The Future of Artificial Intelligence
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The State of State of AI Report

The State of State of AI Report | The Future of Artificial Intelligence | Scoop.it

"Introduction The State of AI Report is our comprehensive round-up of the most important developments of the year in AI research, industry, safety, and politics. I started co-producing the report in 2018 with fellow investor Ian Hogarth. After he took on the important role of leading the UK Government’s AI Safety Taskforce, it was a Team Air Street production in 2023." - by Air Street Capital & Nathan Benaich

Juliette Decugis's insight:

From AlphaGo to LLMs with other big innovations such as diffusion models and CLIP, the past five years have seen a rapid boost in AI development through the creation of many private labs, GPU investments by big tech companies and a focus on open source models. This report highlights the key research developments of AI but most interestingly the ecosystem's changes and its societal impacts. High level and easy to read :)

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Scooped by Juliette Decugis
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Google’s AI passed the Turing test — and showed how it's broken

Google’s AI passed the Turing test — and showed how it's broken | The Future of Artificial Intelligence | Scoop.it
Alan Turing's Imitation Game has long been a benchmark for machine intelligence. But what it really measures is deception.
Juliette Decugis's insight:

In 1950, Turing designed a simple test to evaluate whether a computer possessed artificial intelligence comparable to humans; a computer must be able to pass as a human during a series of questions.

 

Today, Google's text generating deep learning models such as GPT-3 easily pass the Turing test. However, whether these models actually understand their generated output or rather excel at combining human text for specific questions stays up for debate.

 

This article points out the outdated nature of the Turing test to measure NLP advances which is now evaluated on new benchmarks. The Turing test instead raises ethical concerns for AI and its potential for deceit. 

 

It is also interesting to note that NLP models can pass as humans on specific questions but often fail when applied to questions to new domains. Far from resembling human consciousness, current AI remains very specialized and data powered. This motivates the development of new tests to understand model generalization. 

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