Large language models evolved alongside deep-learning neural networks and are critical to generative AI. Here's a first look, including the top LLMs and what they're used for today.
Stories by Martin Heller
InfoWorld’s 2023 Bossie Awards recognise the year’s leading open source tools for software development, data management, analytics, AI, and machine learning.
Use LangSmith to debug, test, evaluate, and monitor chains and intelligent agents in LangChain and other LLM applications.
Llama 2 is a family of generative text models that are optimised for assistant-like chat use cases or can be adapted for a variety of natural language generation tasks. Code Llama models are fine-tuned for programming tasks.
Many low-code and no-code development and RPA platforms now include AI capabilities, often using a version of GPT.
Microsoft's AI Builder introduces low-code generative AI capabilities to Power Apps and Power Automate.
Machine learning uses algorithms to turn a data set into a model that can identify patterns or make predictions from new data. Which algorithm works best depends on the problem.
Large language models have captured the news cycle, but there are many other kinds of machine learning and deep learning with many different use cases.
Ballerina was designed to simplify the development of distributed microservices by making it easier to integrate APIs. For C, C++, C#, and Java programmers, much will feel familiar.
Come for the fast editing. Stay for the debugging, source code management support, and huge ecosystem of extensions.
Human-in-the-loop machine learning takes advantage of human feedback to eliminate errors in training data and improve the accuracy of models.
The public cloud is teeming with the latest and greatest development, devops, and AI tools for building better and smarter applications faster.
Copilot technical preview doesn’t always generate good, correct, or even running code, but it’s still somewhat useful. Future versions could be real time-savers.
Enterprise data warehouses are comprehensive structured data stores designed for analysis. They often serve as the data sources for BI systems and machine learning.