As we close out 2016, if you’ll allow me, I’d like to take a risk and venture into a topic I’m personally compelled to think about… a topic that will seem far out to most readers.
Today’s extraordinary rate of exponential growth may do much more than just disrupt industries. It may actually give birth to a new species, reinventing humanity over the next 30 years.
I believe we’re rapidly heading towards a human-scale transformation, the next evolutionary step into what I call a “Meta-Intelligence,” a future in which we are all highly connected—brain to brain via the cloud—sharing thoughts, knowledge and actions. In this post, I’m investigating the driving forces behind such an evolutionary step, the historical pattern we are about to repeat, and the implications thereof. Again, I acknowledge that this topic seems far-out, but the forces at play are huge and the implications are vast. Let’s dive in…
A Quick Recap: Evolution of Life on Earth in 4 Steps
About 4.6 billion years ago, our solar system, the sun and the Earth were formed.
Step 1: 3.5 billion years ago, the first simple life forms, called “prokaryotes,” came into existence.These prokaryotes were super-simple, microscopic single-celled organisms, basically a bag of cytoplasm with free-floating DNA. They had neither a distinct nucleus nor specialized organelles.
Step 2: Fast-forwarding one billion years to 2.5 billion years ago, the next step in evolution created what we call “eukaryotes”—life forms that distinguished themselves by incorporating biological ‘technology’ into themselves. Technology that allowed them to manipulate energy (via mitochondria) and information (via chromosomes) far more efficiently. Fast forward another billion years for the next step.
Step 3: 1.5 billion years ago, these early eukaryotes began working collaboratively and formed the first “multi-cellular life,” of which you and I are the ultimate examples (a human is a multicellular creature of 10 trillion cells).
Step 4: The final step I want to highlight happened some 400 million years ago, when lungfish crawled out of the oceans onto the shores, and life evolved from the oceans onto land.
The Next Stages of Human Evolution: 4 Steps
Today, at a massively accelerated rate—some 100 million times faster than the steps I outlined above—life is undergoing a similar evolution. In this next stage of evolution, we are going from evolution by natural selection (Darwinism) to evolution by intelligent direction. Allow me to draw the analogy for you:
Step 1: Simple humans today are analogous to prokaryotes. Simple life, each life form independent of the others, competing and sometimes collaborating.
Step 2: Just as eukaryotes were created by ingesting technology, humans will incorporate technology into our bodies and brains that will allow us to make vastly more efficient use of information (BCI) and energy.
Step 3: Enabled with BCI and AI, humans will become massively connected with each other and billions of AIs (computers) via the cloud, analogous to the first multicellular lifeforms 1.5 billion years ago. Such a massive interconnection will lead to the emergence of a new global consciousness, and a new organism I call the Meta-Intelligence.
Step 4: Finally, humanity is about to crawl out of the gravity well of Earth to become a multiplanetary species. Our journey to the moon, Mars, asteroids and beyond represents the modern-day analogy of the journey made by lungfish climbing out of the oceans some 400 million years ago.
The 4 Forces Driving the Evolution and Transformation of Humanity
Four primary driving forces are leading us towards our transformation of humanity into a meta-intelligence both on and off the Earth:
We’re wiring our planet
Emergence of brain-computer interface
Emergence of AI
Opening of the space frontier
Let’s take a look.
1. Wiring the Planet: Today, there are 2.9 billion people connected online. Within the next six to eight years, that number is expected to increase to nearly 8 billion, with each individual on the planet having access to a megabit-per-second connection or better. The wiring is taking place through the deployment of 5G on the ground, plus networks being deployed by Facebook, Google, Qualcomm, Samsung, Virgin, SpaceX and many others. Within a decade, every single human on the planet will have access to multi-megabit connectivity, the world’s information, and massive computational power on the cloud.
2. Brain-Computer Interface: A multitude of labs and entrepreneurs are working to create lasting, high-bandwidth connections between the digital world and the human neocortex (I wrote about that in detail here). Ray Kurzweil predicts we’ll see human-cloud connection by the mid-2030s, just 18 years from now. In addition, entrepreneurs like Bryan Johnson (and his company Kernel) are committing hundreds of millions of dollars towards this vision. The end results of connecting your neocortex with the cloud are twofold: first, you’ll have the ability to increase your memory capacity and/or cognitive function millions of fold; second, via a global mesh network, you’ll have the ability to connect your brain to anyone else’s brain and to emerging AIs, just like our cell phones, servers, watches, cars and all devices are becoming connected via the Internet of Things.
3. Artificial Intelligence/Human Intelligence: Next, and perhaps most significantly, we are on the cusp of an AI revolution. Artificial intelligence, powered by deep learning and funded by companies such as Google, Facebook, IBM, Samsung and Alibaba, will continue to rapidly accelerate and drive breakthroughs. Cumulative “intelligence” (both artificial and human) is the single greatest predictor of success for both a company or a nation. For this reason, beside the emerging AI “arms race,” we will soon see a race focused on increasing overall human intelligence. Whatever challenges we might have in creating a vibrant brain-computer interface (e.g., designing long-term biocompatible sensors or nanobots that interface with your neocortex), those challenges will fall quickly over the next couple of decades as AI power tools give us ever-increasing problem-solving capability. It is an exponential atop an exponential. More intelligence gives us the tools to solve connectivity and mesh problems and in turn create greater intelligence.
4. Opening the Space Frontier: Finally, it’s important to note that the human race is on the verge of becoming a multiplanetary species. Thousands of years from now, whatever we’ve evolved into, we will look back at these next few decades as the moment in time when the human race moved off Earth irreversibly. Today, billions of dollars are being invested privately into the commercial space industry. Efforts led by SpaceX are targeting humans on Mars, while efforts by Blue Origin are looking at taking humanity back to the moon, and plans by my own company, Planetary Resources, strive to unlock near-infinite resources from the asteroids.
The rate of human evolution is accelerating as we transition from the slow and random process of “Darwinian natural selection” to a hyper-accelerated and precisely-directed period of “evolution by intelligent direction.” In this post, I chose not to discuss the power being unleashed by such gene-editing techniques as CRISPR-Cas9. Consider this yet another tool able to accelerate evolution by our own hand.
