Why no AGI can be built with language models

This paper is actually only my notes of presentation “A Formal Perspective On Language Models”, given by Ryan Cotterell, assistant professor at ETH Zürich in the Department of Computer Science

A Thought Once Spoken Is a Lie
(The Fundamental Reasons for Uncertainty and Low Inter-Rater Reliability on a Sentence Level)

Data scientists seem to believe that a magic Genie in the form of AI exists, and all you

Why you should not base your workflow process decisions on any segment-level score (including Phrase’s new QPS)

As I watched the recent video presentation of the Quality Performance Score (QPS)

Our paper “Neural Machine Translation of Clinical Text” has been accepted by the Frontiers magazine

In our quest to provide the best services to our clients and utilize the abilities of machine translation to the utmost

Our Most Significant R&D Result in 2023: Edit Distance Prediction Method

As 2023 draws to a close, it’s a perfect time to talk about year-end results – and we have something very special up our sleeve.

Why it is important to acknowledge the lack of intelligence in “AI”

Generative LLMs, colloquially known as “AI”, have made great strides in the recent months – but that doesn’t mean that they became “intelligent” or that they stopped “hallucinating” and producing inaccurate answers or translations.

GEMBA-SQM translation quality evaluation is easy to implement as zero-shot LLM prompt … and totally useless

The hype ignores AI hallucination, because the hype is caused by people hallucinating on AI.

Translation quality evaluation is all we need

“The unpredictable abilities emerging from large AI models: Large language models like ChatGPT are now big enough that they’ve started to display startling, unpredictable behaviors.”