Nvidia in Talks to Back Data Startup Mercor at $20 Billion
Nvidia has discussed investing in Mercor, a data-labeling startup that supplies expert data for its Nemotron models, in a round that would double the company’s valuation to $20 billion.
Sequence-to-sequence, or Seq2Seq, describes models that map an input sequence to an output sequence whose length may differ. Machine translation converts words in one language into another, speech recognition maps audio frames to text, and summarization produces a shorter sequence from a longer document. Many Seq2Seq systems use an encoder to represent the input and a decoder to generate output step by step, often with attention between them. Transformer encoder–decoder architectures largely replaced earlier recurrent designs. Training typically uses paired examples and token-level loss, while inference relies on greedy, beam, or sampling-based decoding. Quality depends on alignment, context limits, data coverage, and evaluation beyond surface overlap.
Nvidia has discussed investing in Mercor, a data-labeling startup that supplies expert data for its Nemotron models, in a round that would double the company’s valuation to $20 billion.
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Cursor launched Origin, a code-hosting platform built into its editor with GitHub sync, in early beta the same day GitHub suffered a major global outage.
OpenAI paused reinforcement learning on its newest models after it could not rule out that an upcoming model, Astra, reached the top cybersecurity risk tier in its safety framework.
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