The bottom line is that change is coming, faster than ever considered possible. All of us leaders, entrepreneurs and parents have a huge responsibility to inspire and guide the transformation of humanity on and off the Earth. What we do over the next 30 years—the bridges we build to abundance—will impact the future of the human race for millennia to come. We truly live during the most exciting time ever in human history.
An international team of 63 scientists in 14 clinical departments have identified a unique “breathprint” for 17 diseases with 86% accuracy and have designed a noninvasive, inexpensive, and miniaturized portable device that screens breath samples to classify and diagnose several types of diseases, they report in an open-access paper in the journal ACS Nano.
As far back as around 400 B.C., doctors diagnosed some diseases by smelling a patient’s exhaled breath, which contains nitrogen, carbon dioxide, oxygen, and a small amount of more than 100 other volatile chemical components. Relative amounts of these substances vary depending on the state of a person’s health. For example, diabetes creates a sweet breath smell. More recently, several teams of scientists have developed experimental breath analyzers, but most of these instruments focus on one disease, such as diabetes and melanoma, or a few diseases.
Detecting 17 diseases
The researchers developed an array of nanoscale sensors to detect the individual components in thousands of breath samples collected from 1404 patients who were either healthy or had one of 17 different diseases*, such as kidney cancer or Parkinson’s disease.
The team used mass spectrometry to identify the breath components associated with each disease. By analyzing the results with artificial intelligence techniques (binary classifiers), the team found that each disease produces a unique breathprint, based on differing amounts of 13 volatile organic chemical (VOC) components. They also showed that the presence of one disease would not prevent the detection of others — a prerequisite for developing a practical device to screen and diagnose various diseases.
Based on the research, the team designed an organic layer that functions as a sensing layer (recognition element) for adsorbed VOCs and an electrically conductive nanoarray based on resistive layers of molecularly modified gold nanoparticles and a random network of single-wall carbon nanotubes. The nanoparticles and nanotubes have different electrical conductivity patterns associated with different diseases.**
** During exposure to breath samples, interaction between the VOC components and the organic sensing layer changes the electrical resistance of the sensors. The relative change of sensor’s resistance at the peak (beginning), middle, and end of the exposure, as well as the area under the curve of the whole measurement were measured. All breath samples identified by the AI nanoarray were also examined using an independent lab-based analytical technique: gas chromatography linked with mass spectrometry.
Abstract of Diagnosis and Classification of 17 Diseases from 1404 Subjects via Pattern Analysis of Exhaled Molecules
We report on an artificially intelligent nanoarray based on molecularly modified gold nanoparticles and a random network of single-walled carbon nanotubes for noninvasive diagnosis and classification of a number of diseases from exhaled breath. The performance of this artificially intelligent nanoarray was clinically assessed on breath samples collected from 1404 subjects having one of 17 different disease conditions included in the study or having no evidence of any disease (healthy controls). Blind experiments showed that 86% accuracy could be achieved with the artificially intelligent nanoarray, allowing both detection and discrimination between the different disease conditions examined. Analysis of the artificially intelligent nanoarray also showed that each disease has its own unique breathprint, and that the presence of one disease would not screen out others. Cluster analysis showed a reasonable classification power of diseases from the same categories. The effect of confounding clinical and environmental factors on the performance of the nanoarray did not significantly alter the obtained results. The diagnosis and classification power of the nanoarray was also validated by an independent analytical technique, i.e., gas chromatography linked with mass spectrometry. This analysis found that 13 exhaled chemical species, called volatile organic compounds, are associated with certain diseases, and the composition of this assembly of volatile organic compounds differs from one disease to another. Overall, these findings could contribute to one of the most important criteria for successful health intervention in the modern era, viz. easy-to-use, inexpensive (affordable), and miniaturized tools that could also be used for personalized screening, diagnosis, and follow-up of a number of diseases, which can clearly be extended by further development.
The Fourth Industrial Revolution is upon us and now is the time to act.
Everything is changing each day and humans are making decisions that affect life in the future for generations to come.
We have gone from Steam Engines to Steel Mills, to computers to the Fourth Industrial Revolution that involves a digital economy, artificial intelligence, big data and a new system that introduces a new story of our future to enable different economic and human models.
Will the Fourth Industrial Revolution put humans first and empower technologies to give humans a better quality of life with cleaner air, water, food, health, a positive mindset and happiness? HOPE…
Salk Institute researchers have discovered a holy grail of gene editing — the ability to, for the first time, insert DNA at a target location into the non-dividing cells that make up the majority of adult organs and tissues. The technique, which the team showed was able to partially restore visual responses in blind rodents, will open new avenues for basic research and a variety of treatments, such as for retinal, heart and neurological diseases.
“We are very excited by the technology we discovered because it’s something that could not be done before,” says Juan Carlos Izpisua Belmonte, a professor in Salk’s Gene Expression Laboratory and senior author of the paper published on November 16, 2016 in Nature. “For the first time, we can enter into cells that do not divide and modify the DNA at will. The possible applications of this discovery are vast.”
Until now, techniques that modify DNA — such as the CRISPR-Cas9 system — have been most effective in dividing cells, such as those in skin or the gut, using the cells’ normal copying mechanisms. The new Salk technology is ten times more efficient than other methods at incorporating new DNA into cultures of dividing cells, making it a promising tool for both research and medicine. But, more importantly, the Salk technique represents the first time scientists have managed to insert a new gene into a precise DNA location in adult cells that no longer divide, such as those of the eye, brain, pancreas or heart, offering new possibilities for therapeutic applications in these cells.
To achieve this, the Salk researchers targeted a DNA-repair cellular pathway called NHEJ (for “non-homologous end-joining”), which repairs routine DNA breaks by rejoining the original strand ends. They paired this process with existing gene-editing technology to successfully place new DNA into a precise location in non-dividing cells.
“Using this NHEJ pathway to insert entirely new DNA is revolutionary for editing the genome in live adult organisms,” says Keiichiro Suzuki, a senior research associate in the Izpisua Belmonte lab and one of the paper’s lead authors. “No one has done this before.”
First, the Salk team worked on optimizing the NHEJ machinery for use with the CRISPR-Cas9 system, which allows DNA to be inserted at very precise locations within the genome. The team created a custom insertion package made up of a nucleic acid cocktail, which they call HITI, or homology-independent targeted integration. Then they used an inert virus to deliver HITI’s package of genetic instructions to neurons derived from human embryonic stem cells.
