Minimax M2.5 lists $0.30 per million input tokens and $2.40 output on the lightning tier, helping builders plan predictable AI spend.

Discover the step-by-step creation of a stunning miniature landscape, combining detailed diorama techniques and realistic ...

Explore the art of miniature diorama creation in this in-depth tutorial. From digital concept art to sculpting detailed Pyroraptor and Baryonyx figures in polymer clay, learn expert modeling ...

Abstract: Extremely large-scale multiple-input-multiple-output (XL-MIMO), which offers vast spatial degrees of freedom, has emerged as a potentially pivotal enabling technology for the sixth ...

Model making is a great hobby, but knowing how and where to start is another story. It can be overwhelming for novices: Injection-molded plastic models have been on the market for close to a century, ...

Reno may be “the biggest little city in the world,” but it's got some serious competition from the miniature New York City that hobbyist Joseph Macken built in his upstate New York basement over two ...

Meta’s $14.3 billion investment in Scale AI represents the social media giant’s most significant move to secure high-quality training data for artificial intelligence models. The deal gives Meta a 49% ...

Meta’s deal to partially acquire the AI startup Scale, giving it 49% ownership, is certainly unusual. What Scale officially announced is that the deal values the company at over $29 billion and that ...

Meta is investing $14.3 billion into Scale AI, landing the startup's CEO Alexandr Wang to help the company's artificial intelligence efforts. In a memo to employees that he posted on X on Thursday, ...

Deal values Scale AI at $29 billion, sources say Meta spending $14.3 billion Scale AI CEO Wang to run Meta's superintelligence efforts Deal may affect Scale's relationships with Meta's competitors ...

We propose Scale-Aware KV Cache (ScaleKV), a novel KV Cache compression framework tailored for VAR’s next-scale prediction paradigm. ScaleKV leverages on two critical observations: varying cache ...