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Follow the change ·

The day,
in perspective.

What happened in AI and robotics — and the change behind it. A reading path through 19 stories from BIG CHANGE.

Ordered using RADAR attention, story opens and likes. Excerpts from our published reporting; open a story for the full context and sources. Dates in UTC.

Original story: analysis

NVIDIA dates a faster DLSS 5 model for Hogwarts Legacy

NVIDIA says a smaller DLSS 5 neural rendering model reaches Hogwarts Legacy on November 5. A separate Frame Generation Performance Mode is available in beta now.

The big change

NVIDIA has put dates and hardware categories on the next DLSS 5 rollout while giving developers and modders a smaller neural rendering model to work with. Players can try the distinct Frame Generation Preset C beta now, but must wait for the dated game updates to evaluate the revised neural rendering model. The claimed overhead, memory and frame-rate improvements come from NVIDIA's announcement; independent image-quality and performance results for these releases remain to be established.

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Original story: analysis

Z.ai opens GLM-Legal beta applications for legal teams

Z.ai is inviting legal teams to apply for GLM-Legal API access. Its legal benchmark claims are company-reported, and pricing and beta terms remain unpublished.

The big change

What changed: Z.ai is offering legal teams a route to test a model trained for legal tasks, with API access handled through an application. The public evidence consists of company examples and reported benchmarks; independent legal performance testing is still needed.

Why it matters: A legal team evaluating such a system can ask whether it preserves the trail from matter documents to suggested edits, cited evidence or research. The examples make those tasks concrete, while their correctness still needs checking against source material and applicable law.

What to watch: Beta access terms, reproducible benchmark settings and results on a team's own reviewed matters will determine whether GLM-Legal can move beyond a sales discussion. The announcement leaves those purchasing and validation questions open.

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Original story: analysis

MiniCPM-V 4.7 offers two model sizes for local vision tasks

OpenBMB released MiniCPM-V 4.7 in 35B-A3B and 1B variants. Its repository describes local image and video tasks, but its phone memory and speed figures remain vendor-reported measurements.

The big change

What changed: OpenBMB has published both a large mixture-of-experts checkpoint and a much smaller model in the same vision series, with example code for image and video prompts and separate quantized downloads. Developers can choose a model and runtime around their actual task and device.

Why it matters: Local visual analysis can keep the inference workload on hardware the developer controls. The larger model's reported phone performance depends on a particular combination of scheduling, quantization and speculative sampling. Downloading its standard checkpoint alone does not reproduce that result.

What to watch: The useful decision is whether the chosen runtime can handle the required image detail, video frames and response time on the target device. OpenBMB's model cards expose the weights and processing controls, but its launch numbers do not answer that application-specific question.

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