“That was the first indication that HITI might work in non-dividing cells,” says Jun Wu, staff scientist and co-lead author. With that feat under their belts, the team then successfully delivered the construct to the brains of adult mice. Finally, to explore the possibility of using HITI for gene-replacement therapy, the team tested the technique on a rat model for retinitis pigmentosa, an inherited retinal degeneration condition that causes blindness in humans. This time, the team used HITI to deliver to the eyes of 3-week-old rats a functional copy of Mertk, one of the genes that is damaged in retinitis pigmentosa. Analysis performed when the rats were 8 weeks old showed that the animals were able to respond to light, and passed several tests indicating healing in their retinal cells.
“We were able to improve the vision of these blind rats,” says co-lead author Reyna Hernandez-Benitez, a Salk research associate. “This early success suggests that this technology is very promising.”
The team’s next steps will be to improve the delivery efficiency of the HITI construct. As with all genome editing technologies, getting enough cells to incorporate the new DNA is a challenge. The beauty of HITI technology is that it is adaptable to any targeted genome engineering system, not just CRISPR-Cas9. Thus, as the safety and efficiency of these systems improve, so too will the usefulness of HITI.
“We now have a technology that allows us to modify the DNA of non-dividing cells, to fix broken genes in the brain, heart and liver,” says Izpisua Belmonte. “It allows us for the first time to be able to dream of curing diseases that we couldn’t before, which is exciting.”
Clinical trial failure rates for small molecules in oncology exceed 94% for molecules previously tested in animals and the costs to bring a new drug to market exceed $2.5 billion
There are around 2,000 drugs approved for therapeutic use by the regulators with very few providing complete cures
Advances in deep learning demonstrated superhuman accuracy in many areas and are expected to transform industries, where large amounts of training data is available
Generative Adversarial Networks (GANs), a new technology introduced in 2014 represent the “cutting edge” in artificial intelligence, where new images, videos and voice can be produced by the deep neural networks on demand
Here for the first time we demonstrate the application of Generative Adversarial Autoencoders (AAEs), a new type of GAN, for generation of molecular fingerprints of molecules that kill cancer cells at specific concentrations
This work is the proof of concept, which opens the door for the cornucopia of meaningful molecular leads created according to the given criteria
The study was published in Oncotarget and the open-access manuscript is available in the Advance Open Publications section
Authors speculate that in 2017 the conservative pharmaceutical industry will experience a transformation similar to the automotive industry with deep learned drug discovery pipelines integrated into the many business processes
The extension of this work will be presented at the “4th Annual R&D Data Intelligence Leaders Forum” in Basel, Switzerland, Jan 24-26th, 2017
Thursday, 22nd of December Baltimore, MD – Scientists at the Pharmaceutical Artificial Intelligence (pharma.AI) group of Insilico Medicine, Inc, today announced the publication of a seminal paper demonstrating the application of generative adversarial autoencoders (AAEs) to generating new molecular fingerprints on demand. The study was published in Oncotarget on 22nd of December, 2016. The study represents the proof of concept for applying Generative Adversarial Networks (GANs) to drug discovery. The authors significantly extended this model to generate new leads according to multiple requested characteristics and plan to launch a comprehensive GAN-based drug discovery engine producing promising therapeutic treatments to significantly accelerate pharmaceutical R&D and improve the success rates in clinical trials.
Since 2010 deep learning systems demonstrated unprecedented results in image, voice and text recognition, in many cases surpassing human accuracy and enabling autonomous driving, automated creation of pleasant art and even composition of pleasant music.
GAN is a fresh direction in deep learning invented by Ian Goodfellow in 2014. In recent years GANs produced extraordinary results in generating meaningful images according to the desired descriptions. Similar principles can be applied to drug discovery and biomarker development. This paper represents a proof of concept of an artificially-intelligent drug discovery engine, where AAEs are used to generate new molecular fingerprints with the desired molecular properties.
“At Insilico Medicine we want to be the supplier of meaningful, high-value drug leads in many disease areas with high probability of passing the Phase I/II clinical trials. While this publication is a proof of concept and only generates the molecular fingerprints with the very basic molecular properties, internally we can now generate entire molecular structures according to a large number of parameters. These structures can be fed into our multi-modal drug discovery pipeline, which predicts therapeutic class, efficacy, side effects and many other parameters. Imagine an intelligent system, which one can instruct to produce a set of molecules with specified properties that kill certain cancer cells at a specified dose in a specific subset of the patient population, then predict the age-adjusted and specific biomarker-adjusted efficacy, predict the adverse effects and evaluate the probability of passing the human clinical trials. This is our big vision”, said Alex Zhavoronkov, PhD, CEO of Insilico Medicine, Inc.
Previously, Insilico Medicine demonstrated the predictive power of its discovery systems in the nutraceutical industry. In 2017 Life Extension will launch a range of natural products developed using Insilico Medicine’s discovery pipelines. Earlier this year the pharmaceutical artificial intelligence division of Insilico Medicine published several seminal proof of concept papers demonstrating the applications of deep learning to drug discovery, biomarker development and aging research. Recently the authors published a tool in Nature Communications, which is used for dimensionality reduction in transcriptomic data for training deep neural networks (DNNs). The paper published in Molecular Pharmaceutics demonstrating the applications of deep neural networks for predicting the therapeutic class of the molecule using the transcriptional response data received the American Chemical Society Editors’ Choice Award. Another paper demonstrating the ability to predict the chronological age of the patient using a simple blood test, published in Aging, became the second most popular paper in the journal’s history.
“Generative AAE is a radically new way to discover drugs according to the required parameters. At Pharma.AI we have a comprehensive drug discovery pipeline with reasonably accurate predictors of efficacy and adverse effects that work on the structural data and transcriptional response data and utilize the advanced signaling pathway activation analysis and deep learning. We use this pipeline to uncover the prospective uses of molecules, where these types of data are available. But the generative models allow us to generate completely new molecular structures that can be run through our pipelines and then tested in vitro and in vivo. And while it is too early to make ostentatious claims before our predictions are validated in vivo, it is clear that generative adversarial networks coupled with the more traditional deep learning tools and biomarkers are likely to transform the way drugs are discovered”, said Alex Aliper, president, European R&D at the Pharma.AI group of Insilico Medicine.
