An Apache 2.0 designation makes Inkling a true open-source foundation. This gives developers the legal freedom to download, ...

Cognition launched SWE-1.7 on Wednesday, the most capable model it has trained, and with it made a specific claim about reinforcement learning that the broader AI research community will be evaluating ...

B, a 3-billion-parameter AI model, is challenging OpenAI, Google and DeepSeek on math and coding benchmarks while reigniting the debate over AI scaling, benchmark gaming and small-model reasoning.

Crowdsourced cybersecurity company Bugcrowd Inc. today launched Reinforcement Learning Environments, a new offering that lets frontier artificial intelligence labs train models on real vulnerable ...

SAN FRANCISCO, May 21, 2026 /PRNewswire/ -- Bugcrowd, the leader in preemptive cybersecurity, today announced the launch of Reinforcement Learning (RL) Environments, a new offering designed to help AI ...

Nvidia will partner with British startup Ineffable Intelligence to develop new AI systems, the companies announced in Wednesday. Unlike many leading AI models that are trained on human data, Ineffable ...

Study authors Hunter Schweiger (left) and Ash Robbins. Imagine balancing a ruler vertically in the palm of your hand: you have to constantly pay attention to the angle of the ruler and make many small ...

Negative reinforcement is a frequently misused term that diminishes its value as a powerful tool for behavior change. You may be puzzled by the claim that negative reinforcement is actually a good ...

Leaders, whether in boardrooms or garages, constantly face an unchanging force: uncertainty. For a CEO, making a good decision always involves factoring in as much data as possible, and then trusting ...

Most robot headlines follow a familiar script: a machine masters one narrow trick in a controlled lab, then comes the bold promise that everything is about to change. I usually tune those stories out.

AI agents are reshaping software development, from writing code to carrying out complex instructions. Yet LLM-based agents are prone to errors and often perform poorly on complicated, multi-step tasks ...