AI Business

Physical AI is pushing artificial intelligence into robots, factories and other real-world environments, where understanding language is only part of the challenge.

The generative AI vendor released the app with stringent security guardrails for using it in professional and small business settings.

OpenAI now has its models on all three major cloud provider platforms, as it refines its enterprise strategy.

The governance approach focuses on key principles of transparency, explainability, risk management, privacy and security.

With the move, the Chinese AI vendor is looking to gain an advantage in the open source market, while addressing enterprise concerns about steep token rates.

Inside the workplace collaboration and project management platform vendor’s AI strategy.

While the vendor is not the first in the AI for legal market, the Microsoft environment is entrenched in many law firms.

Robotics talent, customers and investment are concentrating in Boston, and what that means for the U.S. physical AI industry.

Neura’s latest foundation model combines vision, touch and audio to improve robotic perception, but training it on enough real-world data could prove difficult.

The new Nemotron 3.5 models show how the AI giant is focusing on reinforcing its own GPU infrastructure while supporting the open source community.

Companies are giving agents more authority, but many are still struggling to track what they can access, what they're doing and how to stop them.

Coordinating robots and autonomous systems will be critical to unlocking physical AI, but it’s still unclear whether interoperability is an immediate barrier to adoption.

As AI agents move from answering questions to making decisions and acting, businesses face a growing challenge of keeping accountability in step with the pace of change.

The social media giant tries to capitalize on, monetize its successful personal agent and maybe crack the business market. Chinese models go astray, like their U.S. counterparts.

A new case of an out-of-control AI model shows that enterprises should treat models and agents as toddlers that need supervision and explicit instructions.

The company’s new releases point to an AI market becoming more personal, with agents and models completing tasks, but enterprises still aren’t ready for this new phase of AI.

Rising production volumes are increasing pressure on suppliers, while U.S.-China tensions could make it harder for Western manufacturers to secure alternatives to Chinese suppliers.

As agents take on more work for users, companies are deciding whether to let outside AI systems act on their platforms.

The agent can use enterprise business context for knowledge work. However, questions about cost and integration with other tools could be difficult for enterprises.

New Western open-weight models could give enterprises an alternative to Chinese and proprietary AI, but greater control also brings new responsibilities.