Recent advances in deep learning and specifically in generative adversarial networks have demonstrated surprising results in generating new images and videos upon request, even when using natural language as input. In this study the group developed a 7-layer AAE architecture with the latent middle layer serving as a discriminator. As an input and output AAE uses a vector of binary fingerprints and concentration of the molecule. In the latent layer the group introduced a neuron responsible for tumor growth inhibition index, which when negative it indicates the reduction in the number of tumour cells after the treatment. To train AAE, the authors used the NCI-60 cell line assay data for 6252 compounds profiled on MCF-7 cell line. The output of the AAE was used to screen 72 million compounds in PubChem and select candidate molecules with potential anti-cancer properties.
“I am very happy to work alongside the Pharma.AI scientists at Insilico Medicine on getting the GANs to generate meaningful leads in cancer and, most importantly, age-related diseases and aging itself. This is humanity’s most pressing cause and everyone in machine learning and data science should be contributing. The pipelines these guys are developing will play a transformative role in the pharmaceutical industry and in extending human longevity and we will continue our collaboration and invite other scientists to follow this path”, said Artur Kadurin, the head of the segmentation group at Mail.Ru, one of the largest IT companies in Eastern Europe and the first author on the paper.
About Insilico Medicine, Inc
Insilico Medicine, Inc. is a bioinformatics company located at the Emerging Technology Centers at the Johns Hopkins University Eastern campus in Baltimore with Research and Development (“R&D”) resources in Belgium, UK and Russia hiring talent through hackathons and competitions. The company utilizes advances in genomics, big data analysis, and deep learning for in silico drug discovery and drug repurposing for aging and age-related diseases. The company pursues internal drug discovery programs in cancer, Parkinson’s Disease, Alzheimer’s Disease, sarcopenia, and geroprotector discovery. Through its Pharma.AI division, the company provides advanced machine learning services to biotechnology, pharmaceutical, and skin care companies. Brief company video: https://www.youtube.com/watch?v=l62jlwgL3v8
Sometimes the solution to a problem is staring you in the face all along. Chip maker Intel is betting that will be true in the race to build quantum computers—machines that should offer immense processing power by exploiting the oddities of quantum mechanics.
Competitors IBM, Microsoft, and Google are all developing quantum components that are different from the ones crunching data in today’s computers. But Intel is trying to adapt the workhorse of existing computers, the silicon transistor, for the task.
Intel has a team of quantum hardware engineers in Portland, Oregon, who collaborate with researchers in the Netherlands, at TU Delft’s QuTech quantum research institute, under a $50 million grant established last year. Earlier this month Intel’s group reported that they can now layer the ultra-pure silicon needed for a quantum computer onto the standard wafers used in chip factories.
This strategy makes Intel an outlier among industry and academic groups working on qubits, as the basic components needed for quantum computers are known. Other companies can run code on prototype chips with several qubits made from superconducting circuits (see “Google’s Quantum Dream Machine”). No one has yet advanced silicon qubits that far.
A quantum computer would need to have thousands or millions of qubits to be broadly useful, though. And Jim Clarke, who leads Intel’s project as director of quantum hardware, argues that silicon qubits are more likely to get to that point (although Intel is also doing some research on superconducting qubits). One thing in silicon’s favor, he says: the expertise and equipment used to make conventional chips with billions of identical transistors should allow work on perfecting and scaling up silicon qubits to progress quickly.
Intel’s silicon qubits represent data in a quantum property called the “spin” of a single electron trapped inside a modified version of the transistors in its existing commercial chips. “The hope is that if we make the best transistors, then with a few material and design changes we can make the best qubits,” says Clarke.
The new process that helps Intel experiment with silicon qubits on standard chip wafers, developed with the materials companies Urenco and Air Liquide, should help speed up its research, says Andrew Dzurak, who works on silicon qubits at the University of New South Wales in Australia. “To get to hundreds of thousands of qubits, we will need incredible engineering reliability, and that is the hallmark of the semiconductor industry,” he says.
Companies developing superconducting qubits also make them using existing chip fabrication methods. But the resulting devices are larger than transistors, and there is no template for how to manufacture and package them up in large numbers, says Dzurak.
Chad Rigetti, founder and CEO of Rigetti Computing, a startup working on superconducting qubits similar to those Google and IBM are developing, agrees that this presents a challenge. But he argues that his chosen technology’s head start will afford ample time and resources to tackle the problem.
Google and Rigetti have both said that in just a few years they could build a quantum chip with tens or hundreds of qubits that dramatically outperforms conventional computers on certain problems, even doing useful work on problems in chemistry or machine learning.
The good news is that mental health professionals have smarter tools than ever before, with artificial intelligence-related technology coming to the forefront to help diagnose patients, often with much greater accuracy than humans.
A new study published in the journal Suicide and Life-Threatening Behavior, for example, showed that machine learning is up to 93 percent accurate in identifying a suicidal person. The research, led by John Pestian, a professor at Cincinnati Children’s Hospital Medical Center, involved 379 teenage patients from three area hospitals.
Each patient completed standardized behavioral rating scales and participated in a semi-structured interview, answering five open-ended questions such as “Are you angry?” to stimulate conversation, according to a press release from the university.
The researchers analyzed both verbal and non-verbal language from the data, then sent the information through a machine-learning algorithm that was able to determine with remarkable accuracy whether the person was suicidal, mentally ill but not suicidal, or neither.
“These computational approaches provide novel opportunities to apply technological innovations in suicide care and prevention, and it surely is needed,” Pentian says in the press release.
In 2014, suicide was ranked as the tenth leading cause of death in the United States, but the No. 2 cause of death for people age 15 to 24, according to the American Association of Suicidology.
A study just published in the journal Psychological Bulletin further punctuated the need for better tools to help with suicide prevention. A meta-analysis of 365 studies conducted over the last 50 years found that the ability of mental health experts to predict if someone will attempt suicide is “no better than chance.”
“One of the major reasons for this is that researchers have almost always tried to use a single factor (e.g., a depression diagnosis) to predict these things,” says lead author Joseph Franklin of Harvard University in an email exchange with Singularity Hub.
