💥 Anthropic reveals Claude Opus 4.7
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💥 Anthropic reveals Claude Opus 4.7
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🌎️ Tencent open-sources a model that can generate full 3D worlds
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🧪 OpenAI launches GPT-Rosalind for biology and drug discovery
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🤖 Physical Intelligence says its new robot brain can figure out tasks it was never taught
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💥 Anthropic reveals Claude Opus 4.7
Opus 4.7 delivers meaningful improvements over Opus 4.6 in advanced software engineering, showing particular strength on the most challenging coding tasks by handling complex, long-running projects with greater rigor and implementing robust methods to verify its own outputs.
While it remains less broadly capable than Claude Mythos Preview — Anthropic’s most powerful and best-aligned model to date — Opus 4.7 outperforms Opus 4.6 across multiple benchmarks in coding, vision, and document reasoning.
Anthropic deliberately trained Opus 4.7 with reduced cyber capabilities compared to Mythos Preview and is using its deployment to test safety safeguards ahead of the eventual broader release of Mythos-class models.
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🌎️ Tencent open-sources a model that can generate full 3D worlds
Tencent has released HY-World 2.0, a multimodal system capable of generating complete, production-ready 3D environments from text, images, or video inputs.
Instead of producing short clips or static scenes, it creates fully editable 3D assets such as meshes, point clouds, and Gaussian splats that can be directly exported into engines like Unity and Unreal.
The system uses a multi-stage pipeline to construct panoramic scenes, plan navigation, expand environments, and assemble them into coherent, usable worlds — dramatically accelerating the creation of maps, level prototypes, and digital assets compared to traditional workflows.
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🧪 OpenAI launches GPT-Rosalind for biology and drug discovery
OpenAI has introduced GPT-Rosalind, a new AI model specialized in life sciences and built to accelerate research in biology, drug discovery, and translational medicine.
The model combines significantly stronger reasoning across chemistry, protein engineering, and genomics with improved tool-use capabilities, enabling researchers to move more efficiently from literature review to experimental planning.
Its core goal is to shorten the traditionally long early-stage discovery process — which often takes 10 to 15 years — by helping scientists explore more hypotheses, connect complex datasets, and design better experiments earlier in the pipeline.
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🤖 Physical Intelligence says its new robot brain can figure out tasks it was never taught
Physical Intelligence has introduced π0.7, a new model that enables robots to perform tasks they were never explicitly trained for by adapting in real time to verbal instructions rather than requiring retraining.
Although it still faces challenges with fully autonomous multi-step tasks from a single command, the system represents meaningful early progress toward more flexible and general-purpose robotics.
The technology remains in the research phase but signals an important shift from rigid, task-specific training toward systems capable of real-time learning and adaptation — a critical requirement for scaling automation in real-world environments.
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