Creating self-improving AI systems is an important step toward deploying agents in dynamic environments, especially in enterprise production environments, where tasks are not always predictable, nor consistent. Current self-improving AI systems face severe limitations because they rely on fixed, handcrafted improvement mechanisms that only work under strict conditions such as software engineering.To overcome this practical challenge, researchers at Meta and several universities introduced “hyperagents,” a self-improving AI system that continuously rewrites and optimizes its problem-solving logic and the underlying code. In practice, this allows the AI to self-improve across non-coding domains, such as robotics and document review. The agent independently invents general-purpose capabi [...]
Some of the most successful creators on Facebook aren't names you'd ever recognize. In fact, many of their pages don't have a face or recognizable persona attached. Instead, they run pa [...]
Market researchers have embraced artificial intelligence at a staggering pace, with 98% of professionals now incorporating AI tools into their work and 72% using them daily or more frequently, accordi [...]
Our LLM API bill was growing 30% month-over-month. Traffic was increasing, but not that fast. When I analyzed our query logs, I found the real problem: Users ask the same questions in different ways.& [...]
OpenAI on Monday released a new desktop application for its Codex artificial intelligence coding system, a tool the company says transforms software development from a collaborative exercise with a si [...]
Researchers at the Massachusetts Institute of Technology (MIT) are gaining renewed attention for developing and open sourcing a technique that allows large language models (LLMs) — like those underp [...]