Franklin says that the complex nature behind such thoughts and behaviors requires consideration of tens if not hundreds of factors to make accurate predictions. He and others argue in a correspondence piece published earlier this year in Psychological Medicine that machine learning and related techniques are an ideal option. A search engine using only one factor would be ineffective at returning results; the same is true of today’s attempts to predict suicidal behavior.
He notes that researchers in Boston, including colleague Matthew K. Nock at Harvard, have already used machine learning to predict suicidal behaviors with 70 to 85 percent accuracy. Calling the work “amazing,” Franklin notes that the research is still in the preliminary stages, with small sample sizes.
“The work by the Pestian group is also interesting, with their use of vocal patterns/natural language processing being unique from most other work in this area so far,” Franklin says, adding that there are also limits as to what can be drawn from their findings at this point. “Nevertheless, this is a very interesting line of work that also represents a sharp and promising departure from what the field has been doing for the past 50 years.”
Machine learning has yet to be used in therapy, according to Franklin, while most conventional treatments for suicide fall short.
“So even though several groups are on the verge of being able to accurately predict suicidality on the scale of entire healthcare systems [with AI], it’s unclear what we should do with these at-risk people to reduce their risk,” Franklin says.
To that end, Franklin and colleagues have developed a free app called Tec-Tec that appears effective at “reducing self-cutting, suicide plans, and suicidal behaviors.”
The app is based on a psychological technique called evaluative conditioning. By continually pairing certain words and images, it changes associations with certain objects and concepts, according to the website, so that within a game-like design, Tec-Tec seeks to change associations with certain factors that may increase risk for self-injurious behaviors.
“We’re working on [additional] trials and soon hope to use machine learning to tailor the app to each individual over time,” Franklin says, “and to connect the people most in need with the app.”
Thirty-four participants were interviewed and assessed quarterly for two and a half years. Using automated analysis, transcripts of the interviews were evaluated for coherence and two syntactic markers of speech complexity—the length of a sentence and the number of clauses it contained.
The speech features analyzed by the computer predicted later psychosis development with 100 percent accuracy, outperforming classification from clinical interviews, according to the researchers.
“Recent developments in computer science, including natural language processing, could provide the foundation for future development of objective clinical tests for psychiatry,” they wrote.
The research uses “the latest methods in computer vision, machine learning and data mining” to assess children while they are performing certain physical and computer exercises, according to a press release from UTA. The exercises test a child’s attention, decision-making and ability to manage emotions. The data are then analyzed to determine the best type of intervention.
“We believe that the proposed computational methods will help provide quantifiable early diagnosis and allow us to monitor progress over time. In particular, it will help children overcome learning difficulties and lead them to healthy and productive lives,” says Fillia Makedon, a professor in UTA’s Department of Computer Science and Engineering.
Keeping an eye out for autism
Meanwhile, a group at the University of Buffalo has developed a mobile app that can detect autism spectrum disorder (ASD) in children as young as two years old with nearly 94 percent accuracy. The results were recently presented at the IEEE Wireless Health conference at the National Institutes of Health.
The app tracks eye movements of a child looking at pictures of social scenes, such as those showing multiple people, according to a press release from the university. The eye movements of someone with ASD are often different from those of a person without autism.
About one in 68 children in the United States has been diagnosed with ASD, according to the CDC. The UB study included 32 children ranging in age from two to 10. A larger study is planned for the future.
It takes less than a minute to administer the test, which can be done by a parent at home to determine if a child requires professional evaluation.
“This technology fills the gap between someone suffering from autism to diagnosis and treatment,” says Wenyao Xu, an assistant professor in UB’s School of Engineering and Applied Sciences.
Technology that helps treat our most vulnerable populations? Turns out, there is an app for that.
These used to be questions that only philosophers worried about. Scientists just got on with figuring out how the world is, and why. But some of the current best guesses about how the world is seem to leave the question hanging over science too.
Several physicists, cosmologists and technologists are now happy to entertain the idea that we are all living inside a gigantic computer simulation, experiencing a Matrix-style virtual world that we mistakenly think is real.
Our instincts rebel, of course. It all feels too real to be a simulation. The weight of the cup in my hand, the rich aroma of the coffee it contains, the sounds all around me – how can such richness of experience be faked?
But then consider the extraordinary progress in computer and information technologies over the past few decades. Computers have given us games of uncanny realism – with autonomous characters responding to our choices – as well as virtual-reality simulators of tremendous persuasive power.
It is enough to make you paranoid.
The Matrix formulated the narrative with unprecedented clarity. In that story, humans are locked by a malignant power into a virtual world that they accept unquestioningly as “real”. But the science-fiction nightmare of being trapped in a universe manufactured within our minds can be traced back further, for instance to David Cronenberg’s Videodrome (1983) and Terry Gilliam’s Brazil (1985).
Over all these dystopian visions, there loom two questions. How would we know? And would it matter anyway?
Elon Musk, CEO of Tesla and SpaceX (Credit: Kristoffer Tripplaar/Alamy)
The idea that we live in a simulation has some high-profile advocates.
In June 2016, technology entrepreneur Elon Musk asserted that the odds are “a billion to one” against us living in “base reality”.
Similarly, Google’s machine-intelligence guru Ray Kurzweil has suggested that “maybe our whole universe is a science experiment of some junior high-school student in another universe”
What’s more, some physicists are willing to entertain the possibility. In April 2016, several of them debated the issue at the American Museum of Natural History in New York, US.
None of these people are proposing that we are physical beings held in some gloopy vat and wired up to believe in the world around us, as in The Matrix.
Instead, there are at least two other ways that the Universe around us might not be the real one.
Cosmologist Alan Guth of the Massachusetts Institute of Technology, US has suggested that our entire Universe might be real yet still a kind of lab experiment. The idea is that our Universe was created by some super-intelligence, much as biologists breed colonies of micro-organisms.
A 14-year-old girl who said before dying of cancer that she wanted a chance to live longer has been allowed by the high court to have her body cryogenically frozen in the hope that she can be brought back to life at a later time.
The court ruled that the teenager’s mother, who supported the girl’s wish to be cryogenically preserved, should be the only person allowed to make decisions about the disposal of her body. Her estranged father had initially opposed her wishes.
