Lifeboat Foundation: Safeguarding Humanity
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Dr. Hébert will be in Berlin to provide an update on his fascinating work. The use of stem cells to repair the brain is relatively straightforward for Parkinson’s disease, in which cell depletion is localized to one small region, but in Alzheimer’s disease and other conditions, the cell loss is widely distributed, whereas cells can only be injected into one spot. The solution that Dr. Hébert explores is to make those cells migrate before dividing and differentiating.

https://www.undoing-aging.org/dr-jean-hebert-to-speak-at-undoing-aging-2018

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Max Tegmark’s Life 3.0 tries to rectify the situation. Written in an accessible and engaging style, and aimed at the general public, the book offers a political and philosophical map of the promises and perils of the AI revolution. Instead of pushing any one agenda or prediction, Tegmark seeks to cover as much ground as possible, reviewing a wide variety of scenarios concerning the impact of AI on the job market, warfare and political systems.

Yuval Noah Harari responds to an account of the artificial intelligence era and argues we are profoundly ill-prepared to deal with future technology.

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‘UN diplomats confirmed that the new email release would worsen the “bad name” of gene drives in some circles. “Many countries [will] have concerns when this technology comes from DARPA, a US military science agency,” one said.‘.

Cutting-edge gene editing tools such as Crispr-Cas9 work by using a synthetic ribonucleic acid (RNA) to cut into DNA strands and then insert, alter or remove targeted traits. These might, for example, distort the sex-ratio of mosquitoes to effectively wipe out malarial populations.

Some UN experts, though, worry about unintended consequences. One told the Guardian: “You may be able to remove viruses or the entire mosquito population, but that may also have downstream ecological effects on species that depend on them.”

“My main worry,” he added, “is that we do something irreversible to the environment, despite our good intentions, before we fully appreciate the way that this technology will work.”

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Of course, it’s not actually all that doom and gloom, the child AI is really only capable of a specific task – image recognition. Using its AutoML AI, Google’s AI-building AI created its child AI using a technique called reinforcement learning. This works just like machine learning, except it’s entirely automated where AutoML acts as the neural network for its task-driven AI child.

Known as NASNet, the child AI was tasked with recognising objects in a video, in real time. AutoML would then evaluate how good NASNet was at its task and then improve its algorithms using the data to create a superior version of NASNet.

READ NEXT: Watching an AI create fake celebrity faces is nightmare fuel.

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