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Category: robotics/AI – Page 1,148

Imagine having an autonomous RV.

We all love and dream of having an RV, but having an electric-powered autonomous RV could be the ultimate dream. There are many RV designs on trucks, but having an autonomous truck that drives you anywhere you wish while doing the chores could be the future of both transport and housing.

Based on the specifications Tesla revealed this week and how amazing these renderings of the electric truck as a motorhome appear, the Tesla Semi may become a fantastic electric-powered luxury RV.

Many individuals find the concept of an entirely solar-and electric-powered camper very appealing.

Jowua/Twitter.

There are many RV designs on trucks, but having an autonomous truck that drives you anywhere you wish while doing the chores could be the future of both transport and housing.

Continue reading “A design company has turned a Tesla Semi into an RV concept” | >

Researchers in the field of optical spectrometry have created a better instrument for measuring light. This advancement could improve everything from smartphone cameras to environmental monitoring.

The research, led by Finland’s Aalto University, developed a powerful, incredibly small spectrometer that fits on a microchip and is run by artificial intelligence. Their research was recently published in the journal Science.

The study used a relatively new class of super-thin materials known as two-dimensional semiconductors, and the result is a proof of concept for a spectrometer that could be easily integrated into a number of technologies such as quality inspection platforms, security sensors, biomedical analyzers, and space telescopes.

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Join the audience for a Women in Medical Physics live webinar at 3 p.m. GMT/10 a.m. EST on 14 December 2022 exploring how to begin a new MR-Linac program for MRIdian in your radiation oncology department.

MRIdian is the world’s first radiation therapy system to integrate a diagnostic-quality MRI with an advanced linear accelerator and the only system with MR-guided, real-time, 3D, multiplanar soft-tissue tracking and automated beam control. MRIdian offers precise and personalized care through on-table adaptive treatments without the need for fiducials. The technological foundations of MRIdian allows for the delivery of ablative dose with tighter margins in five or fewer fractions, all while maintaining low to no toxicity. With tens of thousands of patients treated, and an ever-growing body of clinical evidence, MRIdian is leading the MRI-guided revolution in radiation therapy.

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One of the promising technologies being developed for next-generation augmented/virtual reality (AR/VR) systems is holographic image displays that use coherent light illumination to emulate the 3D optical waves representing, for example, the objects within a scene. These holographic image displays can potentially simplify the optical setup of a wearable display, leading to compact and lightweight form factors.

On the other hand, an ideal AR/VR experience requires relatively to be formed within a large field-of-view to match the resolution and the viewing angles of the human eye. However, the capabilities of holographic image projection systems are restricted mainly due to the limited number of independently controllable pixels in existing image projectors and spatial light modulators.

A recent study published in Science Advances reported a deep learning-designed transmissive material that can project super-resolved images using low-resolution image displays. In their paper titled “Super-resolution image display using diffractive decoders,” UCLA researchers, led by Professor Aydogan Ozcan, used deep learning to spatially-engineer transmissive diffractive layers at the wavelength scale, and created a material-based physical image decoder that achieves super-resolution image projection as the light is transmitted through its layers.

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When trying to make a purchase with a shopping app, we may quickly browse the recommendation list while admitting that the machine does know about us—at least, it is learning to do so. As an effective emerging technology, machine learning (ML) has become pretty much pervasive with an application spectrum ranging from miscellaneous apps to supercomputing.

Dedicated ML computers are thus being developed at various scales, but their productivity is somewhat limited: the workload and development cost are largely concentrated in their software stacks, which need to be developed or reworked on an ad hoc basis to support every scaled model.

To solve the problem, researchers from the Chinese Academy of Sciences (CAS) proposed a parallel computing model and published their research in Intelligent Computing on Sept. 5.

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Professors, programmers and journalists could all be out of a job in just a few years, after the latest chatbot from the Elon Musk-founded OpenAI foundation stunned onlookers with its writing ability, proficiency at complex tasks, and ease of use.

The system, called ChatGPT, is the latest evolution of the GPT family of text-generating AIs. Two years ago, the team’s previous AI, GPT3, was able to generate an opinion piece for the Guardian, and ChatGPT has significant further capabilities.

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Stephen Wolfram is at his jovial peak in this technical interview regarding the Wolfram Physics project (theory of everything).
Sponsors: https://brilliant.org/TOE for 20% off. http://algo.com for supply chain AI.

Link to the Wolfram project: https://www.wolframphysics.org/

Patreon: https://patreon.com/curtjaimungal.
Crypto: https://tinyurl.com/cryptoTOE
PayPal: https://tinyurl.com/paypalTOE
Twitter: https://twitter.com/TOEwithCurt.
Discord Invite: https://discord.com/invite/kBcnfNVwqs.
iTunes: https://podcasts.apple.com/ca/podcast/better-left-unsaid-wit…1521758802
Pandora: https://pdora.co/33b9lfP
Spotify: https://open.spotify.com/show/4gL14b92xAErofYQA7bU4e.
Subreddit r/TheoriesOfEverything: https://reddit.com/r/theoriesofeverything.
Merch: https://tinyurl.com/TOEmerch.

TIMESTAMPS:
00:00:00 Introduction.
00:02:26 Behind the scenes.
00:04:00 Wolfram critiques are from people who haven’t read the papers (generally)
00:10:39 The Wolfram Model (Theory of Everything) overview in under 20 minutes.
00:29:35 Causal graph vs. multiway graph.
00:39:42 Global confluence and causal invariance.
00:44:06 Rulial space.
00:49:05 How to build your own Theory of Everything.
00:54:00 Computational reducibility and irreducibility.
00:59:14 Speaking to aliens / communication with other life forms.
01:06:06 Extra-terrestrials could be all around us, and we’d never see it.
01:10:03 Is the universe conscious? What is “intelligence”?
01:13:03 Do photons experience time? (in the Wolfram model)
01:15:07 “Speed of light” in rulial space.
01:16:37 Principle of computational equivalence.
01:21:13 Irreducibility vs undecidability and computational equivalence.
01:23:47 Is infinity “real”?
01:28:08 Discrete vs continuous space.
01:33:40 Testing discrete space with the cosmic background radiation (CMB)
01:34:35 Multiple dimensions of time.
01:36:12 Defining “beauty” in mathematics, as geodesics in proof space.
01:37:29 Particles are “black holes” in branchial space.
01:39:44 New Feynman stories about his abjuring of woo woo.
01:43:52 Holographic principle / AdS CFT correspondence, and particles as black holes.
01:46:38 Wolfram’s view on cryptocurrencies, and how his company trades in crypto [Amjad Hussain]
01:57:38 Einstein field equations in economics.
02:03:04 How to revolutionize a field of study as a beginner.
02:04:50 Bonus section of Curt’s thoughts and questions.

Just wrapped (April 2021) a documentary called Better Left Unsaid http://betterleftunsaidfilm.com on the topic of “when does the left go too far?” Visit that site if you’d like to watch it.

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