OpenAI introduced Deployment Simulation on June 16, 2026. The method replays past conversations through a new candidate model before release. It then grades the completions to estimate deployment-time rates of undesired behavior. We break down how the pipeline works, the reported 1.5x median multiplicative error, and its limits.
The post OpenAI’s Deployment Simulation Extends Pre-Deployment Risk Assessment to Agentic Coding Through Simulated Tool Calls appeared first on MarkTechPost.
The talent shift highlights a strategic pivot in AI firms towards direct enterprise engagement, reshaping future industry revenue dynamics.
The post OpenAI and Anthropic have poached roughly 100 Salesforce employees in 18 months appeared first on Crypto Briefing.
Anthropic ended May by overtaking OpenAI in business market share for the first time, according to data from Ramp, with AI subscriptions rising to 41% against OpenAI’s 39.5%. The milestone coincided with a $65 billion raise at a near-trillion-dollar valuation and the confidential filing of IPO paperwork off the back of its first profitable quarter. […]
The G7 summit highlights the growing geopolitical tensions over AI access, prompting nations to consider developing independent AI capabilities.
The post OpenAI, Anthropic CEOs break bread with G7 leaders as US AI export controls rattle allies appeared first on Crypto Briefing.
Z.ai has released GLM-5.2, an MIT-licensed open-source AI model designed for long-running software engineering tasks, as the Chinese company seeks to challenge proprietary coding models on cost and performance.
The company said GLM-5.2 ranked just behind Anthropic’s Claude Opus 4.8 on FrontierSWE, a long-horizon coding benchmark, trailing it by 1%. Z.ai said the model also edged out OpenAI’s GPT-5.5 by 1%.
Z.ai said GLM-5.2 supports a one-million-token context window with up to 131,072 output tokens, positioning it for agentic coding workflows that require reasoning across large codebases.
The company is also making an efficiency argument. It said GLM-5.2 uses a technique called IndexShare, which reduces per-token compute by 2.9 times at a one-million-token context length. It also said changes to the model’s multi-token prediction layer increased the acceptance length for speculative decoding by up to 20%.
The changes are aimed at a practical problem for developers: long-context coding
Z.ai has released GLM-5.2, an MIT-licensed open-source AI model designed for long-running software engineering tasks, as the Chinese company seeks to challenge proprietary coding models on cost and performance.
The company said GLM-5.2 ranked just behind Anthropic’s Claude Opus 4.8 on FrontierSWE, a long-horizon coding benchmark, trailing it by 1%. Z.ai said the model also edged out OpenAI’s GPT-5.5 by 1%.
Z.ai said GLM-5.2 supports a one million-token context window with up to 131,072 output tokens, positioning it for agentic coding workflows that require reasoning across large codebases.
The company is also making an efficiency argument. It said GLM-5.2 uses a technique called IndexShare, which reduces per-token compute by 2.9 times at a one million-token context length. It also said changes to the model’s multi-token prediction layer increased the acceptance length for speculative decoding by up to 20%.
The changes are aimed at a practical problem for developers: long-context coding
Having the right certificate can make all the difference. But with so many out there, getting the right one isn’t easy. That’s where OpenAI Academy comes in. OpenAI, the company behind the ChatGPT models, has introduced a learning platform through its OpenAI academy that offers AI courses for upskilling professionals. These courses cover topics like […]
The post OpenAI Just Launched 3 Free AI Courses with Certificates appeared first on Analytics Vidhya.