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  2. cursor_aiFirst-partyProduct release
    AI score60

    English translation is being prepared.

    Quoted postSpaceX Super Intelligence · @SpaceXSI

    We've unified plans across Grok, Cursor, and X Premium. Introducing The X Subscription. https://t.co/SvkrVvBa0p

    Same story · 6 reports

    #Industry news#English text is being prepared.#OpenAI

  3. rohan_paulProduct release
    AI score70

    English translation is being prepared.

    Quoted postNeal Patel · @neal_k_patel

    You already gave the LLM the answer. So why is it writing it out from scratch? Introducing a new AI model architecture: Constrained Decoding Models (CDMs) LLMs were built to write. Most production workloads just need an answer: fast, consistent, and affordable. CDMs are purpose-built for 1 task each. They read your input once and skip the token-by-token generative loop that makes LLMs slow and expensive. Not just a decision model, but a family of 3 CDMs live today: • Classify: define your labels and get back a calibrated probability + reason for each. Used for routing, tagging, and intent detection. • Extract: describe the entities in natural language and get back well-formed JSON with confidence scores + citations. Used for web scraping, document processing, and PII redaction. • Summarize: pass in long text, images, or PDFs and get back a consistent summary under 1,000 tokens. Used for context compaction, metadata generation, and transcript digests. Built for production: • 1M tokens of multimodal (text + image) input, 31x larger than Jev • 77.2% on DecisionBench vs Jev's 72% • 200x faster, 467x cheaper than frontier LLM APIs • $0.05/M input tokens. Output is free (yes, even for summarize) Live on your favorite platforms today: @OpenRouter @vercel_dev @LiteLLM @LangChain @TrustedRouter @itsArthurAI @useRouterPlus Get 50M input tokens for free (for the first 50 hours) at link below 👀

    Same story · 2 reports

    #Product updates#Agents#English text is being prepared.