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#432671 Stuff 3.0: The Era of Programmable ...

It’s the end of a long day in your apartment in the early 2040s. You decide your work is done for the day, stand up from your desk, and yawn. “Time for a film!” you say. The house responds to your cues. The desk splits into hundreds of tiny pieces, which flow behind you and take on shape again as a couch. The computer screen you were working on flows up the wall and expands into a flat projection screen. You relax into the couch and, after a few seconds, a remote control surfaces from one of its arms.

In a few seconds flat, you’ve gone from a neatly-equipped office to a home cinema…all within the same four walls. Who needs more than one room?

This is the dream of those who work on “programmable matter.”

In his recent book about AI, Max Tegmark makes a distinction between three different levels of computational sophistication for organisms. Life 1.0 is single-celled organisms like bacteria; here, hardware is indistinguishable from software. The behavior of the bacteria is encoded into its DNA; it cannot learn new things.

Life 2.0 is where humans live on the spectrum. We are more or less stuck with our hardware, but we can change our software by choosing to learn different things, say, Spanish instead of Italian. Much like managing space on your smartphone, your brain’s hardware will allow you to download only a certain number of packages, but, at least theoretically, you can learn new behaviors without changing your underlying genetic code.

Life 3.0 marks a step-change from this: creatures that can change both their hardware and software in something like a feedback loop. This is what Tegmark views as a true artificial intelligence—one that can learn to change its own base code, leading to an explosion in intelligence. Perhaps, with CRISPR and other gene-editing techniques, we could be using our “software” to doctor our “hardware” before too long.

Programmable matter extends this analogy to the things in our world: what if your sofa could “learn” how to become a writing desk? What if, instead of a Swiss Army knife with dozens of tool attachments, you just had a single tool that “knew” how to become any other tool you could require, on command? In the crowded cities of the future, could houses be replaced by single, OmniRoom apartments? It would save space, and perhaps resources too.

Such are the dreams, anyway.

But when engineering and manufacturing individual gadgets is such a complex process, you can imagine that making stuff that can turn into many different items can be extremely complicated. Professor Skylar Tibbits at MIT referred to it as 4D printing in a TED Talk, and the website for his research group, the Self-Assembly Lab, excitedly claims, “We have also identified the key ingredients for self-assembly as a simple set of responsive building blocks, energy and interactions that can be designed within nearly every material and machining process available. Self-assembly promises to enable breakthroughs across many disciplines, from biology to material science, software, robotics, manufacturing, transportation, infrastructure, construction, the arts, and even space exploration.”

Naturally, their projects are still in the early stages, but the Self-Assembly Lab and others are genuinely exploring just the kind of science fiction applications we mooted.

For example, there’s the cell-phone self-assembly project, which brings to mind eerie, 24/7 factories where mobile phones assemble themselves from 3D printed kits without human or robotic intervention. Okay, so the phones they’re making are hardly going to fly off the shelves as fashion items, but if all you want is something that works, it could cut manufacturing costs substantially and automate even more of the process.

One of the major hurdles to overcome in making programmable matter a reality is choosing the right fundamental building blocks. There’s a very important balance to strike. To create fine details, you need to have things that aren’t too big, so as to keep your rearranged matter from being too lumpy. This might make the building blocks useless for certain applications—for example, if you wanted to make tools for fine manipulation. With big pieces, it might be difficult to simulate a range of textures. On the other hand, if the pieces are too small, different problems can arise.

Imagine a setup where each piece is a small robot. You have to contain the robot’s power source and its brain, or at least some kind of signal-generator and signal-processor, all in the same compact unit. Perhaps you can imagine that one might be able to simulate a range of textures and strengths by changing the strength of the “bond” between individual units—your desk might need to be a little bit more firm than your bed, which might be nicer with a little more give.

Early steps toward creating this kind of matter have been taken by those who are developing modular robots. There are plenty of different groups working on this, including MIT, Lausanne, and the University of Brussels.

In the latter configuration, one individual robot acts as a centralized decision-maker, referred to as the brain unit, but additional robots can autonomously join the brain unit as and when needed to change the shape and structure of the overall system. Although the system is only ten units at present, it’s a proof-of-concept that control can be orchestrated over a modular system of robots; perhaps in the future, smaller versions of the same thing could be the components of Stuff 3.0.

You can imagine that with machine learning algorithms, such swarms of robots might be able to negotiate obstacles and respond to a changing environment more easily than an individual robot (those of you with techno-fear may read “respond to a changing environment” and imagine a robot seamlessly rearranging itself to allow a bullet to pass straight through without harm).

Speaking of robotics, the form of an ideal robot has been a subject of much debate. In fact, one of the major recent robotics competitions—DARPA’s Robotics Challenge—was won by a robot that could adapt, beating Boston Dynamics’ infamous ATLAS humanoid with the simple addition of a wheel that allowed it to drive as well as walk.

