Models are learning how to generate images from captions, a sign that they’re getting better at understanding our world.
Of all the AI models in the world, OpenAI’s GPT-3 has most captured the public’s imagination. It can spew poems, short stories, and songs with little prompting, and has been demonstrated to fool people into thinking its outputs were written by a human. But its eloquence is more of a parlor trick, not to be confused with real intelligence.
Nonetheless, researchers believe that the techniques used to create GPT-3 could contain the secret to more advanced AI. … Now new research from the Allen Institute for Artificial Intelligence, AI2, has taken this idea to the next level. The researchers have developed a new text-and-image model, otherwise known as a visual-language model, that can generate images given a caption. Read More
Daily Archives: September 28, 2020
Rethinking human-AI interaction
Imagine 1977, sitting at the helm of one of your very first personal computers. The Commodore “Personal Electronic Transactor,” endearingly nicknamed the PET, promised to be an all-in-one “bookkeeper, cook, language tutor, inventory clerk, and playmate.” For the first time, you could type up programs on the tiny “chiclet” keyboard — working out your math homework, saving snippets of recipes, designing simple graphics — and see the results spring up before your eyes. Unlike a washing machine or a calculator, here was a first encounter with a machine that was fundamentally open-ended, dynamic, and responsive in a tangible way. Read More
GPT-3’s bigotry is exactly why devs shouldn’t use the internet to train AI
It turns out that a $1 billion investment from Microsoft and unfettered access to a supercomputer wasn’t enough to keep OpenAI’s GPT-3 from being just as bigoted as Tay, the algorithm-based chat bot that became an overnight racist after being exposed to humans on social media. Read More
Model Lifecycle: From ideas to value
Value scoping, discovery, delivery, and stewardship
In Part 1 of this series we examined the key differences between software and models; in Part 2 we explored the twelve traps of conflating models with software; and in Part 3 we looked at the evolution of models. In this article, we go through the model lifecycle, from the initial conception of the idea to build models to finally delivering the value from these models. Read More
Knowledge in the grey zone: AI and cybersecurity
Cybersecurity protects citizens and society from harm perpetrated through computer networks. Its task is made ever more complex by the diversity of actors—criminals, spies, militaries, hacktivists, firms—operating in global information networks, so that cybersecurity is intimately entangled with the so-called grey zone of conflict between war and peace in the early twenty-first century. To counter cyber threats from this environment, cybersecurity is turning to artificial intelligence and machine learning (AI) to mitigate anomalous behaviours in cyberspace. This article argues that AI algorithms create new modes and sites of cybersecurity knowledge production through hybrid assemblages of humans and nonhumans. It concludes by looking beyond ‘everyday’ cybersecurity to military and intelligence use of AI and asks what is at stake in the automation of cybersecurity. Read More
Rick's Cafe AI 