Artificial Analysis has launched Optima, a platform that lets users build custom AI benchmarks from their own data and workflows. Models can be compared not just on quality but also on cost and time per task. For agent-based applications, those metrics often tell you more than raw token pricing.<br /> The article Optima tackles AI benchmarking's biggest flaw by letting users test models against their own data appeared first on The Decoder. [...]
Picture this scenario: An Anthropic Skill scanner runs a full analysis of a Skill pulled from ClawHub or skills.sh. Its markdown instructions are clean, and no prompt injection is detected. No shell c [...]
I came into this review thinking of Private Internet Access (PIA) as one of the better VPNs. It's in the Kape Technologies portfolio, along with the top-tier ExpressVPN and the generally reliable [...]
The arms race to build smarter AI models has a measurement problem: the tests used to rank them are becoming obsolete almost as quickly as the models improve. On Monday, Artificial Analysis, an indepe [...]
The standard guidelines for building large language models (LLMs) optimize only for training costs and ignore inference costs. This poses a challenge for real-world applications that use inference-tim [...]