Rather than building robots into a humanoid shape (only sometimes useful), allowing them to evolve and discover the ideal form for performing whatever you’ve tasked them to do could prove far more useful. This is particularly true in disaster response, where expensive robots can still be more valuable than humans, but conditions can be very unpredictable and adaptability is key.

Further afield, many futurists imagine “foglets” as the tiny nanobots that will be capable of constructing anything from raw materials, somewhat like the “Santa Claus machine.” But you don’t necessarily need anything quite so indistinguishable from magic to be useful. Programmable matter that can respond and adapt to its surroundings could be used in all kinds of industrial applications. How about a pipe that can strengthen or weaken at will, or divert its direction on command?

We’re some way off from being able to order our beds to turn into bicycles. As with many tech ideas, it may turn out that the traditional low-tech solution is far more practical and cost-effective, even as we can imagine alternatives. But as the march to put a chip in every conceivable object goes on, it seems certain that inanimate objects are about to get a lot more animated.

Image Credit: PeterVrabel / Shutterstock.com Continue reading

Posted in Human Robots

#432572 Robots Can Swim, Fetch, Lift, and Dance. ...

Robotics has come a long way in the past few years. Robots can now fetch items from specific spots in massive warehouses, swim through the ocean to study marine life, and lift 200 times their own weight. They can even perform synchronized dance routines.

But the really big question is—can robots put together an Ikea chair?

A team of engineers from Nanyang Technological University in Singapore decided to find out, detailing their work in a paper published last week in the journal Science Robotics. The team took industrial robot arms and equipped them with parallel grippers, force-detecting sensors, and 3D cameras, and wrote software enabling the souped-up bots to tackle chair assembly. The robots’ starting point was a set of chair parts randomly scattered within reach.

As impressive as the above-mentioned robotic capabilities are, it’s worth noting that they’re mostly limited to a single skill. Putting together furniture, on the other hand, requires using and precisely coordinating multiple skills, including force control, visual localization, hand-eye coordination, and the patience to read each step of the manual without rushing through it and messing everything up.

Indeed, Ikea furniture, while meant to be simple and user-friendly, has left even the best of us scratching our heads and holding a spare oddly-shaped piece of wood as we stare at the desk or bed frame we just put together—or, for the less even-tempered among us, throwing said piece of wood across the room.

It’s a good thing robots don’t have tempers, because it took a few tries for the bots to get the chair assembly right.

Practice makes perfect, though (or in this case, rewriting code makes perfect), and these bots didn’t give up so easily. They had to hone three different skills: identifying which part was which among the scattered, differently-shaped pieces of wood, coordinating their movements to put those pieces in the right place, and knowing how much force to use in various steps of the process (i.e., more force is needed to connect two pieces than to pick up one piece).

A few tries later, the bots were able to assemble the chair from start to finish in about nine minutes.

On the whole, nicely done. But before we applaud the robots’ success too loudly, it’s important to note that they didn’t autonomously assemble the chair. Rather, each step of the process was planned and coded by engineers, down to the millimeter.

However, the team believes this closely-guided chair assembly was just a first step, and they see a not-so-distant future where combining artificial intelligence with advanced robotic capabilities could produce smart bots that would learn to assemble furniture and do other complex tasks on their own.

Future applications mentioned in the paper include electronics and aircraft manufacturing, logistics, and other high-mix, low-volume sectors.

Image Credit: Francisco Suárez-Ruiz and Quang-Cuong Pham/Nanyang Technological University Continue reading

Posted in Human Robots

#432568 Tech Optimists See a Golden ...

Technology evangelists dream about a future where we’re all liberated from the more mundane aspects of our jobs by artificial intelligence. Other futurists go further, imagining AI will enable us to become superhuman, enhancing our intelligence, abandoning our mortal bodies, and uploading ourselves to the cloud.

Paradise is all very well, although your mileage may vary on whether these scenarios are realistic or desirable. The real question is, how do we get there?

Economist John Maynard Keynes notably argued in favor of active intervention when an economic crisis hits, rather than waiting for the markets to settle down to a more healthy equilibrium in the long run. His rebuttal to critics was, “In the long run, we are all dead.” After all, if it takes 50 years of upheaval and economic chaos for things to return to normality, there has been an immense amount of human suffering first.

Similar problems arise with the transition to a world where AI is intimately involved in our lives. In the long term, automation of labor might benefit the human species immensely. But in the short term, it has all kinds of potential pitfalls, especially in exacerbating inequality within societies where AI takes on a larger role. A new report from the Institute for Public Policy Research has deep concerns about the future of work.