During the last months of her life, the teenager, who had a rare form of cancer, used the internet to investigate cryonics. Known only as JS, she sent a letter to the court: “I have been asked to explain why I want this unusual thing done. I’m only 14 years old and I don’t want to die, but I know I am going to. I think being cryo‐preserved gives me a chance to be cured and woken up, even in hundreds of years’ time.
“I don’t want to be buried underground. I want to live and live longer and I think that in the future they might find a cure for my cancer and wake me up. I want to have this chance. This is my wish.”
Following the ruling, in a case described by the judge as exceptional, the body of JS has now been preserved and transported from where she lived in London to the US, where it has been frozen “in perpetuity” by a commercial company at a cost of £37,000.
The girl’s parents are divorced. She had lived with her mother for most of her life and had had no face-to-face contact with her father since 2008. She resisted his attempts to get back in touch when he learnt of her illness in 2015.
The judge, Mr Justice Peter Jackson, ruled that nothing about the case should be reported while she was alive because media coverage would distress her. She was too ill to attend the court hearing but the judge visited her in hospital.
Jackson wrote: “I was moved by the valiant way in which she was facing her predicament. It is no surprise that this application is the only one of its kind to have come before the courts in this country, and probably anywhere else. It is an example of the new questions that science poses to the law, perhaps most of all to family law … No other parent has ever been put in [the] position [of JS’s father].”
He added: “A dispute about a parent being able to see his child after death would be momentous enough on its own if the case did not also raise the issue of cryonic preservation.”
Since the first preservation by freezing in the 1960s the process has been performed only a few hundred times. The body has to be prepared shortly after death, ideally within minutes. Arrangements then have to be made for the body to be transported by a registered funeral director.
“The scientific theory underlying cryonics is speculative and controversial, and there is considerable debate about its ethical implications,” Jackson said. “On the other hand, cryopreservation, the preservation of cells and tissues by freezing, is now a well-known process in certain branches of medicine, for example the preservation of sperm and embryos as part of fertility treatment. Cryonics is cryopreservation taken to its extreme.”
The judge said the girl’s family was not well off but that her mother’s parents had raised the money. A voluntary UK group of cryonics enthusiasts, who were not medically trained, had offered to help make arrangements.
Co-operation of a hospital was required. “This situation gives rise to serious legal and ethical issues for the hospital trust,” the judge observed, “which has to act within the law and has duties to its other patients and to its staff.”
The hospital trust in the case was willing to help although it stressed it was not endorsing cryonics. “On the contrary, all the professionals feel deep unease about it,” the judge said.
The Human Tissue Authority (HTA), which regulates organisations which remove, store and use human tissue, had been consulted but said it had no remit to intervene in such a case.
“The HTA would be likely to make representations that activities of the present kind should be brought within the regulatory framework if they showed signs of increasing,” Jackson said.
The HTA said: “We are gathering information about cryopreservation to determine how widespread it is currently, or could become in the future, and any risks it may pose to the individual, or public confidence more broadly. We are in discussion with key stakeholders … and the possible need for regulatory oversight.”
The government may need to intervene in future, Jackson said: “It may be … events in this case suggest the need for proper regulation of cryonic preservation in this country if it is to happen in future.”
Inquiries made of American authorities revealed that there was no prohibition on human remains being shipped to the US for cryonic preservation, providing certain provisions were made.
During the course of the 14-year-old’s case, the father changed his mind and told the court: “I respect the decisions [my daughter] is making. This is the last and only thing she has asked from me.”
A child cannot make a will and the court had to decide where the girl’s best interests lay. The judge concluded that allowing the mother to make a decision about her daughter would be in her best interests. The girl died peacefully knowing that her body would be frozen, the judge recorded.
The Department of Health said: “Cases such as this are rare. Although there are no current plans for legislative change in this area, this is an area we will continue to keep under review with the Human Tissue Authority.
Life at the edge of death Murray Ballard, from the book The Prospect of Immortality
By Helen Thomson
“WE’RE taking people to the future!” says architect Stephen Valentine, as we drive through two gigantic gates into a massive plot of land in the middle of the sleepy, unassuming town that is Comfort, Texas. The scene from here is surreal. A lake with a newly restored wooden gazebo sits empty, waiting to be filled. A pregnant zebra strolls across a nearby field. And out in the distance some men in cowboy hats are starting to clear a huge area of shrub land. Soon the first few bricks will be laid here, marking the start of a scientific endeavour like no other.
After years of searching, Valentine chose this site as the unlikely home of the new Mecca of cryogenics. Called Timeship, the monolithic building will become the world’s largest structure devoted to cryopreservation, and will be home to thousands of people who are neither dead nor alive, frozen in time in the hope that one day technology will be able to bring them back to life. And last month, building work began.
Cryonics, the cooling of humans in the hope of reanimating them later, has a reputation as a vanity project for those who have more money than sense, but this “centre for immortality” is designed to be about much more than that. As well as bodies, it will store cells, tissues and organs, in a bid to drive forward the capabilities of cryogenics, the study of extremely low temperatures that has, in the last few years, made remarkable inroads in areas of science that affect us all; fertility therapy, organ transplantation and emergency medicine. What’s more, the cutting-edge facilities being built here should break through the limitations of current cryopreservation, making it more likely that tissues – and whole bodies – can be successfully defrosted in the future.
Timeship is the brainchild of Bill Faloon and Saul Kent, two entrepreneurs and prominent proponents of life extension research. Their vision was to create a building that would house research laboratories, DNA from near-extinct species, the world’s largest human organ biobank, and 50,000 cryogenically frozen bodies. Kent called it “all part of a plan to conquer ageing and death”.
In 1997, Kent asked Valentine, an architect based in New York, whether he could design a building that was stable enough to operate continuously for 100 years with minimal human input. It needed to withstand earthquakes, to be protected from natural disasters and acts of violence, and to survive without the main power supply for months on end. It was a list of demands that no building in the world currently satisfies.
Valentine spent months drawing up proposals for the building, together with advice from engineers who had previously worked for NASA and security experts from around the world. “We had to address everything from pandemics and cyberattacks to snipers and global warming,” says Fred Waterman, a risk mitigation expert on the Timeship team. The designs were approved by Kent but immediately put on ice. He believed the technology that would make the building worthwhile was not yet advanced enough to warrant its construction.
