way to produce Linkedin Posts using Genei's AI writing tool. Plus GPT3 explained.


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Speed Write with the Genei AI Writing Tool


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How to Use the Genei AI Writing Tool for Linkedin Posts

ReadThis:  You've read a great article online and want to share it to your network on Linkedin. You don't want to spend half an hour writing a post, nor do you want to just share the link with a "read this" at the top.

What do you do?

Use Genei to auto write a summary for you.

Genei uses AI to read the page and then write a short summary. The AI picks out salient points and crafts a short, to the point summary that is perfect for a Linkedin post. It also means that you avoid getting ignored by the Linkedin algorithms, which happens when you (just) use the Share buttons included on every page.

I use the Genei extension in the Brave browser. It's a simple process.

1️⃣ Install the Genei extension into your browser
2️⃣ Click the extension button on every page you want to summarise
3️⃣ Login using your account or Google sign-in (if you're not already logged in)
4️⃣ Cut and paste the text into a New Post on Linkedin (edit the text if you want to tweak it)
5️⃣ Write your CTA, add hashtags or copy in any @mentions, then hit Post
6️⃣ Final step is to add the link to the source article in the 1st comment. I use Bitly to create a short link. This means that I can see every time one clicks on the link in my post (you can't get that from Linkedin)


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What is GPT3?

GPT-3 is a machine learning model, which means it can learn and improve on tasks without explicitly programming it to do so. However, it also engages in deep learning utilising artificial neural networks, allowing it to educate itself using brain-like algorithm structures.

GPT-3 is now one of the largest neural networks and language prediction models, with 175 billion parameters. These parameters indicate that GPT-3 can take an input and estimate what will be the most valuable output or production.

Because it was pre-trained, GPT-3 was able to forecast the best and most valuable findings. The model was trained by OpenAI utilising a significant amount of text-based internet data.

This enables the model to detect trends and generate accurate predictions as it continues to learn which ways of generation work and which do not. GPT-3, on the other hand, isn't confined to generating human language text; it can generate anything with a language structure, including programming code.

Because GPT-3 can interpret literature and write like a person, the possibilities for its application are nearly limitless. The most obvious advantage is that it can generate vast amounts of text, making text-based content development simpler and more efficient for us.

It can be used to translate languages, produce essays, summarise text, and answer queries, among other things. Over 300 apps are now using OpenAI's GPT-3 API, demonstrating the AI's power and capacity.

GPT-3 is used to rewrite, summarise, and enlarge text, making the note-taking process more efficient while researching a topic or subject area. GPT-3 has been utilised in several applications to create content generation tools ranging from authoring marketing copy, job descriptions, code, and stories to generating blog post ideas and review responses.

Others have used GPT-3 to improve semantic searches, allowing them to go beyond keywords and instead extract meaning from the user's input and return appropriate results.

GPT-3 demonstrates the power of AI

This system provides a very early insight into the future potential and the utility of such AI. GPT-3 contains defects and limits, which is why it is regarded as an early glimpse into the future.

However, it is a step advance in natural language processing (NLP), the field of AI that focuses on machines understanding, responding to, or producing human-like language.

GPT-3 addresses a critical component of NLP known as natural language generation, which is the capacity to convert information into human-like language. Of course, this is not the first model to do so, but it is the most effective at the present.


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Currently 112,848 people follow me across Social Media for Insights and Information from the Tech Economy (whoop-di-do!😊). You get to see most of it here because you're subscribers to the Newsletter. I'm most active on Twitter and Linkedin, however here are some other places you can find me:

Hacker Noon: A great place to find tons of content from independent writers like me.
Medium: Still the number 1 place for bloggers and writers (IMHO).
Reddit: Building a community on the Wiser! sub-reddit.
YouTube: Over 37,000 views last time I looked
Instagram: the place to make writing visual.



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