MarkTechPost (3 weeks ago)
Google Research has introduced Retrieve-for-Train (R4T), a framework for search that returns coherent, diverse result sets. It trains a fan-out language model with RL once, using groundedness, diversity, and alignment rewards.
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Its prices make it competitive for developers and businesses willing to pay for their AI use, but the lack of a free option will likely hamstring mainstream appeal.
Mark Zuckerberg says Meta committed as much as $200B to AI infrastructure before anyone could tell him it would work, with his chief AI officer saying it was not clear at all. Meta’s free cash flow fell 91% in the second quarter.
More AI agents will soon be able to browse and purchase from Shopify listings, marking an expansion of the company’s agentic commerce ambitions.
AI leaders joined whistleblowers and security leaders at a sweeping parliamentary session, while a few hundred meters away Britain’s spy chief warned AI could be used to create new bioweapons.
The company unites resources from disparate macOS devices
If you thought recursive self-improvement was bad, get ready for “autonomous replication and adaptation.”
Z.ai’s GLM-Legal is a legal AI model built on GLM-5.3-Flash. It scores 19.2% all-pass on Harvey’s Legal Agent Benchmark, nearly 3x its base, at $0.15 per test. Access is by application.
Alibaba’s Qwen team has introduced QwenGyre, an elastic reinforcement learning RL framework for extreme-long-horizon agent training. QwenGyre is an online reinforcement learning system from Alibaba that trains coding agents through unmodified, black-box harnesses.
We checked 12 AI live translation tools, including Palabra.ai, Google Live Translate, DeepL Voice, Teams Interpreter and Wordly, against official pages for languages, latency, platforms and pricing.
TII has released Falcon-ASR, a 1.6B speech recognition model for Arabic with an Emirati focus. It reports 20.92% average WER on 6 Arabic test sets, but weights and an API are not yet available.
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