Lifeboat Foundation: Safeguarding Humanity
Toggle light / dark theme

Blog – Page 11109

Read this introductory list of contemporary machine learning algorithms of importance that every engineer should understand.

By James Le, New Story Charity.

Blackboard header

It is no doubt that the sub-field of machine learning / artificial intelligence has increasingly gained more popularity in the past couple of years. As Big Data is the hottest trend in the tech industry at the moment, machine learning is incredibly powerful to make predictions or calculated suggestions based on large amounts of data. Some of the most common examples of machine learning are Netflix’s algorithms to make movie suggestions based on movies you have watched in the past or Amazon’s algorithms that recommend books based on books you have bought before.

Read more

It is not often that a scientist walks the red carpet at a Silicon Valley party and has Morgan Freeman award them millions of dollars while Alicia Keys performs on stage and other A-listers rub shoulders with NASA astronauts.

But the guest list for the Breakthrough prize ceremony is intended to make it an occasion. At the fifth such event in California last night, a handful of the world’s top researchers left their labs behind for the limelight. Honoured for their work on black holes and string theory, DNA repair and rare diseases, and unfathomable modifications to Schrödinger’s equation, they went home to newly recharged bank accounts.

Founded by Yuri Milner, the billionaire tech investor, with Facebook’s Mark Zuckerberg and Google’s Sergey Brin, the Breakthrough prizes aim to right a perceived wrong: that scientists and engineers are not appreciated by society. With lucrative prizes and a lavish party dubbed “the Oscars of science”, Milner and his companions want to elevate scientists to rock star status.

Read more

A brand new type of HIV vaccine will move onto phase II clinical trials in 2017, after phase I trials showed that it was safe to use in humans.

The potential new vaccine will be tested on 600 people in North America, to see how well it can prevent them from getting the virus.

Before we get too excited, the phase I trials were only set up to show that the vaccine was tolerated well by the human body — they didn’t demonstrate if it actually works as a preventative treatment.

Read more

Scientists hoping to get a glimpse of molecules that control brain activity have devised a new probe that allows them to image these molecules without using any chemical or radioactive labels.

Currently the gold standard approach to imaging molecules in the brain is to tag them with radioactive probes. However, these probes offer low resolution and they can’t easily be used to watch dynamic events, says Alan Jasanoff, an MIT professor of biological engineering.

Jasanoff and his colleagues have developed new sensors consisting of proteins designed to detect a particular target, which causes them to dilate blood vessels in the immediate area. This produces a change in blood flow that can be imaged with magnetic resonance imaging (MRI) or other imaging techniques.

Read more

Great.

Research published in Acta Neuropathologica, identified alterations in a protein known as ATRX in human brain tumours; researchers might also be able to target microRNAs directly, altering their levels to make cancer cells less likely to form tumours.

A recent study suggests that two recently discovered genetic differences between brain cancer cells and normal tissue cells could offer clues to tumour behaviour and potential new targets for therapy.

Published in Acta Neuropathologica, the study identified alterations in a protein known as ATRX in human brain tumours that arise as part of a genetically inherited condition known as neurofibromatosis type 1 (NF1). The disorder, marked initially by benign tumours on nerves, often leads to brain cancer, and although most NF1-related malignancies are nonaggressive, a fraction are “high-grade” and difficult to treat, experts say.

Continue reading “Research sets new target for brain cancer therapy” | >

MIT researchers and their colleagues have developed a new computational model of the human brain’s face-recognition mechanism that seems to capture aspects of human neurology that previous models have missed.

The researchers designed a machine-learning system that implemented their model, and they trained it to recognize particular faces by feeding it a battery of sample images. They found that the trained system included an intermediate processing step that represented a face’s degree of rotation — say, 45 degrees from center — but not the direction — left or right.

This property wasn’t built into the system; it emerged spontaneously from the training process. But it duplicates an experimentally observed feature of the primate face-processing mechanism. The researchers consider this an indication that their system and the brain are doing something similar.

Read more

Hmmmm.

Sam Gussman arrived four years ago at Stanford University hoping to eventually parlay an engineering degree into a product manager job at Google or Facebook.

Working for the National Security Agency or other intelligence bureaus never crossed his mind. For Gussman, the government didn’t seem like the place for the most exciting, cutting-edge research in human computer interaction — his area of interest. Plus, it did no on-campus recruiting, unlike the many tech startups that e-mailed him daily about job opportunities and happy hours.

That career plan changed dramatically after Gussman took a new graduate class at Stanford’s engineering school called Hacking for Defense, or H4D, where he got to tackle real-life national security challenges. There he met with U.S. military officers and studied the mental duress soldiers face during combat and then worked on software that distinguishes insurgents from civilians in video feeds from drones. Suddenly government work was “super cool.”

Continue reading “Should tech grads pick defense over Silicon Valley?” | >