Last year, OpenAI announced Codex, a model for efficient programming with the aid of Artificial Intelligence (AI). One of the videos uploaded to the OpenAI YouTube channel showed a live demo that was hard to believe even when seen with one's own eyes. With just a few lines of commands, it was possible to create a whole game in JavaScript. The level of the commands seemed somewhat high, but with Codex you can see that it is immediately able to implement the code and run the game. In this way, Codex is a model that helps people write code much more efficiently than they could on their own.

AI art has been bursting into the mainstream thanks to the likes of DALL-E 2 and MidJourney. The tools allow anyone to create almost any image they can dream of from just a short text prompt. The results can be very, very strange, but artists, designers and brands are learning how to make the technology work for them, sometimes very successfully. But if you've been impressed so far, it seems the next advance is already on the way: AI video generators. AI art generators work based on text prompts. You type in what you want, and the art generator will create it – or at least its interpretation of the prompt.

Cerebras Systems, with its latest WSE-2 chip, has set the record for the largest AI model ever trained on a single device. The chip, which has 850k cores and 2.6 trillion transistors, is much larger than the largest GPUs. It has 123x more cores, 1k times more memory, and 12k times more bandwidth than the largest GPU. This allowed Cerebras to train a 20 billion parameter neural network model on a single chip. Doing so with GPUs would require complex compute cluster engineering and management, which could be much more expensive and only doable at large tech companies.

Generative models capable of automatically producing paragraphs of text or digital art are becoming increasingly accessible. People are using them to write fantasy novels, marketing copy, and to create memes and magazine covers. Content automatically created by software is poised to flood the internet for better or worse as AI technology is commercialized. Take Cosmopolitan's recent and "world's first artificially intelligent magazine cover," for instance: the image of a giant astronaut walking on the surface of a planet against a dark sky splattered with what looks like stars and gas as produced by OpenAI's DALL-E 2 model. Karen Cheng, a creative director, described trying various text prompts to guide DALL-E 2 in producing the perfect picture.

Photographer Nicholas Sherlock created a Sony camera app that sends all the photos taken directly to OpenAI's DALL-E 2 artificial intelligence …

OpenAI's top researcher has made a startling claim this week: that artificial intelligence may already be gaining consciousness. Ilya Sutskever, chief scientist of the OpenAI research group, tweeted today that "it may be that today's large neural networks are slightly conscious." Needless to say, that's an unusual point of view. The widely accepted idea among AI researchers is that the tech has made great strides over the past decade, but still falls far short of human intelligence, nevermind being anywhere close to experiencing the world consciously. It's possible that Sutskever was speaking facetiously, but it's also conceivable that as the top researcher at one of the foremost AI groups in the world, he's already looking downrange.

Artificial intelligence will not replace humans, we are not rivals. Here are some of my favorites made together with ai friends.

Verdict has listed five of the companies that trended the most in Twitter discussions related to disruptive tech, using research from GlobalData's Technology Influencer platform. The top companies are the most mentioned companies among Twitter discussions of more than 513 disruptive tech experts tracked by GlobalData's Technology Influencer platform during the second quarter (Q2) of 2022. OpenAI's text-to-image engine DALL·E 2 not understanding some mysterious language, and the company's release of GPT-3, a new generative language model, were some of the popularly discussed topics in Q2. Spiros Margaris, a venture capitalist and board member at the venture capital firm Margaris Ventures, shared an article on the artificial intelligence (AI) company, OpenAI, having found its text-to-image engine DALL·E 2 to show peculiar behaviours, including something that may be hidden or a fictional language. According to Giannis Daras, a PhD student at the University of Texas at Austin, the AI model produced an artwork when given the input "apoploe vesrreaitais eating Contarra ccetnxniams luryca tanniounons", which makes no sense to humans but the machine generated images of birds eating bugs constantly, the article detailed.

I've been dying to try DALL·E 2 ever since I first saw this artificially generated image of a "Shiba Inu Bento Box". For those of you unfamiliar, DALL·E 2 is a system created by OpenAI that can generate original images from text. It's currently in closed Beta -- I signed up for the waitlist in early May and got access at the end of July. During the Beta, users receive credits (50 free in the first month, 15 credits every month after that) where every use costs 1 credit, and each use results in 3–4 images. You can also purchase 115 credits for US$15.

DALL-E 2, OpenAI's powerful text-to-image AI system, can create photos in the style of cartoonists, 19th century daguerreotypists, stop-motion animators and more. But it has an important, artificial limitation: a filter that prevents it from creating images depicting public figures and content deemed too toxic. Now an open source alternative to DALL-E 2 is on the cusp of being released, and it'll have no such filter. London- and Los Altos-based startup Stability AI this week announced the release of a DALL-E 2-like system, Stable Diffusion, to just over a thousand researchers ahead of a public launch in the coming weeks. A collaboration between Stability AI, media creation company RunwayML, Heidelberg University researchers and the research groups EleutherAI and LAION, Stable Diffusion is designed to run on most high-end consumer hardware, generating 512 512-pixel images in just a few seconds given any text prompt. "Stable Diffusion will allow both researchers and soon the public to run this under a range of conditions, democratizing image generation," Stability AI CEO and founder Emad Mostaque wrote in a blog post.