AIR's platform can discover agents running at a company, continuously vets any skills and add-ons they use, and blocks any unwanted behavior.
This is a summary curated by AIFuture. Read the complete article at the original source:
Read the full story on TechCrunchMost production voice stacks are three systems stitched together. One model transcribes, a second separates speakers, and a detector decides when the user stopped talking. Each hand-off adds latency and a new failure mode. Muse Voice Transcribe, announced by Meta Superintelligence Labs this week, collapses those three jobs into a single autoregressive model. Meta calls […] The post Meta…
Sep 2, 2026
Agentic assistants have a structural problem: the context that makes them useful — deal documents, privileged files, client records — is exactly the context users cannot send to a cloud endpoint. This week, Perplexity shipped its answer for Mac. Hybrid compute splits a single Perplexity Computer task between frontier models in the cloud and a […] The post Perplexity Releases Hybrid Compute on…
Sep 2, 2026
Google has reportedly been reaching out to a number of Hollywood's biggest studios, hoping to strike licensing agreements that would allow it to train its AI models on copyrighted material in exchange for massive piles of cash. In theory, these deals would be a win-win: a huge financial boon to the studios that would also give Google a significant advantage in its race to outpace other AI…
Sep 1, 2026
Five-course series on neural networks, CNNs, sequence models, and transformers from DeepLearning.AI.
Andrew Ng's flagship program covering supervised and unsupervised learning, neural networks, and best practices for real-world ML.
Harvard's deep dive into the algorithms behind modern AI — search, knowledge, optimization, and machine learning.
Get the most important AI news and course picks in your inbox.