I created an OpenAI compatible endpoint to make migrating to Text-Generator.io There are more controls like min_probability to generate a short likely autocomplete as well as a max_sentence parameter only supported in the Text Generator.io HTTP JSON API so consider switching to that. We think OpenAI is 10x too expensive right now, so we bet on it! If you send us your usage (currie/babbage/davinci) this month and havn't seen 10x cost savings after switching for a month, we will drop pricing for everyone to make sure it's a 10x cost savings.

"In my youth, I would've argued that life is just a series of random events, devoid of any meaning. But as a data scientist, I must recognise that patterns sometimes emerge." When Gilfoyle, one of the main characters on the popular sitcom Silicon Valley said this, he could have as well extended this to patterns that emerge in the AI innovation space. It is an undeniable fact that whenever a new, popular and eye-grabbing tool comes to the market, tech companies rush to replicate them and create their own renditions. This gives birth to a certain trend – a pattern.

An artificial intelligence program that has impressed the internet with its ability to generate original images from user prompts has also sparked concerns and criticism for what is now a familiar issue with AI: racial and gender bias. And while OpenAI, the company behind the program, called DALL·E 2, has sought to address the issues, the efforts have also come under scrutiny for what some technologists have claimed is a superficial way to fix systemic underlying problems with AI systems. "This is not just a technical problem. This is a problem that involves the social sciences," said Kai-Wei Chang, an associate professor at the UCLA Samueli School of Engineering who studies artificial intelligence. There will be a future in which systems better guard against certain biased notions, but as long as society has biases, AI will reflect that, Chang said.

In artificial synthesis, diffusion models worked very well, even better than GANs for images. Because of this, they became popular in the machine learning community and are a key part of systems like DALL-E 2, Imagen and Parti that use text to make photorealistic images. The field of computer vision has had the most success with diffusion models. But most of the recent research on diffusion models is not available to the machine learning community as a whole and stays behind closed doors. Here is the READY-to-USE code that will guide you through the most essential parts of diffusion models.

Ghosting can hurt, for sure. When someone suddenly cuts off contact, doesn't show up at a date or just unmatches on one of those many dating apps, it sucks. One Filipino lawmaker is trying to make it stop, which could be a tall order. Arnolfo Teves Jr., a member of the Philippine House of Representatives, said ghosting was "a form of emotional cruelty and should be punished as an emotional offense." The bill -- yes there's proposed legislation -- doesn't offer specific penalties, but Teves suggested in an interview that community service might work.

Relations are basic building blocks of human cognition. Classic and recent work suggests that many relations are early developing, and quickly perceived. Machine models that aspire to human-level perception and reasoning should reflect the ability to recognize and reason generatively about relations. We report a systematic empirical examination of a recent text-guided image generation model (DALL-E 2), using a set of 15 basic physical and social relations studied or proposed in the literature, and judgements from human participants (N = 169). Overall, we find that only ~22% of images matched basic relation prompts. Based on a quantitative examination of people's judgments, we suggest that current image generation models do not yet have a grasp of even basic relations involving simple objects and agents. We examine reasons for model successes and failures, and suggest possible improvements based on computations observed in biological intelligence.

Security is at the foundation of OpenAI's mission to ensure that artificial general intelligence benefits all of humanity. The Security team protects OpenAI's technology, people, and products. We are technical in what we build but are operational in how we do our work, and are committed to supporting all products and research at OpenAI. Our Security team tenets include: prioritizing for impact, enabling researchers, preparing for future transformative technologies, and engaging a robust security culture. As a Security Engineering Manager, you will lead OpenAI engineers and researchers in building transformational and secure AI technologies.

A study has found that OpenAI's GPT-3 is capable of being indistinguishable from a human philosopher. The now infamous GPT-3 is a powerful autoregressive language model that uses deep learning to produce human-like text. Eric Schwitzgebel, Anna Strasser, and Matthew Crosby set out to find out whether GPT-3 can replicate a human philosopher. The team "fine-tuned" GPT-3 based on philosopher Daniel Dennet's corpus. Ten philosophical questions were then posed to both the real Dennet and GPT-3 to see whether the AI could match its renowned human counterpart.

In 1917, Marcel Duchamp submitted a sculpture to the Society of Independent Artists under a false name. Fountain was a urinal, bought from a toilet supplier, with the signature R. Mutt on its side in black paint. Duchamp wanted to see if the society would abide by its promise to accept submissions without censorship or favor. But Duchamp was also looking to broaden the notion of what art is, saying a ready-made object in the right context would qualify. Then, as before, the debate raged about if something mechanically produced – a urinal, or a soup can (albeit hand-painted by Warhol) – counted as art, and what that meant.

When OpenAI announced last week that its art-making AI system DALL-E is now available in beta, the company also gave users lucky enough to get off the waiting list what appeared to be a great gift. "Starting today," the company wrote in a post, "users get full usage rights to commercialize the images they create with DALL-E, including the right to reprint, sell, and merchandise." To be clear, this doesn't mean OpenAI is relinquishing its own right to commercialize images users create using DALL-E. JESSICA RIZZO is is an attorney with the law firm Montgomery McCracken Walker & Rhoads. She writes about art, technology, and the law.