Lifeboat Foundation

This transformer robot can stand on two legs and navigate a staircase. Its developers expect it to be a key member of rescue teams by 2030.

The next breakthrough to take the AI world by storm might be 3D model generators. This week, OpenAI open sourced Point-E, a machine learning system that creates a 3D object given a text prompt. According to a paper published alongside the code base, Point-E can produce 3D models in one to two minutes on a single Nvidia V100 GPU.

Point-E doesn’t create 3D objects in the traditional sense. Rather, it generates point clouds, or discrete sets of data points in space that represent a 3D shape — hence the cheeky abbreviation. (The “E” in Point-E is short for “efficiency,” because it’s ostensibly faster than previous 3D object generation approaches.) Point clouds are easier to synthesize from a computational standpoint, but they don’t capture an object’s fine-grained shape or texture — a key limitation of Point-E currently.

To get around this limitation, the Point-E team trained an additional AI system to convert Point-E’s point clouds to meshes. (Meshes — the collections of vertices, edges and faces that define an object — are commonly used in 3D modeling and design.) But they note in the paper that the model can sometimes miss certain parts of objects, resulting in blocky or distorted shapes.

You d still have human kitchen staff, but could quietly be automated once tec was ready.

McDonald’s has begun testing its first-ever robot restaurant in Texas, sparking debate and intrigue in equal measure.

In Forth Worth, Texas, the branch is fully automated and requires no human contact to order and pick up your favorite meal.

Continue reading “Welcome to the first ever McDonald’s where you’re served by robots—in Texas” »

Robots and autonomous cars will have eyes that see much more than the human eye is capable of, a review of the growing field of meta-optics has found.

Meta-optics is advancing science and technology far beyond the 3,000-year-old optical paradigm that we rely on for the visual human-machine interface, such as through cameras in our mobile phones, the lenses in microscopes, drones, and telescopes. Optical components are the technology bottleneck that meta-optics aims to transform, bringing the stuff of science-fiction stories into everyday devices.

The field, which blossomed after the early 2000s thanks to the conceptualization of a material with negative refractive index that could form a perfect lens, has grown rapidly in the last five years and now sees around 3,000 publications a year.

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AI art is amazing and is changing the world for the better. In this video, I explain why we should be embracing AI rather than trying to hold it back.

Continue reading “AI Art Is Getting Scary… — YouTube” »

Summary: Using advances in machine learning, researchers have created a new model that predicts the ease with which individuals produce and comprehend complex sentences.

Source: MIT

Cognitive scientists have long sought to understand what makes some sentences more difficult to comprehend than others. Any account of language comprehension, researchers believe, would benefit from understanding difficulties in comprehension.

A talon-like claw with sharp ends and a softer middle helps this flying robot grasp onto thin perches just like a bird.

As we look back at 2022, it’s clear that the field of artificial intelligence (AI) has made some very important strides. From breakthroughs in natural language processing and computer vision to improved adoption of AI by businesses, we’ve seen several milestones.

It’s no doubt that AI will continue its explosive growth into 2023. However, given the rapid pace of change, it’s important to separate meaningful advancements from distracting fads.

What are the top AI trends and fads for 2023? What’s one thing business leaders must stop doing to unlock business value from AI? Hear predictions from 10 experts, including ChatGPT AI!

Continue reading “AI Trends For 2023: Industry Experts (And ChatGPT AI) Make Their Predictions” »

Text-to-image AI exploded this year as technical advances greatly enhanced the fidelity of art that AI systems could create. Controversial as systems like Stable Diffusion and OpenAI’s DALL-E 2 are, platforms including DeviantArt and Canva have adopted them to power creative tools, personalize branding and even ideate new products.

But the tech at the heart of these systems is capable of far more than generating art. Called diffusion, it’s being used by some intrepid research groups to produce music, synthesize DNA sequences and even discover new drugs.

So what is diffusion, exactly, and why is it such a massive leap over the previous state of the art? As the year winds down, it’s worth taking a look at diffusion’s origins and how it advanced over time to become the influential force that it is today. Diffusion’s story isn’t over — refinements on the techniques arrive with each passing month — but the last year or two especially brought remarkable progress.