It could replace cartilage in knees and even help create soft robots 🤯
Is it a bird? Is it a plane? No, it’s ‘super jelly’ — a bizarre new material that can survive being run over by a car even though it’s composed of 80 per cent water.
The ‘glass-like hydrogel’ may look and feel like a squishy jelly, but when compressed it acts like shatterproof glass, its University of Cambridge developers said.
It is formed using a network of polymers held together by a series of reversible chemical interactions that can be tailored to control the gel’s mechanical properties.
I continue to introduce you to a series of articles on the nature of human intelligence and the future of artificial intelligence systems. In the previous article “Artificial intelligence vs neurophysiology: Why the difference matters” we found out that the basis of the work of any biological nervous system is not a computational function (like in a computer), but a reflex or a prepared answer.
But how then did our intelligence come about? How did a biological system repeating pre-prepared reactions become a powerful creative machine?
In this article, we will answer this question in the language of facts. Creating our intelligence, nature has found a simple and at the same time ingenious solution, which is not devoid of a great mystery, which we will also touch.
Nvidia deep learning technologies continue to do wonderful and weird things. Just a few weeks ago we saw how the company can use AI to automatically match voice lines to 3D animated faces. This cool kind of tech that can help people create great things with ease, or in the case of Nvidia’s latest unveiling, potentially horrible things, but still with ease.
We first saw Nvidia’s GauGAN a few years back. It was demonstrated to turn basic doodles into photorealistic images with a click of a few buttons. It’s pretty neat stuff, and definitely worth playing with. Now GuaGAN2 is out and it doesn’t even need your sketches to make highly detailed landscape images.
See customers interact with a second example of Project Tokkio, a Maxine-powered AI talking kiosk. This reference application leverages NVIDIA Metropolis vision AI and Riva speech #AI technology to communicate with the user. It uses NVIDIA’s Megatron-Turing NLG 530B, a state-of-the-art language model for understanding intent and NVIDIA Merlin to make meaningful recommendations. The 3D avatar is animated and visualized with NVIDIA Omniverse to deliver a visually stunning experience—all in real time.
It’s almost Time to use our AI Brothers to search for and Welcome our Space Brothers. Welcome AI and Space friends.
The best public policy is shaped by scientific evidence. Although obvious in retrospect, scientists often fail to follow this dictum. The refusal to admit anomalies as evidence that our knowledge base may have missed something important about reality stems from our ego. However, what will happen when artificial intelligence plays a starring role in the analysis of data? Will these future ‘AI-scientists’ alter the way information is processed and understood, all without human bias?
The mainstream of physics routinely embarks on speculations. For example, we invested 7.5 billion Euros in the Large Hadron Collider with the hope of finding Supersymmetry 0, without success. We invested hundreds of millions of dollars in the search for Weakly Interacting Massive Particles (WIMPs) as dark matter 0, and four decades later, we have been unsuccessful. In retrospect, these were searches in the dark. But one wonders why they were endorsed by the mainstream scientific community while less speculative searches are not?
Consider, for example, the search for equipment in space from extraterrestrial civilizations. Our own civilization launched five interstellar probes. Moreover, the Kepler satellite data revealed that a substantial fraction of all Sun-like stars have an Earth-sized planet at the same separation. Given that most stars formed billions of years before the Sun, imagining numerous extraterrestrial probes floating in interstellar space should not be regarded as more speculative than the notions of Supersymmetry or WIMPs.
Architecture and construction have always been, rather quietly, at the bleeding edge of tech and materials trends. It’s no surprise, then, especially at a renowned technical university like ETH Zurich, to find a project utilizing AI and robotics in a new approach to these arts. The automated design and construction they are experimenting with show how homes and offices might be built a decade from now.
The project is a sort of huge sculptural planter, “hanging gardens” inspired by the legendary structures in the ancient city of Babylon. (Incidentally, it was my ancestor, Robert Koldewey, who excavated/looted the famous Ishtar Gate to the place.)
