Generative AI Insights
By Josh Fruhlinger, Janakiram MSV, Sharon Machlis, Isaac Sacolick, Matthew Tyson
Generative AI Insights, an InfoWorld blog open to outside contributors, provides a venue for technology leaders to explore and discuss the challenges and opportunities presented by generative artificial intelligence. The selection is wide-ranging, from technology deep dives to case studies to expert opinion, but also subjective, based on our judgment of which topics and treatments will best serve InfoWorld’s technically sophisticated audience. InfoWorld does not accept marketing collateral for publication and reserves the right to edit all contributed content.
Applying the lessons of open source to generative AI
The excitement and turmoil surrounding generative AI is not unlike the early days of open source, or the Wild West. We can resolve the uncertainty and confusion.
How to take action against AI bias
Humans must be the custodians for preserving high-quality data as AI use continues to advance.
What is generative AI? Artificial intelligence that creates
Generative AI models can carry on conversations, answer questions, write stories, produce source code, and create images and videos of almost any description. Here's how generative AI works, how it's being used, and why it’s more...
Ease into similarity search with Google’s PaLM API
Learn how to use Google Cloud Vertex AI and the PaLM 2 large language model to create text embeddings and search text ranked by semantic similarity.
How AI will impact the developer experience
Generative AI is not the first new technology that has changed how software developers work. While developers have nothing to fear, the stakes will be high for their employers.
Build a chatbot with Google’s PaLM API
Using the PaLM 2 large language model available in Google Cloud Vertex AI, you can create a chatbot in just a few lines of code. These are the steps.
How to use GPT as a natural language to SQL query engine
A few strategic decisions can help improve your generative AI code and queries, and prevent sending out sensitive data.
3 open source NLP tools for data extraction
Unstructured text and data are like gold for business applications and the company bottom line, but where to start? Here are three tools worth a look.
How to use GPT-4 with streaming data for real-time generative AI
For businesses and their customers, the answers to most questions rely on data that is locked away in enterprise systems. Here’s how to deliver that data to GPT model prompts in real time.
Reactive JavaScript with Stable Diffusion
Use React and the Stable Diffusion API to build a reactive application that generates images from user-submitted text.
Getting started with Google’s PaLM API
The PaLM API allows you to tap Google’s PaLM 2 large language model directly from your application. Let’s start by writing some code to generate a blog post, including the HTML code.
AI is my copilot: The promise of AI code generation
Software engineers using AI will be astonishingly more capable than either engineers or AI working alone. If we do this right.
8 ChatGPT tools for R programming
The generative power of OpenAI's GPT 3.5 LLM is now available to R users, with a growing collection of ChatGPT packages and apps to choose from.
ChatGPT’s parasitic machine
What do ChatGPT and other large language models owe to the human creators who provide the information they train on? What if creators stop making their insights publicly available?
Build a Java application to talk to ChatGPT
Build your own Java-based chatbot and get a feel for interacting with the ChatGPT API in a Java client.
LLMs and the rise of the AI code generators
Large language models like GPT-4 and tools like GitHub Copilot can make good programmers more efficient and bad programmers more dangerous. Are you ready to dive in?
Are large language models wrong for coding?
When the goal is accuracy, consistency, mastering a game, or finding the one right answer, reinforcement learning models beat generative AI.
AI coding assistants: 8 features enterprises should seek
Some AI coding assistants are toylike, while others are enterprise-class. Here’s how to tell the difference.
Large language models are the new cloud battleground
Perhaps the biggest thing since open source or Google, LLMs may have companies fighting for supremacy, but it’s the developers who come out ahead.
The AI singularity is here
The time to figure out how to use generative AI and large language models in your code is now.
