A comprehensive overview of generative AI and LLMs' trends, use cases, and future implications I. - Business, technology trends and applications

7 weeks (from 4.9. to 22.10.2023) in the world of Large Language Models and Generative AI tools:

AI in Business and Technology Trends:

How OpenAI turned LLMs into a mainstream success.

Oracle outlines a vision for AI and a cloud-driven future.

Enterprise SaaS companies have announced generative AI features, threatening AI startups.

How Generative AI is disrupting data practices.

Data Provenance in the age of Generative AI.

Is ChatGPT going to take data science jobs?

40% of the labour force will be affected by AI in 3 years.

And Gartner says: 

55% of organizations are in piloting or production mode with Generative AI.

CIOs must prioritize their AI ambition and AI-ready scenarios for next 12-24 months.

More than 80% of enterprises will have used Generative AI APIs or deployed Generative AI-enabled applications by 2026.

60% of seller work to be executed by Generative AI technologies within five years.

AI Applications and Use Cases:

Large Language Models in real-world customer experience applications.

Five generative AI use cases companies can implement today.

Five use cases for CFOs using generative AI.

Revolutionizing business automation with generative AI.

Redefining conversational AI with Large Language Models.

Pros and cons of LLMs for bad content moderation.

Generative AI on research papers using the Nougat model.

Document topic extraction with Large Language Models and the Latent Dirichlet Allocation (LDA) algorithm.

Using AI to add vector search to Cassandra in six weeks.

Large Language Models and other AI tools in software development (from 4.9. to 22.10.2023)

7 weeks (from 4.9. to 22.10.2023) in the world of Large Language Models and other AI tools used for software development:

List of five free AI Tools for programmers (Amazon CodeWhisperer, ChatGPT, CodeGeeX, GitHub Copilot, Bugasura).

A more detailed comparison of AI tools for programmers - the same as above, except Bugasura - another tool - Replit - is mentioned.

And here are 5 ChatGPT alternatives for code generation (Tabnine, Kite, Codota, DeepCode, GitHub Copilot).

Comparing ChatGPT with Bard AI - for software development.

GitHub Copilot Chat in open beta - now available for all individuals in Visual Studio and VS Code.

Couchbase has introduced generative AI capabilities for SQL into Database as a Service (Couchbase Capella)

MetaGPT - ChatGPT-powered AI assistant turning text into ChatGPT-based apps.

AI Assistant for IntelliJ-based IDEs update for October 2023.

Meta open-sources code generation LLM code Llama.

A new customization capability in Amazon CodeWhisperer generates even better suggestions (Preview).

Chatting with the GM of CodeWhisperer.

How is GenAI different from other code generators?

Is AI enough to increase your productivity?

The future of AI in software development - trends and innovations.

Reimagining application development with AI - a new paradigm.

The pitfalls of using general AI in software development - a case for a human-centric approach.

The challenges of producing quality code when using AI-based generalistic models.

Applying Large Language Models (LLM) to software requirements - creating a knowledge hub of business logic and copilot for faster development.

Chat with the Oracle DB - leveraging OpenAI models to query the Oracle DB, building a Text-to-SQL tool and testing it on a public dataset.

Leveraging GPT models to transform natural language to SQL queries by training GPT to query with few-shot prompting.

Retro-engineering a database schema with LLama2 - the idea here is to ask each LLM to analyze sample data and provide some insight into what the initial data scheme might look like.

‘Talk’ to Your SQL Database Using LangChain and Azure OpenAI.

AI-Driven microservice automation - use ChatGPT to build a MySQL database model, and add API Logic Server to automate the creation of SQLAlchemy model, react-admin UI, and OpenAPI (Swagger).