AWS Elemental Inference will let networks and studios convert live sports, news and other content into vertical video in real-time.

Users running a quantized 7B model on a laptop expect 40+ tokens per second. A 30B MoE model on a high-end mobile device ...

In machine learning, privacy risks often emerge from inference-based attacks. Model inversion techniques can reconstruct ...

Adding big blocks of SRAM to collections of AI tensor engines, or better still, a waferscale collection of such engines, turbocharges AI inference, as has ...

Extracting and analyzing relevant medical information from large-scale databases such as biobanks poses considerable challenges. To exploit such "big data," attempts have focused on large sampling ...

After years of rapid advancement in cloud‑centric AI training and inference, the industry is reaching an edge AI tipping point.

ABSTRACT: A new conceptual framework is presented that unifies Gödel’s incompleteness theorems with practical physical modeling through information-theoretic analysis. The method of variables with ...

Abstract: This article introduces a scalable distributed probabilistic inference algorithm for intelligent sensor networks, tackling challenges of continuous variables, intractable posteriors, and ...

ABSTRACT: For an independent and identically distributed skew-t-normal random sequence, this paper establishes the limit distribution of normalized sample range M n − m n . Based on the optimal ...

new video loaded: I’m Building an Algorithm That Doesn’t Rot Your Brain transcript “Our brains are being melted by the algorithm.” [MUSIC PLAYING] “Attention is infrastructure.” “Those algorithms are ...

Abstract: Although AI has been extensively adopted and has profoundly transformed our lives, it is not feasible to directly deploy large AI models on edge devices with limited resources. To enhance ...