Frontiers

Computational Frameworks for Decision-Making: From Bayesian Inference to Reinforcement Learning Models

The ability to make adaptive decisions in uncertain environments is a fundamental characteristic of biological intelligence. Historically, computational ...

Industrial AI's Real Bottleneck Isn't the Algorithm

Walk through enough industrial AI deployments and a pattern becomes uncomfortable to ignore. The pilot works. The model ...

Sandisk: A Cyclical Stock Priced For Secular Perfection

The company is being misunderstood as a secular growth story rather than a cyclical commodity producer. Even though the ...
24/7 Wall St.

The Silicon Showdown: Can Nvidia Defend Its Moat Against Google’s TPUs?

Nvidia (NASDAQ:NVDA | NVDA Price Prediction) remains the undisputed heavyweight champ of AI chips, and CEO Jensen Huang seems to be ready to keep rising above the competition. It’s hard to tell just ...

From LLMs to hallucinations, here’s a simple guide to common AI terms

The rise of AI has brought an avalanche of new terms and slang. Here is a glossary with definitions of some of the most ...
EDN

The truth about AI inference costs: Why cost-per-token isn’t what it seems

The AI industry has converged on a deceptively simple metric: cost per token. It’s easy to understand, easy to compare, and easy to market. Every new system promises to drive it lower. Charts show ...

Google unveils TurboQuant, a new AI memory compression algorithm — and yes, the internet is calling it ‘Pied Piper’

Google’s TurboQuant has the internet joking about Pied Piper from HBO's "Silicon Valley." The compression algorithm promises ...
VentureBeat

Google's new TurboQuant algorithm speeds up AI memory 8x, cutting costs by 50% or more

As Large Language Models (LLMs) expand their context windows to process massive documents and intricate conversations, they encounter a brutal hardware reality known as the "Key-Value (KV) cache ...
PNAS

Navigating the mysterious space of evolutionary histories

In this issue of PNAS, Gao et al. (1) probe the limits of Bayesian phylodynamic inference, a statistical framework that has revolutionized the study of pathogen evolution and epidemic spread. By ...
acm.org

Building Intelligent Agents with Neuro-Symbolic Concepts

One of the long-term goals of artificial intelligence (AI) is to build machines that can continually learn new knowledge from their experiences, ground these experiences in the physical world, and ...
Scientific Research Publishing

MacKay, D.J.C. (2003) Information Theory, Inference, and Learning Algorithms. Cambridge University Press.

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 ...
IEEE

Practical Secure Inference Algorithm for a Fine-Tuned Large Language Model Based on Fully Homomorphic Encryption

Abstract: Large language models (LLMs) are currently at the forefront of the machine learning field, showing broad application prospects but at the same time presenting certain risks of privacy ...