Open-source generative AI appears to be developing rapidly, especially over the past week with several tech giants unveiling powerful AI models one after the other. French AI startup Mistral just unveiled the Mixtral 8x22B and Meta announced Llama 3 only […]
Source: aibeat.co
Anthropic’s most capable AI model has already found thousands of AI cybersecurity vulnerabilities across every major operating system and web browser. The company’s response was not to release it, but to quietly hand it to the organisations responsible for keeping the internet running. That model is Claude Mythos Preview, and the initiative is called Project…
The open-source AI movement has never lacked for options. Mistral, Falcon, and a growing field of open-weight models have been available to developers for years. But when Meta threw its weight behind Llama, something shifted. A company with three billion users, vast compute resources, and the credibility of a tech giant was now building openly,…
A billion dollars in startup funding for a company that employs 12 people is an indication that investors still have faith in AI. But the founder of the startup in question – AMI Labs’ Yann LeCun – believes that the breed of technology we currently term AI (large language models) is not the way through…
Many companies are taking a slower, more controlled approach to autonomous systems as AI adoption grows. Rather than deploying systems that act on their own, they are focusing on tools that assist human decision-making while keeping tight control over outputs. This approach is especially clear in sectors where errors carry real financial or legal risk….
RingCentral has expanded its AI Receptionist product with new links to Shopify, Calendly and WhatsApp, as the communications software company tries to push the product beyond basic call answering and into more routine customer service tasks. The company said AI Receptionist, known as AIR, can now handle some order enquiries through Shopify, arrange appointments through…
Cloud migration becomes much harder when teams are not moving workloads, but also trying to make every environment reproducible and deployment-ready through Infrastructure as Code. The challenge is not limited to copying applications from one platform to another. It includes validating architecture decisions, controlling drift, enforcing policies, coordinating approvals, and making sure deployment logic can…