At body temperature, cells need a constant supply of oxygen. Without it they start to die and tissues decay. At low temperatures, cells need less oxygen because the chemical activity of metabolism slows down. At very low temperatures, metabolism stops altogether. The problem faced when trying to preserve human tissue by freezing it is that water in the tissue forms ice and causes damage. The trick is to replace the water with cryoprotectants, essentially antifreeze, which prevent ice from forming. This works well for small, uncomplicated structures like sperm and eggs. But when you try to scale it up to larger organs, damage still occurs.
But in 2000, Greg Fahy, a cryobiologist at 21st Century Medicine in Fontana, California, made a breakthrough with a technique called vitrification. It involves adding cryoprotectants then rapidly cooling an organ to prevent any freezing; instead the tissue turns into a glass-like state. Fahy later showed that you could vitrify a whole rabbit kidney that functioned well after thawing and transplantation. This was the breakthrough Kent and Faloon had been waiting for.
Cold comfort farm
The pair gave Valentine a multimillion-dollar budget and told him to find land on which to build Timeship. Valentine spent five years scouring the US, believing it to be the country most likely to remain politically stable for the next 100 years. He homed in on four states that fitted his exacting criteria. And after evaluating more than 200 sites in Texas alone, Valentine ended up in Comfort. Here he discovered the Bildarth Estate, which came with acres of land, a 1670-square-metre mansion and even a few zebras.
“There’s an urgent need to be able to store whole organs for longer”
Since then, Valentine, together with a team of specialists, has fine-tuned the project. Timeship’s architectural plans make it look like something between a fortress and a spaceship. The central building is a low-lying square with a single entrance. This sits inside a circular wall surrounded by concentric concrete rings. Inside are what Valentine calls “neighbourhoods”, collections of thermos-like dewars that will store the cryopreserved DNA, organs and bodies (see “Cool design”).
Parts of the project are somewhat theatrical – backup liquid nitrogen storage tanks are covered overhead by a glass-floored plaza on which you can walk surrounded by a fine mist of clouds – others are purely functional, like the three wind turbines that will provide year-round back-up energy.
The question is, do we need Timeship? Such an extravagant endeavour might not be vital, but it looks as if something similar will be necessary sooner or later. In fact, the strongest argument for such a facility, and the technological developments it promises, might have nothing to do with the desire to be frozen for the future.
We already have small biobanks for storing bones from human donors, as well as tendons, ligaments and stem cells. But with rapid advances in regenerative medicine, there is a growing need for large-scale facilities in which we can store more cryogenically frozen biological material.
Stem cells, for instance, are increasingly cryopreserved after being extracted and grown outside the body for use in regenerative therapies. “Beyond the age of 50, it’s harder to isolate stem cells for regenerative medicine,” says Mark Lowdell at University College London. “If I were in my 30s, I would certainly be cryopreserving some bone marrow for future tissue to fix my tennis injuries.” Lowdell will soon do the first transplant of a tissue-engineered larynx created from a donor larynx that has been seeded with cryopreserved stem cells to reduce the risk of rejection.
Then there’s the problem of organ shortage. In the US, almost 31,000 transplants were carried out in 2015, but at least six times as many people are on the waiting list – each day 12 people die before they can get a kidney. To make matters worse, many organs go to waste because their shelf life is too short to find a well-matched patient. Nearly 500 kidneys went unused in the US last year because the recipient couldn’t get the organ in time.
So there’s an urgent need to be able to store whole organs for longer. The issue is so important that the US government this month pledged to start funding research into this very area. We can already reversibly cryopreserve small bundles of cells – many thousands of babies have been born from vitrified human embryos. Doing the same with large organs, like kidneys or hearts, is harder, but not impossible. Over the past decade, for instance, several babies have been born from ovarian tissue that was removed before chemotherapy, cryopreserved and later replaced. Similarly, rabbit kidneys and rat limbs have been cryopreserved, thawed and placed in a new body. Fahy says his team is well on its way to the first human trial of a cryogenically frozen organ. “After decades of research, we’re now at a tipping point,” he says. Having improved both the vitrification technique and the cryoprotectant solution, they are moving to trials in pigs, and human trials could follow within five years, he says.
That might help prevent wastage, but we would still have a shortage of organs for transplant. Another solution is to grow them from scratch using our own stem cells, and keep them until we need them. So far, tiny 3D heart-like organs have been made from stem cells alone, as well as mini kidneys and livers, all with the ultimate aim of bioengineering replacement organs for transplantation.
Once organs can be produced like this, we will need a way of storing either the raw material or the organs themselves. “I’m not enthusiastic about the notion of freezing whole heads, but I can certainly imagine people needing to freeze cells, or ‘starter kits’ for the development of tissues, or even whole organs – and in the not-so-distant future,” says Arthur Caplan, a bioethicist at New York University Langone Medical Center.
Like Caplan, most scientists I spoke to said it was becoming more likely that we could bring individual cryopreserved organs back to life, but were less convinced by the idea of freezing whole bodies. So I decided to visit Alcor Life Extension Foundation, the world’s biggest cryonics facility, in Scottsville, Arizona, to find out what happens when a body is put on ice.
Alcor’s lobby has the feel of a doctor’s waiting room, except that lining the walls are portraits of men, women, children and the occasional dog. The people in the pictures are preserved there, some alongside their beloved pets.
Aaron Drake, head of Alcor’s medical response team, says the company has more than 1000 clients signed up worldwide – 99 per cent are healthy, but 1 per cent have a terminal disease. Some of them want to freeze their whole body, others – known as “neuros” – opt for just the head.
Drake admits that the techniques his firm uses aren’t perfect, which is why they continue to research the process. Recently, Alcor scientists placed acoustical devices on the brains of neuros as they were lowered into liquid nitrogen, listening as the heads cooled to -196 °C. The colder they got, the more frequently the team heard acoustical anomalies, which they attribute to micro-fracturing of the tissue. “That’s damage happening,” says Drake. It’s difficult to say what effects this might have. “It’s not universal or consistent, but it’s something we know doesn’t happen at around -140 °C.”
