Sep 04, 2019

I traveled to Taiwan last week, where I met many CEOs interested in AI transformation of traditional companies. I also visited Taiwan AI Labs which, similar to OpenAI, started as a nonprofit AI research institute.

Creating a virtual representation of a scene using traditional polygons and texture maps involves several complex operations, and even neural-network approaches have required manual preprocessing. Researchers propose a new deep-learning pipeline that visualizes scenes with far less fuss.

A growing number of companies that sell standardized tests are using natural language processing to assess writing skills. Critics contend that these language models don’t make the grade.

OpenAI raised eyebrows in February when it announced — and withheld — the full version of its groundbreaking language model, GPT-2. Six months later, the company has re-examined the decision.

Microscopes outfitted with AI-driven augmented reality could improve the accuracy of cancer diagnoses. Google Health developed an attachment for analog microscopes that outlines signs of breast and prostate cancer in real time.

Deep learning models can be unwieldy and often impractical to run on smaller devices without major modification. Researchers at Facebook AI Research found a way to compress neural networks with minimal sacrifice in accuracy.

Theoretical advances can be thrilling, but the excitement can drown out all the ways AI is actually being put to use. DeepIndex provides an up-to-date, well organized, cheeky guide to practical applications culled from news reports.

I traveled to Taiwan last week, where I met many CEOs interested in AI transformation of traditional companies. I also visited Taiwan AI Labs which, similar to OpenAI, started as a nonprofit AI research institute.