When Subquadratic launched earlier this year, it could build a sparse-attention model that could handle a 12-million-token context window and be significantly faster than today’s large language models. But it didn’t launch the model widely, nor did it publish benchmarks.
The company’s large claims created considerable skepticism, writes Frederic Lardinois, Senior Editor for AI, in today’s lead story. But last month, Subquadratic published its first model card and benchmarks for its small model, SubQ 1.1, provided third-party verification from data firm Appen, and began talking about its first design partners, who now have access to its model.
So far, however, few people have actually used its model. To talk about the company, why its model isn’t widely available yet, and what it has in store for the near future, we met up with Subquadratic co-founder and CTO Alex Whedon.
Read the full interview: What comes after attention? This startup says it already knows.
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