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The Day in AI

Friday 13 November 2026

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In short

  • OpenAI launched ChatGPT Wallet on 13 November, letting its agents complete purchases for US ChatGPT Pro subscribers after a Face ID or fingerprint approval.
  • ggml-org released llama.cpp v1.0.0 and ggml v1.0.0 after about 3.5 years of development, and both projects now follow semantic versioning.
  • Google Cloud open-sourced TPU Sync, a C++ library for moving KV caches and weights, and reports over 90% lower KV transfer latency on large MoE models.
  • Shi Yunfeng, who ran ByteDance's AI chip and DPU teams, has resigned, according to LatePost, after the first chip fell short of expectations.
  • Meta opened Muse outbound phone calls to US businesses to all paying US subscribers on 12 November, after a September test with early adopters.

The day in brief

OpenAI launched ChatGPT Wallet on 13 November, which lets ChatGPT agents check out and pay for orders for US ChatGPT Pro subscribers once the user approves each purchase biometrically.

Until now ChatGPT agents could recommend products and fill carts, and the user still had to pay. With Wallet, a Pro subscriber saves an eligible US-issued Visa, Mastercard or American Express card. Each order is charged with a payment token, so the agent and the merchant never see the card number, and every purchase needs Face ID or a fingerprint. OpenAI says spending limits and pre-approved purchases by category or time period will come later. It also published a Commerce Partner Playbook telling retailers how to take agent orders.

On the open-source side, ggml-org tagged llama.cpp v1.0.0 and ggml v1.0.0, the first major versions of the local inference library and the tensor library under it. The change is a promise about stability. From now on, anything that breaks the public C headers of libllama or libggml gets a major version bump. Minor versions carry new features, backend updates and model support, and patch versions carry bug fixes.

Google Cloud released TPU Sync, an open-source C++ library with Python wheels for PyTorch and JAX. It treats TPU high-bandwidth memory, host DRAM, shared storage and the data center network as one memory hierarchy, so a KV cache (the stored attention state of a conversation) can be moved or tiered without custom plumbing. It plugs into vLLM and SGLang as a KV connector and as the transfer backend when prefill and decode run on separate machines. Google reports over 90% lower KV transfer latency on MoE models of 235B to 480B parameters, measured on TPU v7x.

Also in the news

  • Shi Yunfeng, who joined ByteDance in 2018 and led its AI chip and DPU teams, has resigned, according to LatePost. The TPU-style accelerator reached tape-out this year but missed performance targets, and a successor chip is in development.
  • Meta made Muse's outbound calls to US businesses such as restaurants and the DMV available to all paying US subscribers on 12 November, with plans from $20 per month.
  • Edge0 open-sourced Edge0-145B and Edge0-120B on 12 November and says the larger model runs on a laptop with 29GB peak memory. The company reports 64.6 on DeepSWE 1.1, and its speed figures are only partly confirmed.
  • ElevenLabs released ElevenAI in preview on 11 November, an app for meeting notes and dictation in over 90 languages that can hand follow-ups to ElevenAgent.
  • Google and Samsung opened preorders for the first Android XR glasses on 12 November, without a display, from $395 in Warby Parker frames and shipping in December.
  • OpenAI has disbanded its standalone robotics team and moved the staff into research and Applied, according to Fortune.
  • SpaceXSI laid off about 60 Grok Imagine staff in the past week to focus on coding tools, according to The Information.
  • Fractile, a British AI chip startup, has reportedly raised $720 million at a $7 billion valuation.

Everything from this day

Launches and products

People and teams

Shi YunfengByteDance → unknown. Shi, who joined ByteDance in 2018, has submitted his resignation and is handing over his duties, according to LatePost. The AI chip effort, a custom accelerator modeled on Google's TPU, reached tape-out this year but fell short of performance expectations, and a successor is in development.