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News reporting focused on AI and machine learning, covering the companies behind these technologies, their real-world applications, and the ethical concerns they raise. This includes areas like generative AI (large language models, text-to-image and video), speech tech, and predictive analytics.

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4 articles

AI Models

Appeals Court Lifts Injunction Blocking Perplexity's AI Agents From Amazon

A US appeals court overturned an injunction that blocked Perplexity's AI shopping agents from accessing Amazon, ruling that users, not the AI company, are the ones accessing the platform. The decision, the first by a federal appeals court on AI agents, found Amazon unlikely to succeed on its computer fraud claim. The underlying case remains unresolved, with Amazon vowing to continue its legal fight.

Aug 55 minNeura News

AI Tools

Perplexity Model Council Expands to Computer Platform

Perplexity has expanded its Model Council feature to its Computer platform, allowing users to configure multi-model queries with up to eight AI models. The council generates a synthesis report showing where models agree and diverge on ambiguous issues. The feature is now available to individual Pro and Max subscribers, with usage-based billing.

Jul 284 minNeura News

AI Models

Perplexity's Search as Code lets AI models write custom search pipelines

Perplexity introduces 'Search as Code', a new architecture where AI models write their own search workflows as Python code instead of calling fixed APIs. The approach reduces token usage by 85% in a cybersecurity benchmark and beats rivals on four out of five tests. The system is rolling out in Perplexity Computer and the Agent API.

Jun 74 minNeura News

Research

Study Tests Whether Transformers Need All Three QKV Projections

A new paper systematically evaluates three variants of projection sharing in transformer attention: shared key-value, shared query-key, and a single projection. The authors found that sharing key and value projections performs on par with standard QKV attention while reducing KV cache by 50% with only 3.1% perplexity degradation. Combining this with grouped-query or multi-query attention can cut cache by up to 96.9%, enabling practical on-device inference.

Jun 53 minNeura News