After simulating 10 contests, with more than 5,000 participants, AlphaCode has ranks in the top 54%.
Category: robotics/AI – Page 1,748
Motor Trend reimagines the ‘Apple Car,’ sees autonomous rideshare in Apple’s future
American auto magazine Motor Trend is back to rehash its initial predictions for Apple’s yet unannounced “Apple Car”, this time updating it for the “inevitable” autonomous future.
The new report is, once again, a think piece that collates a collection of rumors into Motor Trend’s best guess at what Apple might have in the works.
It doesn’t take long for the publication to reference its first stab at imagining the “Apple Car,” one which wound up being ridiculed for being too “podlike.” Yet, as Motor Trend points out, podlike cars are being developed all over.
Accelerating Growth Using AI — A Look At Complexity And The Metaverse Series 1/5
When I did my doctoral studies I studied a number of growth disciplines in areas like: complexity science, social network science (relationship and collaboration science), system thinking science, information science, and cognitive science. As a result of this knowledge, I learned how to connect business strategy goals using diverse growth strategies and analyze underlying operating systems that were either enabling relationship strength and growth outcomes or creating negative systemic feedback loops that prevented revenue acceleration.
There is a word in the English language seldom used called quaquaversal which means looking in all directions all at once which represents the field of complexity science and is the reality of the executive mindset that needs to operate in the board room and in today’s fast paced world — *what one sees as relevant today may well be obsolete tomorrow.*
This blog series will explore each of these discipline areas and connect real life examples of AI approaches that are enabling growth acceleration techniques using these science and social science techniques. This is the first blog in this five part blog series and will focus on complexity science.
Full Story:
President biden please acknowledge tesla’s EV leadership.
Electreon, Ford Developing In-Road Charging System Near Mobility Tech Hub
Ford Motor Co. is working with Israeli startup Electreon to construct a mile-long road near Detroit’s Michigan Central Terminal that will charge electric vehicles as they travel on it. The pilot program will deploy an inductive in-road charging system in partnership with the Michigan Department of Transportation, the Michigan Office of Future Mobility and Electrification and the Michigan Economic Development Corp. “As we aim to lead the future of mobility and electrification by boosting electric vehicle production and lowering consumer costs, a wireless in-road charging system is the next piece to the puzzle for sustainability,” Michigan Governor Gretchen Whitmer said in a statement. Also supporting the project, which is expected to be operational in 2023, are Next Energy and the Jacobs Engineering Group. Ford purchased the long-abandoned train station and is converting it to be the hub of what it calls its “mobility innovation district,” where software developers and others will focus on making electrified and autonomous transportation more practical.
Full Story:
Chip designer mimicking brain, backed by Sam Altman, gets $25 million funding
(Reuters) — Rain Neuromorphics Inc., a startup designing chips that mimic the way the brain works and aims to serve companies using artificial intelligence (AI) algorithms, said on Wednesday it raised $25 million.
Gordon Wilson, CEO and co-founder of Rain, said that while most AI chips on the market today are digital, his company’s technology is analogue. Digital chips read 1s and 0s while analogue chips can decipher incremental information such as sound waves.
Retracted coronavirus (COVID-19) papers
Omuterema AkhahendaAdmin.
🤔 if it is Optimus, can I buy it with Amazon Prime.
Wojtek TekOmuterema Akhahenda free delivery.
Alan LightAdmin.
More than just free delivery: self-delivery.
We should really come up with a new term for an autonomous robot that delivers itself this way. Probably some combination of the terms “auto” (for “self”) and “bot”.… See more.
Ron FriedmanJust when I thought I have enough Tesla stocks, it looks like I’ll buy more.
Image De-noising Using Deep Learning
Denoising an image is a classical problem that researchers are trying to solve for decades. In earlier times, researchers used filters to reduce the noise in the images. They used to work fairly well for images with a reasonable level of noise. However, applying those filters would add a blur to the image. And if the image is too noisy, then the resultant image would be so blurry that most of the critical details in the image are lost.
There has to be a better way to solve this problem. As a result, I have implemented several deep learning architectures that far surpass the traditional denoising filters. In this blog, I will explain my approach step-by-step as a case study, starting from the problem formulation to implementing the state-of-the-art deep learning models, and then finally see the results.
This AI Learned the Design of a Million Algorithms to Help Build New AIs Faster
Might there be a better way? Perhaps.
A new paper published on the preprint server arXiv describes how a type of algorithm called a “hypernetwork” could make the training process much more efficient. The hypernetwork in the study learned the internal connections (or parameters) of a million example algorithms so it could pre-configure the parameters of new, untrained algorithms.
The AI, called GHN-2, can predict and set the parameters of an untrained neural network in a fraction of a second. And in most cases, the algorithms using GHN-2’s parameters performed as well as algorithms that had cycled through thousands of rounds of training.