Lifeboat Foundation

Researchers at Heidelberg University and University of Bern have recently devised a technique to achieve fast and energy-efficient computing using spiking neuromorphic substrates. This strategy, introduced in a paper published in Nature Machine Intelligence, is a rigorous adaptation of a time-to-first-spike (TTFS) coding scheme, together with a corresponding learning rule implemented on certain networks of artificial neurons. TTFS is a time-coding approach, in which the activity of neurons is inversely proportional to their firing delay.

“A few years ago, I started my Master’s thesis in the Electronic Vision(s) group in Heidelberg,” Julian Goeltz, one of the leading researchers working on the study, told TechXplore. “The neuromorphic BrainScaleS system developed there promised to be an intriguing substrate for brain-like computation, given how its neuron and synapse circuits mimic the dynamics of neurons and synapses in the brain.”

When Goeltz started studying in Heidelberg, deep-learning models for spiking networks were still relatively unexplored and existing approaches did not use spike-based communication between neurons very effectively. In 2,017 Hesham Mostafa, a researcher at University of California—San Diego, introduced the idea that the timing of individual neuronal spikes could be used for information processing. However, the neuronal dynamics he outlined in his paper were still quite different from biological ones and thus were not applicable to brain-inspired neuromorphic hardware.

Driving this revolution has been a new breed and wave of founders and startups that merge the worlds of technology and bio — importantly, not just the old world of biotech (or a narrow definition of tech in bio as only “digital health”), but something much broader, bigger, and blending both worlds. In short, biology — enabled by technology — is eating the world. This has not only changed how we diagnose, treat, and manage disease, but has been changing the way we access, pay for, and deliver care in the healthcare system. It is now entering into manufacturing, food, and several other industries as well. Bio is becoming a part of everything.

This new era of industrialized bio — enabled by AI as well as an ongoing, foundational shift in biology from empirical science to more engineered approaches — will be the next industrial revolution in human history. And propelling it forward is an enormous new driving force, the novel coronavirus SARS-CoV-2, its ever-evolving strains, and the resulting COVID-19 disease pandemic and response — which I believe is analogous to our generation’s World War II (WW2). In other words: a massive global upheaval, but that later led to unprecedented innovation and significant new players.

Continue reading “The Coming Age for Tech x Bio: The ‘Industrial Bio Complex’” »

It can be difficult to distinguish between substance and hype in the field of artificial intelligence. In order to stay grounded, it is important to step back from time to time and ask a simple question: what has AI actually accomplished or enabled that makes a difference in the real world?

This summer, DeepMind delivered the strongest answer yet to that question in the decades-long history of AI research: AlphaFold, a software platform that will revolutionize our understanding of biology.

Continue reading “AlphaFold Is The Most Important Achievement In AI —Ever” »

Without a new legal framework, they could destabilize societal norms.

Autonomous weapon systems – commonly known as killer robots – may have killed human beings for the first time ever last year, according to a recent United Nations Security Council report on the Libyan civil war. History could well identify this as the starting point of the next major arms race, one that has the potential to be humanity’s final one.

Autonomous weapon systems are robots with lethal weapons that can operate independently, selecting and attacking targets without a human weighing in on those decisions. Militaries around the world are investing heavily in autonomous weapons research and development. The U.S. alone budgeted US$18 billion for autonomous weapons between 2016 and 2020.

Continue reading “Could Autonomous Robots Be More Dangerous than Nukes?” »

Moving beyond the digital revolution, librarians are now confronting the Fourth Industrial Revolution, thinks Bohyun Kim. She sees the lines between the physical, the digital, and the biological spheres becoming blurred. Implications regarding virtual, augmented, and mixed reality will affect the future of libraries.

Summary: The brain’s reward system plays a key role in helping behaviors and empathy.

Source: Tel Aviv University.

Are mammals at all able to demonstrate empathy for one another, engage in pro-social behavior, and help others in distress? New research from the Tel Aviv University examined the issue based on an animal model (rats) and found that just as with humans, rats are also split into various groups with different indicators, to the point that they only come to the aid of members of their group but do not help rats from other groups.

Like many other living organisms, humans are born, survive, compete for resources, reach maturity, reproduce, take care of their young, sometimes the young of their young, continuously decline, and die. Evolution needs us for just two purposes – adapt and reproduce. But, unlike other species, humans are very conscious of their fate. Humans are very much aware that after reaching peak performance they will eventually grow old and die. We are very conscious of our fate after reaching peak performance – loss of function, frailty, and eventual loss of everything we worked so hard to earn.

We observe our parents, and other elderly around them, attend funerals, and understand that eventually we will get into this state. We are also very contempt with that fate as evolution made sure that. The more ambitious of us are trying to advance science, the rest seek refuge in religion, some in philosophy, some in accumulation of wealth, and some see the continuation of ourselves in our children. But despite the many technological advances transpiring in the laboratories all over the world, there is nothing we can do at this point to escape aging. There are diets, exercises, sleep, and supplements, but these provide very marginal benefits. We do not see 120+ old yoga and diet practitioners or marathon runners around. But these simple habits do help look younger longer. And many people that have very harmful habits like smoking but still diet and exercise to look younger.

Autonomous weapon systems – commonly known as killer robots – may have killed human beings for the first time ever last year, according to a recent United Nations Security Council report on the Libyan civil war. History could well identify this as the starting point of the next major arms race, one that has the potential to be humanity’s final one.

Autonomous weapon systems are robots with lethal weapons that can operate independently, selecting and attacking targets without a human weighing in on those decisions. Militaries around the world are investing heavily in autonomous weapons research and development. The U.S. alone budgeted US$18 billion for autonomous weapons between 2016 and 2020.

Meanwhile, human rights and humanitarian organizations are racing to establish regulations and prohibitions on such weapons development. Without such checks, foreign policy experts warn that disruptive autonomous weapons technologies will dangerously destabilize current nuclear strategies, both because they could radically change perceptions of strategic dominance, increasing the risk of preemptive attacks, and because they could become combined with chemical, biological, radiological and nuclear weapons themselves.

The firm worked with UK weather forecasters to create a model that was better at making short term predictions than existing systems.

First protein folding, now weather forecasting: London-based AI firm DeepMind is continuing its run applying deep learning to hard science problems. Working with the Met Office, the UK’s national weather service, DeepMind has developed a deep-learning tool called DGMR that can accurately predict the likelihood of rain in the next 90 minutes—one of weather forecasting’s toughest challenges.

In a blind comparison with existing tools, several dozen experts judged DGMR’s forecasts to be the best across a range of factors—including its predictions of the location, extent, movement, and intensity of the rain—89% of the time. The results were published in a Nature paper today.

Continue reading “DeepMind’s AI predicts almost exactly when and where it’s going to rain” »