Lifeboat Foundation

Meta, formerly known as Facebook, today showed off a prototype of an AI system that enables people to generate or import things into a virtual world just by using voice commands. The company sees the tool, which is called “Builder Bot,” as an “exploratory concept” that shows AI’s potential for creating new worlds in the metaverse. Meta CEO Mark Zuckerberg showed off the prototype at the Meta AI: Inside the Lab event on Wednesday in a pre-recorded demo video.

In the video, Zuckerberg explained the process of building parts of a virtual world by describing them. He begins with the prompt, “let’s go to a park.” The bot then creates a 3D landscape of a park with green grass and trees. Zuckerberg then says “actually, let’s go to the beach,” after which the bot replaces the current landscape with a new one of sand and water. He then says he wants to add clouds and notes that everything is AI-generated. Zuckerberg then changes up the landscape by saying he’d rather have altocumulus clouds, which is meant to demonstrate how specific the voice commands can be.

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The current media environment is filled with visual effects and video editing. As a result, as video-centric platforms have gained popularity, demand for more user-friendly and effective video editing tools has skyrocketed. However, because video data is temporal, editing in the format is still difficult and time-consuming. Modern machine learning models have shown considerable promise in enhancing editing, although techniques frequently compromise spatial detail and temporal consistency. The emergence of potent diffusion models trained on huge datasets recently caused a sharp increase in the quality and popularity of generative techniques for picture synthesis. Simple users may produce detailed pictures using text-conditioned models like DALL-E 2 and Stable Diffusion with only a text prompt as input. Latent diffusion models effectively synthesize pictures in a perceptually constrained environment. They research generative models suitable for interactive applications in video editing due to the development of diffusion models in picture synthesis. Current techniques either propagate adjustments using methodologies that calculate direct correspondences or, by finetuning on each unique video, re-pose existing picture models.

They try to avoid costly per-movie training and correspondence calculations for quick inference for every video. They suggest a content-aware video diffusion model with a configurable structure trained on a sizable dataset of paired text-image data and uncaptioned movies. They use monocular depth estimations to represent structure and pre-trained neural networks to anticipate embeddings to represent content. Their method gives several potent controls on the creative process. They first train their model, much like image synthesis models, so the inferred films’ content, such as their look or style, correspond to user-provided pictures or text cues (Fig. 1).

Figure 1: Video Synthesis With Guidance We introduce a method based on latent video diffusion models that synthesises videos (top and bottom) directed by text-or image-described content while preserving the original video’s structure (middle).

In Celebration of the Recent 20-Year Anniversary of Snapple’s Real Facts®, Snapple is Putting its Fact Writing into Fans’ Hands.

FRISCO, Texas, Feb. 8, 2023 /PRNewswire/ — Snapple®, the iconic beverage brand that delivers fun and flavorful teas and juice drinks, is proud to announce the launch of the Snapple fAIct Generator, an AI-powered tool that makes it easy to create facts about any topic. Celebrating 20-years of Snapple Real Facts®, facts found under every Snapple bottle cap, the Snapple fAIct Generator puts fact-creation in the hands of the brand’s fans. To help share the news of this new tool, Snapple used ChatGPT to write this press release, with some light edits to make it more Snapple-y.

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They also detected Celtic fields, charcoal kilns, and cart tracks.

Min Chen, February 10, 2023.

Lurking inside your next gadget may be a chip unlike those of the past. People used to do all the complex silicon design work, but for the first time, AI is helping to build new chips for data centers, smartphones, and IoT devices. AI firm Synopsys has announced that its DSO.ai tool has successfully aided in the design of 100 chips, and it expects that upward trend to continue.

Companies like STMicroelectronics and SK Hynix have turned to Synopsys to accelerate semiconductor designs in an increasingly competitive environment. The past few years have seen demand for new chips increase while materials and costs have rocketed upward. Therefore, companies are looking for ways to get more done with less, and that’s what tools like DSO.ai are all about.

The tool can search design spaces, telling its human masters how best to arrange components to optimize power, performance, and area, or PPA as it’s often called. Among those 100 AI-assisted chip designs, companies have seen up to a 25% drop in power requirements and a 3x productivity increase for engineers. SK Hynix says a recent DSO.ai project resulted in a 15% cell area reduction and a 5% die shrink.

Deciphering the behavior of cephalopods can be messy.

The purpose of such an elaborate structure remains a big open question.

There’s a lot about ecology in frank Herbert’s dune saga and eco mysticism as well.

I will never make any money from Youtube and that is perfectly correct!
I will always get this message: “Your video is ineligible for monetization due to a copyright claim.“
And: “Ad revenue paid to copyright owner”

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