We present CardiacGen, a Deep Learning framework for generating synthetic but physiologically plausible cardiac signals like ECG. Based on the physiology of cardiovascular system function, we propose a modular hierarchical generative model and impose explicit regularizing constraints for training each module using multi-objective loss functions. The model comprises 2 modules, an HRV module focused on producing realistic Heart-Rate-Variability characteristics and a Morphology module focused on generating realistic signal morphologies for different modalities. We empirically show that in addition to having realistic physiological features, the synthetic data from CardiacGen can be used for data augmentation to improve the performance of Deep Learning based classifiers. CardiacGen code is available at https://github.com/SENSE-Lab-OSU/cardiac_gen_model.

Large language and image AI models, sometimes called generative AI or foundation models, have created a new set of opportunities for businesses and professionals that perform content creation. How adept is this technology at mimicking human efforts at creative work? Well, for an example, the italicized text above was written by GPT-3, a "large language model" (LLM) created by OpenAI, in response to the first sentence, which we wrote. GPT-3's text reflects the strengths and weaknesses of most AI-generated content. First, it is sensitive to the prompts fed into it; we tried several alternative prompts before settling on that sentence.

Subscribe to our daily newsletter and have the latest stories from Mission Local delivered directly to your inbox. Tamales sold from roadside carts. When artificial intelligence DALL-E was asked to portray the Mission, these are some of the motifs that were conjured from its digital depths. Tech company OpenAI, which created DALL-E, is based in the Mission on Folsom and 18th Streets. Last weekend, it opened up access to its AI to the general public, allowing anyone and everyone to try out the model.

Generative AI is in a Cambrian explosion of capability.

DeviantArt, the Wix-owned artist community, today announced a new protection for creators to disallow art-generating AI systems from being developed using their artwork. An option on the site will allow artists to preclude third parties from scraping their content for AI development purposes, aiming to prevent work from being swept up without artists' knowledge or permission. "AI technology for creation is a powerful force we can't ignore. . . . It would be impossible for DeviantArt to try to block or censor this art technology," CEO Moti Levy told TechCrunch in an email interview. "We see so many instances where AI tools help artists' creativity, allowing them to express themselves in ways they could not in the past. That said, we believe we have a responsibility to all creators. To support AI art, we must also implement fair tools and add protections in this domain."

Nvidia's eDiffi is a generative AI model for text-to-image and beats alternatives like DALL-E 2 or Stable Diffusion, according to the company. Following OpenAI, Google, Midjourney, and StabilityAI, Nvidia is now showing a generative text-to-image model. All major generative text-to-image models today are diffusion models. Well-known examples are DALL-E 2, Midjourney, Imagen or Stable Diffusion. These models perform image synthesis via an iterative denoising process, the eponymous diffusion. In this way, images are gradually generated from random noise.

There's a great episode of Doctor Who where the stars start vanishing in the sky. This high concept storyline from the sci-fi classic comes to mind when thinking about future disruption to the metaverse should the tech concept ever emerge from its current state of pure fiction and speculation. Take Adobe, a company seen as a leader in the metaverse space through its AR, creative and UX footprint. The brand has taken flack recently from its creative core audience for removing Pantone colors from its flagship Creative Cloud software. To get the color range back, Adobe users will need to pay up or otherwise they'll see black.

Jot automagically generates infinite ad copy variations for you using AI. Streamline your team's copywriting processes with artificial intelligence. Powered by OpenAI GPT-3.

Welcome to Startups Weekly, a nuanced take on this week's startup news and trends. To get this in your inbox, subscribe here. It's Kyle, filling in this issue for Natasha, who's taking a much needed break from the news cycle (and the spectacle that's become Twitter). While it's my first Startups Weekly column, you've likely seen me on TC here and there, covering chiefly venture, AI and enterprise-related items. It's a real pleasure to round up this week's startup news -- partially because it doesn't center around Musk shenanigans.

New users can start creating straight away. Lessons learned from deployment and improvements to our safety systems make wider availability possible. Starting today, we are removing the waitlist for the DALL·E beta so users can sign up and start using it immediately. More than 1.5M users are now actively creating over 2M images a day with DALL·E--from artists and creative directors to authors and architects--with over 100K users sharing their creations and feedback in our Discord community. Responsibly scaling a system as powerful and complex as DALL·E--while learning about all the creative ways it can be used and misused--has required an iterative deployment approach.