Lifeboat Foundation

Exponential Organizations 2.0: The New Playbook for 10x Growth and Impact — Kindle edition by Ismail, Salim, Diamandis, Peter H., Malone, Michael S., Kurzweil, Ray. Download it once and read it on your Kindle device, PC, phones or tablets. Use features like bookmarks, note taking and highlighting while reading Exponential Organizations 2.0: The New Playbook for 10x Growth and Impact.

Every day, tens of thousands of songs are released. This constant stream of options makes it difficult for streaming services and radio stations to choose which songs to add to playlists. To find the ones that will resonate with a large audience, these services have used human listeners and artificial intelligence. This approach, however, lingering at a 50% accuracy rate, does not reliably predict if songs will become hits.

Now, researchers in the US have used a comprehensive machine learning technique applied to brain responses and were able to predict hit songs with 97% accuracy.

“By applying machine learning to neurophysiologic data, we could almost perfectly identify hit songs,” said Paul Zak, a professor at Claremont Graduate University and senior author of the study published in Frontiers in Artificial Intelligence. “That the neural activity of 33 people can predict if millions of others listened to new songs is quite amazing. Nothing close to this accuracy has ever been shown before.”

Gravitational waves, like the discovery of the Higgs boson in 2012, have made their mark on a decade of extraordinary discoveries in physics. Unlike gravity, which is created when massive objects leave their mark in the fabric of spacetime, gravitational waves are very weak ripples in spacetime that are caused by gravity-accelerated masses.

So far, researchers have been able to detect the gravitational waves produced by the melting together of very heavy objects, such as black holes or neutron stars. When this happens, these echoes from the past reverberate through the whole universe and finally reach Earth, allowing us to piece together what happened millions of light-years ago.

Current gravitational-wave observatories can only detect a few gravitational waves as they cover just a narrow spectrum of the whole range of wavelengths that are emitted. Future gravitational-wave observatories, such as the Einstein Telescope, a CERN-recognized experiment, need to be larger in order to search for a larger bandwidth of gravitational waves that could tell us more about the universe.

The design could overcome one of the key challenges facing electrifying larger planes.

DaveAI, a leading virtual sales experience platform, is thrilled to announce the launch of its innovative 3D visualizer for Hindware, a renowned brand in the world of premium sanitaryware. This deployment sets new standards for the virtual showroom experience, providing Hindware customers with an unparalleled level of interactivity and realism.

DaveAI’s 3D visualizer marks an important step forward in the growth of virtual sales, enabling businesses and customers alike to engage with items in a transformative way. Users may now immerse themselves in a visually spectacular virtual environment, where every product detail is brought to life with incredible precision and lifelike accuracy, thanks to modern technology.

“We are excited to partner with DaveAI and bring the 3D visualizer to our customers” said Nitin Dhingra, CDO & Vice President at Hindware Limited. “This cutting-edge technology brings our extensive collection of quality sanitaryware to life in an entirely new way. Our customers can now explore and personalize imaginary bathroom facilities with unprecedented simplicity and realism. This deployment reflects Hindware’s dedication to providing excellent client experiences while remaining at the forefront of industry innovation. We are enthusiastic about the unlimited possibilities that this collaboration opens up, and are looking forward to seeing our customers interact with our products in this immersive virtual environment.”

Airbnb CEO Brian Chesky isn’t afraid of artificial intelligence displacing jobs. In fact, he thinks it’ll create more of them — particularly in the world of entrepreneurship.

Since ChatGPT started gaining popularity last winter, tech icons from Apple co-founder Steve Wozniak to billionaire entrepreneur Mark Cuban have admitted they’re worried that AI will replace human workers in just about every industry.

Continue reading “A.I. will make having a lucrative side hustle or startup much easier, says Airbnb CEO” »

Rocks and minerals contribute essential raw materials for any civilization, and in a technological society minerals (and the rare elements they contain) are especially sought after. In the past, most discoveries of mineral deposits have resulted from perseverance and luck.

In the last 200 years scientists realized that minerals are not distributed randomly. Many of the over 5,000 different minerals occurring on Earth exist in a so-called paragenesis. A paragenesis is a mineral assemblage formed under specific physico-chemical rules, like a certain chemical composition of the host rock or when the right conditions — like temperature and pressure — are met.

A machine learning model can predict the locations of minerals on Earth — and potentially other planets — by taking advantage of patterns in mineral associations.

Continue reading “How AI Can Help Find New Minerals On Earth And Other Planets” »

Self-driving efforts today focus on particular niches, such as the urban robotaxi, delivery, trucking or freeeway driving. Other than Tesla, most major players don’t have a focus on the general personal robocar — a car which consumers will buy, which will drive them door to door on city streets and most other roads. Tesla is very far behind other teams, and barely counts in the minds of many in the industry, thought it gets the most press. A few startups pursue the full robocar dream, but thinking has changed.

In spite of that perceived dream, that is not what the industry is building, or what it is going to release for some time. It may be some time before you can buy a car for yourself with this ability, not just because it’s hard, but because it’s not where the money is. This has led some people to think that robocars are still very far away, and also to a common perception that the technology is many years behind what people expected. Indeed, some people expected, or at least hoped for, faster timelines, but others did not.

The public has a different perception, in part because of Tesla, but also because of a document written over a decade ago by NHTSA (the federal road safety agency) and now manged by the Society of Automotive Engineers known as “the levels.” This document filled the need for a taxonomy of self-driving, but it was written by non-developers when the technology was immature. As such it’s largely useless and even counterproductive, but people are so hungry for a taxonomy that it still is often referred to. The leading teams (mostly tech companies not auto OEMs) do not use these level or attempt to adhere to them. They are mostly a way to talk about the dwindling role of the human in the operation of a self-driving car, a bit like a document about the role of the horse in the horseless carriage.

Generative AI in supply chains will be able to forecast demand, predict when trucks need maintenance and work out optimal shipping routes, according to analysts.“AI may be able to totally (or nearly) remove all human touchpoints in the supply chain including ‘back office’ tasks,” said Morgan Stanley analysts.

But “Generative AI, in my mind is, once in a lifetime kind of disruption that’s going to happen … so there are going to be losses of jobs in the more traditional setting, but I also believe it’s going to create new jobs like every prior technology disruption has,” said Navneet Kapoor, chief technology and information officer at shipping giant Maersk.

Artificial intelligence is likely… More.

Continue reading “A.I. could ‘remove all human touchpoints’ in supply chains. Here’s what that means” »