1/ Services like HeyGen and arcads.ai let you make “digital avatars” that can talk in sync with their lips, speak different languages, and move and gesture naturally.
2/ The high quality of these AI-made videos makes it hard for even supposed experts to tell fakes from real ones.
Just as AI-generated photos can look very realistic, there are now AI-generated videos that are almost indistinguishable from real video.
AR-Smart glasses: 2029. Will look like just a normal pair of sunglasses. All normal smartphone type features. Built in AI systems. Set up for some VR stuff. An built in earbud / mic, for calls, music, talking to Ai, etc… May need a battery pack, we ll see in 2029.
The smart glasses will soon come with a built-in assistant.
With tech, “things take longer to happen than you think they will, and then they happen faster than you thought they could,” the former Treasury Secretary said Thursday.
Google.org, Google’s charitable wing, is launching a new program to help fund nonprofits developing tech that leverages generative AI.
Called Google.org Accelerator: Generative AI, the program is to be funded by $20 million in grants and include 21 nonprofits to start, including Quill.org, a company creating AI-powered tools for student writing feedback, and World Bank, which is building a generative AI app to make development research more accessible.
In addition to funding, nonprofits in the six-month accelerator program will get access to technical training, workshops, mentors and guidance from an “AI coach.” And, through Google.org’s fellowship program, teams of Google employees will work with three of the nonprofits — Tarjimly, Benefits Data Trust and mRelief — full-time for up to six months to help launch their proposed generative AI tools.
Popular artificial intelligence (AI) powered image generators can run up to 30 times faster thanks to a technique that condenses an entire 100-stage process into one step, new research shows.
Scientists have devised a technique called “distribution matching distillation” (DMD) that teaches new AI models to mimic established image generators, known as diffusion models, such as DALL·E 3, Midjourney and Stable Diffusion.
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A number of companies are racing to make a business on the back of these breakthroughs. Most are figuring out what that business is as they go. “I’ll routinely scream, ‘Holy cow, that is wicked cool’ while playing with these tools,” says Gary Lipkowitz, CEO of Vyond, a firm that provides a point-and-click platform for putting together short animated videos. “But how can you use this at work?”
Whatever the answer to that question, it will probably upend a wide range of businesses and change the roles of many professionals, from animators to advertisers. Fears of misuse are also growing. The widespread ability to generate fake video will make it easier than ever to flood the internet with propaganda and nonconsensual porn. We can see it coming. The problem is, nobody has a good fix.
As we continue to get to grips what’s ahead—good and bad—here are four things to think about. We’ve also curated a selection of the best videos filmmakers have made using this technology, including an exclusive reveal of “Somme Requiem,” an experimental short film by Los Angeles–based production company Myles. Read on for a taste of where AI moviemaking is headed.
Cerebras held an AI Day, and in spite of the concurrently running GTC, there wasn’t an empty seat in the house.
As we have noted, Cerebras Systems is one of the very few startups that is actually getting some serious traction in training AI, at least from a handful of clients. They just introduced the third generation of Wafer-Scale Engines, a monster of a chip that can outperform racks of GPUs, as well as a partnership with Qualcomm to provide custom training and Go-To-Market collaboration with the Edge AI leader. Here’s a few take-aways from the AI Day event. Lots of images from Cerebras, but they tell the story quite well! We will cover the challenges this bold startup still faces in the Conclusions at the end.
As the third generation of wafer-scale engines, the new WSE-3 and the system in which it runs, the CS-3, is an engineering marvel. While Cerebras likes to compare it to a single GPU chip, thats really not the point, which is to simplify scaling. Why cut up a a wafer of chips, package each with HBM, put the package on a board, connect to CPUs with a fabric, then tie them all back together with networking chips and cables? Thats a lot of complexity that leads to a lot of programing to distribute the workload via various forms of parallelism then tie them all back together into a supercomputer. Cerebras thinks it has a better idea.
At a time when other AI assistants and chatbots are also beefing up their own voice interaction capabilities — as OpenAI just did with ChatGPT — Hume AI may have just set a new standard in mind-blowing human-like interactivity, intonation, and speaking qualities.
One obvious potential customer, rival, or would-be acquirer that comes to mind in this case is Amazon, which remains many people’s preferred voice assistant provider through Alexa, but which has since de-emphasized its voice offerings internally and stated it would reduce headcount on that division.
Asked by VentureBeat: “Have you had discussions with or been approached for partnerships/acquisitions by larger entities such as Amazon, Microsoft, etc? I could imagine Amazon in particular being quite interested in this technology as it seems like a vastly improved voice assistant compared to Amazon’s Alexa,” Cowen responded via email: “No comment.”
These two chips might be the key to developing sophisticated brain-computer interfacing.
Scientists from the University of Electronic Science and Technology of China claim to have developed the world’s most energy-efficient artificial intelligence AI microchips that are small enough to fit inside smart devices and could open doors for innovative offline functions like voice and even mind control.
Generally, AI chips that are designed for heavy tasks often require significant power because of high computational demands, which limits their use in real-world scenarios. Professor Zhou Jun and his team managed to significantly reduce power consumption through algorithm and architectural optimization.
