Humans snapping photos of themselves with melting skin, blood smeared faces and mutated bodies, while standing in front of a world that is burning is what the DALL-E AI believes will be the last selfies taken at the end of times. DALL-E AI, developed by OpenAI, is a new system that can produce full images when fed natural language descriptions and TikToker Robot Overlords simply asked it to'show the last selfie ever taken.' The nightmarish results each show a human holding a phone and behind them are scenes of bombs dropping, colossal tornados and cities on fire, along with zombies standing in the middle of the destruction. One of the selfies is a animated image of a man wearing what looks like riot gear. He slowly moves his head around with a look as if his life is flashing before his eyes while bombs fall from the sky around him.

We know Dall-E and Midjourney can create some truly compelling images from a bit of text, but do they owe a debt to all of the images that they were trained on? Also, we explore the sorry state of Meta and Cherlynn gushes about the new Pixel Buds Pro. Stay tuned to the end of the show for our chat with Joshua Stiksma, Design Director of Moss 2, who discusses the current state of VR game development. Listen above, or subscribe on your podcast app of choice. If you've got suggestions or topics you'd like covered on the show, be sure to email us or drop a note in the comments!

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.