#xAI

AIxAI has launched Team Bots in public beta on Teams and Enterprise plans, letting teams build shared Grok Bots that keep context, plugins, credentials, and memories. Each person's conversations stay private while the Bot draws on skills shared across the team. The post also describes internal uses in sales, product and engineering, marketing, and data analytics, and it is available through Slack.

AISpaceXAI says its combined support team handled a 175% rise in tickets without hiring, crediting Grok Bot, which it says would otherwise have required about 200 additional staff. The company reports resolving tickets for $0.20 to $0.30 each, versus the $1 to $4 per resolution it attributes to traditional AI support tools. Grok Bot is also reported to resolve 99% of refund requests without human intervention.

AIxAI released Grok 4.7, which it calls its most capable model for coding and knowledge work, built on a larger base model than Grok 4.6 and trained with a longer reinforcement learning run. It is priced from $2 per million input tokens and $6 per million output tokens, the same as Grok 4.6, and is available in Cursor, Grok Build, and the Grok API. xAI reports gains on CursorBench 4.0 (46.3%) and AA Briefcase v1.1 (1,657) over Grok 4.6, and says it posts the strongest safety results it has tested on refusals and jailbreak resistance.

Why it matters: The release pairs a new base model with benchmark tables against named rivals and pricing, letting readers compare its coding and office-work gains against Grok 4.6 and frontier models.

AIxAI released Grok Voice Transcribe 2.0, a speech-to-text model that is twice as accurate as Grok Voice Transcribe 1.0 at the same price, and ranks first for accuracy among 32 streaming models on the Artificial Analysis leaderboard. Batch transcription costs $0.10 per hour of audio and streaming $0.20 per hour, with diarization, timestamps, and key terms included. Existing Speech-to-Text API integrations gain the improvement with no code changes, and developers must pin grok-voice-transcribe-1.0 to stay on the older model during the transition.

AIGrok Build now has memory, which records conventions, decisions, and project facts after each completed turn and reads them in later sessions. Notes are stored per project plus a global set, and the /dream command organizes them into topic files while /memory opens a read-only browser. The feature is available now and applies to new sessions.

AIxAI built a Grok-powered procurement agent, Haggle Bot, that audits vendor spend, flags unused SaaS seats, and prepares renewal negotiations. The Bot has identified more than $100,000 in direct savings, including $14,220 from 43 unused seats of one SaaS product and $85,662 a year in unused SKUs from another. A person still approves any spending, contract terms, or messages sent to vendors.

AIxAI describes Grok Bot as built around persistent agents that keep their own identity, memory, runtime, and tools, rather than disposable chat sessions. Its interface organizes around five objects: Bots, Chats, Prompts, Tools, and Artifacts. Each Bot's avatar shows its identity and lifecycle state, with hover revealing its current action.

AIxAI announced Grok Bot, a platform for creating autonomous AI Bots that run in the cloud and carry out tasks end to end inside tools teams already use. Today's release adds access, network, and audit controls so enterprises can govern Bots at scale, and Enterprise customers can get Grok Bot free for two weeks.

AICursor has been acquired by SpaceX, completing a process that began in April when the two companies announced a partnership to accelerate model training. The post says the deal gives Cursor access to what it calls the largest GPU fleet in the world, which it expects to yield more capable models at lower cost. It cites Grok 4.6, released Wednesday, as an early look at what the companies can build together.

Why it matters: The post confirms a completed acquisition and links it to GPU access and cheaper model serving, which explains why the deal matters for coding tools.

AIARC Prize reports that the top Kaggle entry reached 24% on the ARC-AGI-2 private dataset at $0.20 per task, and that all winning solutions and papers are open source. The top verified commercial model, Opus 4.5 (Thinking, 64k), scored 37.6% at $2.20 per task, while a Poetiq refinement on Gemini 3 Pro reached 54% at $30 per task. The author argues that refinement loops are the main driver of 2025 progress, and says ARC-AGI-3 is planned for early 2026.

Why it matters: The post links 2025 competition results to a broader argument about refinement loops, showing how benchmark outcomes are being read as evidence of AI reasoning progress.