
Onton, a San Francisco-based search and discovery company, has released Ontology 1, a neurosymbolic model for complex, conversational, multimodal product search. On a 90-query benchmark scored by three independent LLM judges, Ontology 1 reached a mean precision@10 of 0.630, against 0.543 for Google Shopping and 0.469 for Amazon. It did this while indexing roughly 1% of their catalogs. Is it deployable Yes, but not as weights you download. Ontology 1 is live for end users at Onton.com, an
A neurosymbolic search model called Ontology 1 has been released for e-commerce product discovery, combining explicit reasoning about product properties with neural pattern matching. In benchmark testing on home decor queries, it achieved higher precision scores than major competitors while indexing a much smaller catalog. The model differs from traditional search by building an inspectable knowledge graph that reasons from objective product properties rather than relying on seller labels or category metadata alone. The system is currently available as a live product but not as downloadable weights or through a public API.

Microsoft has open sourced code-testing-generator, a polyglot agent that writes unit tests and then proves they work. It ships in the dotnet-test plugin inside the MIT-licensed dotnet/skills repository. The agent targets a gap that coding assistants usually leave open. A prompt like ‘generate unit tests’ does not say which framework, file location or assertions to use. code-testing-generator settles those decisions by reading the repository before it writes anything. It then pla

A new SaferAI report finds Z.ai's open-weight GLM-5.2 approaches frontier AI capabilities while lacking key safety mitigations, renewing concerns that powerful open models could outpace governance and safeguards.

In this tutorial, we design an end-to-end evaluation workflow for PerceptionBench. This multimodal benchmark measures fine-grained visual perception capabilities across tasks such as OCR, counting, localization, contextual reasoning, comparison, depth understanding, and hallucination detection. We begin by configuring a Colab-compatible environment, installing the required libraries, and loading a balanced subset of the dataset through a robust multi-stage streaming and download strategy. We th
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