The problem is, to store a person at -140 °C, you have to keep them warmer than nitrogen’s boiling point, which is incredibly hard to do – certainly much harder than placing a body in a giant thermos full of liquid nitrogen, letting it boil and occasionally topping it up.
But at Timeship, Valentine thinks he’s cracked the problem. After years of experimentation, he has designed a system called a Temperature Control Vessel (TCV), a dewar that houses cryogenically preserved bodies, heads or tissues. Inside the dewar are moving rods that can be dipped into a pool of liquid nitrogen whenever a sensor notes that the temperature has risen from -140 °C. This would provide a relatively autonomous way of maintaining the contents at an ideal temperature (see “Cool design”).
Each TCV can carry hundreds of samples of tissue and organs, or four bodies and five heads.They are designed to be stacked together in a tessellating pattern that forms the neighbourhoods within the main building.
This should reduce some of the damage to brain tissue that the Alcor team heard. But even with that technology, is there any hope of reanimating a brain?
There is some evidence to suggest that certain properties of the mind – memories, for instance – can survive cryopreservation. In 2015, researchers trained worms to recognise a smell, then froze them. On thawing, the worms retained the smell memories. And this year, Fahy’s team cryopreserved a rabbit brain in a near-perfect state. Although the group used a chemical fixative that is not yet used in human preservation, the thawed rabbit brain appeared “uniformly excellent” when examined using electron microscopy.
“These kinds of experiments show that it’s not such a massive leap of faith to think that we could preserve the human mind,” says Max More, president and CEO of Alcor. But not everyone is convinced. Even if you could preserve the delicate structures of the human brain, the cryoprotectants themselves are toxic. “No matter how smart scientists are in the future, you can’t change mush into a functional brain,” says Caplan, “and I just don’t think that what we’re able to do right now to preserve the brain is good enough to ever bring it back to life.”
There are precedents for the idea that the human brain can be revived after being cooled, however. In 1986, two-and-a-half-year-old Michelle Funk fell into an icy creek where she was submerged for just over an hour. Despite showing no signs of life, doctors spent 2 hours warming her blood through a heart-lung machine. Eventually, she recovered fully. Her doctors figured that the sudden cooling of her brain must have slowed the organ’s need for oxygen, staving off brain damage.
“What we are doing is just an extension of emergency medicine – we are stretching time“
Funk’s recovery was so remarkable it spurred researchers to repeat the scenario experimentally in pigs and dogs – cryopreserving them for hours before bringing them back to life. The same procedure is now being tested in humans in a groundbreaking trial by surgeons at UPMC Presbyterian Hospital in Pittsburgh, Pennsylvania. There they are placing patients in suspended animation for a few hours, to buy time to fix injuries that would otherwise be lethal, such as gunshot wounds. The technique involves replacing the person’s blood with a cold saline solution and cooling the body. They will then try to fix the injuries and bring the patient back to life by slowly warming the body with blood.
That’s not so different from what goes on at Alcor, says More. “What we’re doing is trying to stretch the time in which the person is suspended. It’s just an extension of emergency medicine.” I ask More whether he really believes that his members will be brought back to life. “I don’t know if it will ever happen,” he says, “but we’re breaking no laws of physics here. Who is to say that in 100 years we won’t have the medical tools – some kind of nanotechnology perhaps – that can fix cells at an individual level and repair what’s necessary to revive someone in good health.”
This is the central argument in favour of cryonics – the possibility, no matter how slim, that it offers a chance of survival. “We think of cryonics as a scientific experiment,” says More. “People that are buried or cremated are our control group, and so far, everyone in the control group has died.”
Facing the future
It is an expensive experiment, however. Cryopreserving your body will set you back up to $220,000, payable on death – often via life insurance, with Alcor as the beneficiary.
“People often say that the money would be better spent on family or given to charity,” says Ole Moen, a philosopher and ethicist at the University of Oslo, Norway. “But what’s strange about this is that nobody complains when people spend money on expensive cancer treatments or long-term care – people drain the public healthcare budget trying to stay alive all the time,” he says. “So why complain when people want to spend their own money trying to live longer via cryonics?”
If you’re happy to fork out, there’s the big question of what kind of future you’d wake up to. “Even if you could get this technique up and running by some magical future science I believe you’d be a freak – you’d be so far out of it culturally, so lost, that you’d be at risk of being driven mad,” Caplan says.
With so many big unknowns, I leave Alcor and Timeship undecided on the utility of cryonics. What’s clear, though, is that the underlying research into cryopreservation is worthwhile. Whether it’s to help me have children, fix a future tennis injury or potentially even provide me with a new heart, I’d be first in line to freeze cells and tissues today that might help my future self live longer, and healthier.
On my way out of Alcor, I ask Drake whether he wants to be frozen, given that he has cryopreserved so many others. “Yes,” he says. “Not because I want to be immortal, I don’t think that’s possible. I just want to see if all this work was futile. I was the last person these people saw before they took their last breath. Will they see me again? Will they thank me? I don’t know if that will ever happen. But wouldn’t that be nice?”
What is death?
Death has been redefined several times over the past century. It was once considered the cessation of a heartbeat and breathing. Today it includes other scenarios, such as the cessation of brain activity. But even that’s not good enough for some.
“Death is a process, not a switch,” says Max More, president and CEO of the Alcor Life Extension Foundation in Scottsdale, Arizona. “If you go back 100 years and someone falls over in the street and stops breathing, doctors would say ‘this person is dead’. Today we can do CPR and defibrillation to restart their heart and they can be brought back to life. So when that doctor declared them dead, were they? With today’s standards, no they weren’t.” Instead, says More, what we’re really saying is “given today’s technology and the medicine I have available to me right now, there’s nothing more I can do for you”.
A definition that emerged in the 1990s in response to this problem is the information-theoretic definition of death. It states that a person is dead only when the structures that encode memory and personality are so disrupted that it is no longer possible in principle to restore them.
Therefore a person who is cryogenically frozen, with brain structures preserved in a state close to what they were before the pronouncement of clinical death, is not by this definition, actually dead. So if the people frozen at Alcor aren’t dead, what are they? “There’s no good word for what they are,” says More (see Interview “I want to put your death on ice so that you can live again“). “Some people say they are de-animated.”
This article appeared in print under the headline “The big freeze”