Artificial Intelligence | News, analysis, features, how-tos, and videos
A significant chasm exists between most organizations’ current data infrastructure capabilities and those necessary to effectively support AI workloads.
Global politics, chip wars, and the ever-present confusion of managing AI source code. It’s been a tough week for open source.
New capabilities for building safe models include watermarking, prompt refining, and prompt debugging and work with any large language models.
The difference in pricing suggests cost savings for enterprises, at least for usage of open models.
Anthropic’s has upgraded its Claude 3.5 Sonnet LLM with a new ability, computer use, opening up new opportunities for developers in robotic process automation (RPA) and more.
Do you need to distribute a heavy Python workload across multiple CPUs or a compute cluster? These seven frameworks are up to the task.
The API service, currently in public beta, is more expensive than OpenAI’s API service and supports integrations with both OpenAI and Anthropic SDKs.
Python developers are uniquely positioned to succeed in the AI era, with a little help from upskilling.
The watsonx Code Assistant uses the newly announced Granite 3.0 models to provide general-purpose coding assistance across multiple programming languages.
AI copilots are great, but what else is out there? Here are 11 open source AI projects that make writing beautiful software easier.