Lifeboat Foundation

Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory have developed a new computational model of a neural circuit in the brain, which could shed light on the biological role of inhibitory neurons — neurons that keep other neurons from firing.

The model describes a neural circuit consisting of an array of input neurons and an equivalent number of output neurons. The circuit performs what neuroscientists call a “winner-take-all” operation, in which signals from multiple input neurons induce a signal in just one output neuron.

Using the tools of theoretical computer science, the researchers prove that, within the context of their model, a certain configuration of inhibitory neurons provides the most efficient means of enacting a winner-take-all operation. Because the model makes empirical predictions about the behavior of inhibitory neurons in the brain, it offers a good example of the way in which computational analysis could aid neuroscience.

Scientists identify the physical connection through which the prefrontal cortex inhibits instinctive behavior

From fighting the urge to hit someone to resisting the temptation to run off stage instead of giving that public speech, we are often confronted with situations where we have to curb our instincts. Scientists at the European Molecular Biology Laboratory (EMBL) have traced exactly which neuronal projections prevent social animals like us from acting out such impulses. The study, published in Nature Neuroscience, could have implications for schizophrenia and mood disorders like depression.

Continue reading “Neural connection keeps instincts in check” »

What happens when you have Deep Learning begin to generate your designs? The commons misconception would be that a machine’s design would look ‘mechanical’ or ‘logical’. However, what we seem to be finding is that they look very organic, in fact they look organic or like an alien biology. Take a look at some of these fascinating designs.

The photo above design is described as follows:

“This is not only an exciting development for the construction sector, but many other industries as well. In the case of this particular piece, the height is approximately half that of one designed for traditional production methods, while the direct weight reduction per node is 75%. On a construction project that means we could be looking at an overall weight reduction of the total structure of more than 40%. But the really exciting part is that this technique can potentially be applied to any industry that uses complex, high quality, metal products.”

Continue reading “The Alien Style of Deep Learning Generative Design” »

In Brief

• Peter Diamandis, founder and chairman of the XPRIZE Foundation, thinks the human species is headed for an evolutionary transformation.
• The evolution of life has slowly unfolded over 3.5 billion years; but its pace has rapidly increased in recent years. Diamandis believes this heralds the next, exciting stages of human evolution.

In the next 30 years, humanity is in for a transformation the likes of which we’ve never seen before—and XPRIZE Foundation founder and chairman Peter Diamandis believes that this will give birth to a new species. Diamandis admits that this might sound too far out there for most people. He is convinced, however, that we are evolving towards what he calls “meta-intelligence,” and today’s exponential rate of growth is one clear indication.

In an essay for Singularity Hub, Diamandis outlines the transformative stages in the multi-billion year pageant of evolution, and takes note of what the recent increasing “temperature” of evolution—a consequence of human activity—may mean for the future. The story, in a nutshell, is this—early prokaryotic life appears about 3.5 billion years ago (bya), representing perhaps a symbiosis of separate metabolic and replicative mechanisms of “life;” at 2.5 bya, eukaryotes emerge as composite organisms incorporating biological “technology” (other living things) within themselves; at 1.5 bya, multicellular metazoans appear as eukaryotes are yoked together in cooperative colonies; and at 400 million years ago, vertebrate fish species emerge onto land to begin life’s adventure beyond the seas.

Continue reading “Peter Diamandis Thinks We’re Evolving Toward ‘Meta-Intelligence’” »

https://www.youtube.com/watch?v=iLr7E2Ms4Y4

“I’m a political theory researcher at Sciences Po, and this talk draws on modern political theories of liberalism, the latest transhumanist literature, and ancient Greek theories of the good life.”

The Transhumanist Paradox.

Continue reading “The Transhumanist Paradox [33c3]” »

Amino is a bioengineering platform that allows anyone to learn and create with synthetic biology and bioengineering, at home, school or in the lab!

Find us on Indiegogo http://igg.me/at/amino

Nice article raising old concerns and debates on ethics. Synbio like any technology or science can in the wrong hands be used to do anything destructive. Placing standards and laws on such technologies truly does get the law abiding researchers, labs and companies aligned and sadly restricted. However, it does not prevent an ISIS, or the black market, or any other criminal with money from trying to meet an intended goal. So, I do caution folks to at least step back assess and think before imposing a bunch of restrictions and laws on a technology that prevents it from helping those in need v. criminals who never follow ethics or the law.

When artists use synthetic biology, are they playing God, or just playing with cool new toys? Scientists Drew Endy and Christina Agapakis weigh in on the ethics.

Biology and technology are moving closer and experts are wondering if this poses a new security threat.

Constructing gene circuits that satisfy quantitative performance criteria has been a long‐standing challenge in synthetic biology. Here, we show a strategy for optimizing a complex three‐gene circuit, a novel proportional miRNA biosensor, using predictive modeling to initiate a search in the phase space of sensor genetic composition. We generate a library of sensor circuits using diverse genetic building blocks in order to access favorable parameter combinations and uncover specific genetic compositions with greatly improved dynamic range. The combination of high‐throughput screening data and the data obtained from detailed mechanistic interrogation of a small number of sensors was used to validate the model. The validated model facilitated further experimentation, including biosensor reprogramming and biosensor integration into larger networks, enabling in principle arbitrary logic with miRNA inputs using normal form circuits. The study reveals how model‐guided generation of genetic diversity followed by screening and model validation can be successfully applied to optimize performance of complex gene networks without extensive prior knowledge.