Lifeboat Foundation

It’s an evolutionary simplification of the larynx.

A so-called evolutionary simplification of the larynx led to human speech. This trait is still present today. Researchers are unsure at what point in history it evolved.

Scientists have spotted the evolutionary modifications in the voice box that make humans able to speak compared to other primates. They did this through an examination of the voice box, or larynx, in 43 species of primates.

Continue reading “Scientists identify what makes humans able to speak compared to other primates” »

Circa 2010 face_with_colon_three

http://www.ted.com Stephen Wolfram, creator of Mathematica, talks about his quest to make all knowledge computational — able to be searched, processed and manipulated. His new search engine, Wolfram Alpha, has no lesser goal than to model and explain the physics underlying the universe.

Continue reading “Computing a theory of everything | Stephen Wolfram” »

A potentially better way to make oxygen for astronauts in space using magnetism has been proposed by an international team of scientists, including a University of Warwick chemist.

The conclusion is from new research on magnetic phase separation in microgravity published in npj Microgravity by researchers from the University of Warwick in the United Kingdom, University of Colorado Boulder and Freie Universität Berlin in Germany.

Keeping astronauts breathing aboard the International Space Station and other space vehicles is a complicated and costly process. As humans plan future missions to the Moon or Mars better technology will be needed.

Circa 2017 Basically this not about cheating but artificial intelligence helping students with their homework with perfect accuracy which is monumental.

Teachers are being forced to adapt to Wolfram Alpha, which executes homework perfectly and whose use almost impossible to detect.

The unusual chemistry of the lava burbling to the island’s surface has raised many questions about what’s churning deep below.

Capturing details of faraway members of our universe is an understandably complicated affair, but translating these details into the stunning space images that we see from space agencies around the world is equally difficult. It is here that supercomputers step in, helping process the massive amounts of data that are captured by terrestrial and space telescopes. On August 11, that is exactly what Australia’s upcoming supercomputer, called Setonix, helped achieve.

Capturing details of faraway members of our universe is an understandably complicated affair, but translating these details into the stunning space images that we see from space agencies around the world is equally difficult. It is here that supercomputers step in, helping process the massive amounts of data that are captured by terrestrial and space telescopes. On August 11, that is exactly what Australia’s upcoming supercomputer, called Setonix, helped achieve.

As its first project, Setonix processed the image of a dying supernova — the last stages of a dying star — from data sent to it by the Australian Square Kilometer Array Pathfinder (Askap). The latter is a terrestrial radio telescope, which has 36 individual antennas working together to capture radio frequency data about objects that are far away in space.

Such data contains intricate details about the object being observed. This not only increases the volume of the data being captured by the telescope, but also puts increasing pressure on a supercomputer to process it into a composite image.

Apple is set to expand ads to new areas of your iPhone and iPad in search of its next big revenue driver. Also: The company slows its pace of acquiring startups, and Peloton embarks on a major overhaul.

Last week in Power On: Apple’s delay of iPadOS 16 and Stage Manager keeps the focus on the iPhone 14.

“We are aiming to provide capabilities in the tens to hundreds of milliwatts range, depending on the use case,” Makhijani said.

Compared to the first–gen chip GrAI One, the third–gen GrAI VIP is slightly physically smaller at 7.6 × 7.6 mm, but the company has skipped a process node and migrated to TSMC 12 nm. The chip has slightly fewer neuron cores, 144 compared to 196, but each core is bigger. The result is a jump from 200,000 neuron cores (250,000 parameters) to around 18 million neurons for a total of 48 million parameters. On–chip memory has jumped from 4 MB to 36 MB.

An M.2 hardware development kit featuring GrAI VIP is available now, shipping with GrAI Matter’s GrAI Flow software stack and model zoo for image classification, object detection, and image segmentation.