As people tested the system, it asked them to rate its responses. Then, through a technique called reinforcement learning, it used the ratings to hone the system and more carefully define what it would and would not do. "This allows us to get to the point where the model can interact with you and admit when it's wrong," said Mira Murati, OpenAI's chief technology officer. "It can reject something that is inappropriate, and it can challenge a question or a premise that is incorrect." The method was not perfect.

Photo editing app Lensa grew massively popular over the last week as social media has become flooded with people posting AI-generated selfies from the app's latest feature. For $3.99, Lensa users can upload 10-20 images of themselves and then receive 50 selfies generated by the app's artificial intelligence in a variety of art styles. But, before you slam the purchase button, a word of warning: Lensa's privacy policy and terms of use stipulate that the images users submit to generate their selfies, or rather the "Face Data," can be used by Prisma AI, the company behind Lensa, to further train the AI's neural network. An artificial neural network like the one used by Lensa, or the popular text-to-image generator Dall-E 2, studies vast quantitites of data to learn how to create better and better results. To be able to convert simple sentences into surprisingly well-crafted images, Dall-E 2 was trained on hundreds of millions of images to learn the association between different words and different visual characteristics. Similarly, Lensa's neural network is continuously learning how to more accurately portray faces.

Daath AI Parser is an open-source application that uses OpenAI to parse visible text of HTML elements. It is built on top of FastAPI. It is ready to set up as a server, and make calls from any language. It is currently hosted in ai.kagermanov.com. You need to register a free account first.

Check out all the on-demand sessions from the Intelligent Security Summit here. Canva, the popular Australian-based graphic design platform, is boosting its efforts to target enterprise business users with today's release of Canva Docs, part of its Visual Worksuite that was launched in September. Generative AI plays a big role in the release: Canva Docs incorporates the company's recently-released text-to-image beta built on Stable Diffusion, as well as the newly-announced Magic Write, an AI-powered copywriting assistant built on OpenAI's GPT-3. Cameron Adams, cofounder and chief product officer of Canva, says that in 2015 the company started allowing users to create presentations in Canva, which "was a real pivotal moment," he explained. During COVID-19, he added, remote-working employees needed to communicate with colleagues differently and were looking for tools.

More than three years ago, this editor sat down with Sam Altman for a small event in San Francisco soon after he'd left his role as the president of Y Combinator to become CEO of the AI company he co-founded in 2015 with Elon Musk and others, OpenAI. At the time, Altman described OpenAI's potential in language that sounded outlandish to some. Altman said, for example, that the opportunity with artificial general intelligence -- machine intelligence that can solve problems as well as a human -- is so incomprehensibly enormous that if OpenAI managed to crack it, the outfit could "maybe capture the light cone of all future value in the universe." He said that the company was "going to have to not release research" because it was so powerful. Asked if OpenAI was guilty of fear-mongering -- Elon Musk, a co-founder of the outfit, has repeatedly called all organizations developing AI to be regulated -- Altman talked about dangers of not thinking about "societal consequences" when "you're building something on an exponential curve."

Anyone who's seen the show knows that this is not what happened. Instead, it's a somewhat humorous misconfiguration of the details--sorta like listening to a friend misremember a series that they haven't seen in awhile. In a different conversation, I asked ChatGPT how the TV show Gilligan's Island ended. In reality, Gilligan's Island was cancelled by its network, so there was no ending.

10 questions I asked AI-driven ChatGPT. Launched recently, OpenAI’s natural language processing tool is pretty impressive, but still has room for improvement.

When the eerily accurate AI image generator Dall-E 2 was released for public experimentation by OpenAI this summer, most people immediately used it to create whimsical scenes such as "samurai dolphin painted in the style of Rembrandt" or "Bruce Willis angrily devouring a cheeseburger on the moon". True, if you looked too closely at Bruce's left ear you might have noticed it wasn't there – but the freaky glitches were, though somewhat unsettling, part of the fun, not to mention a calming reminder that AI cannot entirely trick us that its images are real – yet. But more than one panicked architect also typed in, "Four-storey family home in forest in the style of Mies van der Rohe" or "Japanese-Scandi lounge area in office building lobby", and let out a tiny scream when the results resembled the renders of projects that architects otherwise spend long hours churning out. If an AI could knock out a decent interior in seconds, did it promise to be a fabulous time-saver – or would it put everyone out of a job? Not only does it celebrate the painstaking construction of physical structures, complete with tiny people and fake trees like a model railway set, which clearly took ages to make and no AI could come close to replicating – yet, but these models are also animatronic: they move, open, chirp, whirr, creak and close like Victorian clockwork figurines or the childlike works of Rodney Peppe.

Generative AI is revolutionising how we experience the internet and the world around us. Global AI investment surged from $12.75 million in 2015 to $93.5 billion in 2021, and the market is projected to reach $422.37 billion by 2028. While this outlook might make it sound like generative AI is the "silver bullet" for pushing our global society forward, it comes with an important footnote: The ethical implications are not yet well-defined. This is a severe problem that can inhibit continued growth and expansion.

Maybe that sounds like a utopian fantasy. You have gotten used to the feeling that once you put digital bits of yourself or your loved ones online, you lose control of what happens next. Dryhurst told me that with publicly available AI, such as Dall-E and ChatGPT, getting a lot of attention but still imperfect, this is an ideal time to reestablish what real personal consent should be for the AI age. And he said that some influential AI organizations are open to this, too.