Generative AI use cases Text Summarization


AI Tech Circle

Hey Reader!

This week’s roundup is all about the latest happenings of AI:

  • Generative AI use cases Text Summarization
  • Weekly Latest news & updates
  • Courses, events, and Tech tools to try

Before I start the topic of today, thank you so much for your wonderful feedback for this newsletter, keep sharing it.

This week we are also witnessing the COP28 (The 2023 United Nations Climate Change Conference) happening in Dubai from Nov 30 to Dec 12, 2023. Let's all pledge and play a role in activities of environment-friendly and sustainable.

Large language models (LLMs) have revolutionized the way we interact with text-based data and summarizing a large piece of data is one of the top use cases, and organizations are trying to get their hands on it.

Here’s how summarization is changing the game:

Use Case: Text Summarization

  • What it is: Text summarization involves condensing a large body of text into a concise version, capturing the essence or key points. This can be particularly useful for digesting large volumes of information quickly.
  • How Gen AI Help: LLMs understand the context and semantics of the text, enabling them to identify and extract key information effectively. This capability is crucial for creating summaries that are not only concise but also meaningful and coherent.

Benefits and Examples:

Efficiency in Information Processing:

  • Example: A legal firm can use an LLM to quickly summarize case files and legal documents, saving hours of manual reading.

2. Enhanced Learning and Research:

  • Example: Students and researchers can use LLM-based tools to summarize academic papers and articles, making it easier to review literature and conduct research.

3. Business Intelligence:

  • Example: Companies can employ LLMs to summarize market research reports, customer feedback, and financial documents to support decision-making.

4. Media and News Digests:

  • Example: News agencies can use LLMs to provide concise news summaries, allowing readers to consume news efficiently.

5. Personalized Content Curation:

  • Example: Content curation platforms use LLMs to generate personalized summaries of articles and posts based on user interests.

6. Customer Service Enhancement:

  • Example: Customer service chatbots can use LLMs to summarize customer queries or complaints, enabling quicker and more effective responses.

In summary, Generative AI (LLMs) in text summarization is a game-changer, offering improved efficiency, better knowledge assimilation, and enhanced business intelligence. Their ability to process and condense information accurately and contextually makes them an invaluable tool across multiple domains.

Weekly News & Updates...

This week's new AI features and products are announced, fueling the technology revolution.

  1. Sam Altman is back to Open AI as CEO and the focus is on advancing the research and putting more investment into full-stack safety with the improvement of services and products for the consumers, and partners.
  2. Amazon has announced 'Amazon Q' the generative-based chatbot that can help you to do the tasks and it is tailored to your organization.
  3. Pika - a new AI model capable of generating and editing videos in different styles such as 3D animation, anime, cartoon, and cinematic. You can join the waitlist for Pika 1.0 at https://pika.art
  4. Pi ai - a new generative chatbot, you can experiment over here

The Cloud: the backbone of the AI revolution

Favorite Tip Of The Week:

here’s my favorite resource of the week.

It’s from 'Build Your Own RAG with Mistral-7B and LangChain', and this is a very detailed article to get you started on the Gen AI.

Hope this helps!

Potential of AI

  • How to Build a RAG-Powered Chatbot with Chat, Embed, and Rerank. An excellent article from Cohere
  • Three Ways Generative AI Can Bolster Cybersecurity, a report from Nvidia

Things to Know

The Opportunity...

Podcast:

Courses to attend:

Events:

Tech and Tools...

  • Several AI research models under the umbrella of Seamless Communication by Meta enable more natural and authentic communication across languages. Great stuff to add watermarking to the speech translations model. This brings AI safety and ethical AI into practice.
  • GPT-Fast: Simple and efficient pytorch-native transformer text generation
  • Graph Networks for Materials Science (GNoME) is a machine learning method to tackle the core task. With results recently published, this repository serves to share the discovery of 381,000 novel stable materials with the wider materials science community and hopefully enable exciting new research.

Other Technology News

Want to stay on the cutting edge?

Here’s what else is happening in Information Technology you should know about:

  • Dell bought AI Startup Imbue: According to Bloomberg, $150million deal to provide computing hardware to Ambue. This is a big deal for Dell to enter into the AI. Personally, I think this means there is a race for all the global vendors to tag with some AI startups or technology and more similar stories will appear.
  • 70% of Workloads Will Run in a Cloud Computing Environment: According to Gartner, reported by TechRepbulic. This is a way that we are all observing in the tech industry. Personally, I think this will somehow get into more shape of getting a dedicated cloud for the complex workloads, and in-country cloud data centers, due to factors of geo-politically situations among different countries.

That’s it!

As always, thanks for reading.

Hit reply and let me know what you found most helpful this week - I’d love to hear from you!

Until next week,

Kashif Manzoor


The opinions expressed here are solely my own conjecture based on experience, practice, and observation. They do not represent the thoughts, intentions, plans, or strategies of my current or previous employers or their clients/customers. The objective of this newsletter is to share and learn with the community.

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