Begun in 2019, Semiramis (named after the queen of Babylon back then) is a collaboration between human and AI designers. The general idea of course came from the creative minds of its creators, architecture professors Fabio Gramazio and Matthias Kohler. But the design was achieved by putting the basic requirements, such as size, the necessity of watering and the style of construction, through a set of computer models and machine learning algorithms.
In this DNA factory, organism engineers are using robots and automation to build completely new forms of life. »Subscribe to Seeker! http://bit.ly/subscribeseeker. »Watch more Focal Point | https://bit.ly/2M3gmbK
Ginkgo Bioworks, a Boston company specializing in “engineering custom organisms,” aims to reinvent manufacturing, agriculture, biodesign, and more.
Biologists, software engineers, and automated robots are working side by side to accelerate the speed of nature by taking synthetic DNA, remixing it, and programming microbes, turning custom organisms into mini-factories that could one day pump out new foods, fuels, and medicines.
While there are possibly numerous positive and exciting outcomes from this research, like engineering gut bacteria to produce drugs inside the human body on demand or building self-fertilizing plants, the threat of potential DNA sequences harnessing a pathological function still exists.
That’s why Ginkgo Bioworks is developing a malware software to effectively stomp out the global threat of biological weapons, ensuring that synthetic biology can’t be used for evil.
Learn more about synthetic DNA and this biological assembly line on this episode of Focal Point.
NASA’s Curiosity rover has marked the 10th anniversary of its launch to Mars by sending back a spectacular ‘picture postcard’ from the Red Planet.
The robotic explorer snapped two black and white images of the Martian landscape which were then combined and had colour added to them to produce the remarkable composite.
Curiosity, which launched to the Red Planet almost exactly 10 years ago on November 26, 2011, took the pictures from its most recent perch on the side of Mars’ Mount Sharp.
In recent years, many frameworks and guidelines have been created that identify objectives and priorities for ethical AI.
This is certainly a step in the right direction. But it’s also critical to look beyond technical solutions when addressing issues of bias or inclusivity. Biases can enter at the level of who frames the objectives and balances the priorities.
In a recent paper, we argue that inclusivity and diversity also need to be at the level of identifying values and defining frameworks of what counts as ethical AI in the first place. This is especially pertinent when considering the growth of AI research and machine learning across the African continent.
Tutel is a high-performance MoE library developed by Microsoft researchers to aid in the development of large-scale DNN (Deep Neural Network) models; Tutel is highly optimized for the new Azure NDm A100 v4 series, and Tutel’s diverse and flexible MoE algorithmic support allows developers across AI domains to execute MoE more easily and efficiently. Tutel achieves an 8.49x speedup on an NDm A100 v4 node with 8 GPUs and a 2.75x speedup on 64 NDm A100 v4 nodes with 512 A100 GPUs compared to state-of-the-art MoE implementations like Meta’s Facebook AI Research Sequence-to-Sequence Toolkit (fairseq) in PyTorch for a single MoE layer.
Tutel delivers a more than 40% speedup for Meta’s 1.1 trillion–parameter MoE language model with 64 NDm A100 v4 nodes for end-to-end performance, thanks to optimization for all-to-all communication. When working on the Azure NDm A100 v4 cluster, Tutel delivers exceptional compatibility and comprehensive capabilities to assure outstanding performance. Tutel is free and open-source software that has been integrated into fairseq.
Tutel is a high-level MoE solution that complements existing high-level MoE solutions like fairseq and FastMoE by focusing on the optimizations of MoE-specific computation and all-to-all communication and other diverse and flexible algorithmic MoE supports. Tutel features a straightforward user interface that makes it simple to combine with other MoE systems. Developers can also use the Tutel interface to include independent MoE layers into their own DNN models from the ground up, taking advantage of the highly optimized state-of-the-art MoE features right away.
