Netflix pitted its years-old recommendation engine against an in-house language model called GenRec and says it got better results. Instead of relying on thousands of hand-crafted features, GenRec converts viewing behavior into plain text. Netflix itself calls it "an early but promising step."<br /> The article Netflix tests language model as alternative to hand-built recommendation logic appeared first on The Decoder. [...]
Netflix's $82.7 billion acquisition of Warner Bros. is, in many ways, the last thing a weakened Hollywood needs right now. The industry is still recovering from the COVID-19 pandemic, where theat [...]
AI coding agents are rapidly accelerating data engineering by generating transformations, pipelines, orchestration workflows, validation tests, and infrastructure configurations from prompts. However, [...]
Training a foundation LLM from scratch costs millions and requires internet-scale data — which is why most enterprises don't bother. Sapient thinks it has a cheaper path.To overcome this brute- [...]
Netflix is giving its TV user interface a major overhaul. Alongside a fresh, cleaner look, you'll see recommendations that adapt to your activity as Netflix tries to better gauge what you might b [...]
The Dfinity Foundation on Wednesday released Caffeine, an artificial intelligence platform that allows users to build and deploy web applications through natural language conversation alone, bypassing [...]
Christmas Day famously belongs to football. This Dec. 25, there are three NFL games to watch: the Dallas Cowboys vs. Washington Commanders, the Detroit Lions vs. the Minnesota Vikings, and the Denver [...]
Christmas Day famously belongs to football. This Dec. 25, there are three NFL games to watch: the Dallas Cowboys vs. Washington Commanders, the Detroit Lions vs. the Minnesota Vikings and the Denver B [...]
Microsoft on Tuesday released Phi-4-reasoning-vision-15B, a compact open-weight multimodal AI model that the company says matches or exceeds the performance of systems many times its size — while co [...]