Uneven Distribution
While the report doesn’t foresee the same gloom and doom of mass unemployment that other commentators have considered, the concern is that the gains in productivity and economic benefits from AI will be unevenly distributed. In the UK, jobs that account for £290 billion worth of wages in today’s economy could potentially be automated with current technology. But these are disproportionately jobs held by people who are already suffering from social inequality.

Low-wage jobs are five times more likely to be automated than high-wage jobs. A greater proportion of jobs held by women are likely to be automated. The solution that’s often suggested is that people should simply “retrain”; but if no funding or assistance is provided, this burden is too much to bear. You can’t expect people to seamlessly transition from driving taxis to writing self-driving car software without help. As we have already seen, inequality is exacerbated when jobs that don’t require advanced education (even if they require a great deal of technical skill) are the first to go.

No Room for Beginners
Optimists say algorithms won’t replace humans, but will instead liberate us from the dull parts of our jobs. Lawyers used to have to spend hours trawling through case law to find legal precedents; now AI can identify the most relevant documents for them. Doctors no longer need to look through endless scans and perform diagnostic tests; machines can do this, leaving the decision-making to humans. This boosts productivity and provides invaluable tools for workers.

But there are issues with this rosy picture. If humans need to do less work, the economic incentive is for the boss to reduce their hours. Some of these “dull, routine” parts of the job were traditionally how people getting into the field learned the ropes: paralegals used to look through case law, but AI may render them obsolete. Even in the field of journalism, there’s now software that will rewrite press releases for publication, traditionally something close to an entry-level task. If there are no entry-level jobs, or if entry-level now requires years of training, the result is to exacerbate inequality and reduce social mobility.

Automating Our Biases
The adoption of algorithms into employment has already had negative impacts on equality. Cathy O’Neil, mathematics PhD from Harvard, raises these concerns in her excellent book Weapons of Math Destruction. She notes that algorithms designed by humans often encode the biases of that society, whether they’re racial or based on gender and sexuality.

Google’s search engine advertises more executive-level jobs to users it thinks are male. AI programs predict that black offenders are more likely to re-offend than white offenders; they receive correspondingly longer sentences. It needn’t necessarily be that bias has been actively programmed; perhaps the algorithms just learn from historical data, but this means they will perpetuate historical inequalities.

Take candidate-screening software HireVue, used by many major corporations to assess new employees. It analyzes “verbal and non-verbal cues” of candidates, comparing them to employees that historically did well. Either way, according to Cathy O’Neil, they are “using people’s fear and trust of mathematics to prevent them from asking questions.” With no transparency or understanding of how the algorithm generates its results, and no consensus over who’s responsible for the results, discrimination can occur automatically, on a massive scale.

Combine this with other demographic trends. In rich countries, people are living longer. An increasing burden will be placed on a shrinking tax base to support that elderly population. A recent study said that due to the accumulation of wealth in older generations, millennials stand to inherit more than any previous generation, but it won’t happen until they’re in their 60s. Meanwhile, those with savings and capital will benefit as the economy shifts: the stock market and GDP will grow, but wages and equality will fall, a situation that favors people who are already wealthy.

Even in the most dramatic AI scenarios, inequality is exacerbated. If someone develops a general intelligence that’s near-human or super-human, and they manage to control and monopolize it, they instantly become immensely wealthy and powerful. If the glorious technological future that Silicon Valley enthusiasts dream about is only going to serve to make the growing gaps wider and strengthen existing unfair power structures, is it something worth striving for?

What Makes a Utopia?
We urgently need to redefine our notion of progress. Philosophers worry about an AI that is misaligned—the things it seeks to maximize are not the things we want maximized. At the same time, we measure the development of our countries by GDP, not the quality of life of workers or the equality of opportunity in the society. Growing wealth with increased inequality is not progress.

Some people will take the position that there are always winners and losers in society, and that any attempt to redress the inequalities of our society will stifle economic growth and leave everyone worse off. Some will see this as an argument for a new economic model, based around universal basic income. Any moves towards this will need to take care that it’s affordable, sustainable, and doesn’t lead towards an entrenched two-tier society.

Walter Schiedel’s book The Great Leveller is a huge survey of inequality across all of human history, from the 21st century to prehistoric cave-dwellers. He argues that only revolutions, wars, and other catastrophes have historically reduced inequality: a perfect example is the Black Death in Europe, which (by reducing the population and therefore the labor supply that was available) increased wages and reduced inequality. Meanwhile, our solution to the financial crisis of 2007-8 may have only made the problem worse.

But in a world of nuclear weapons, of biowarfare, of cyberwarfare—a world of unprecedented, complex, distributed threats—the consequences of these “safety valves” could be worse than ever before. Inequality increases the risk of global catastrophe, and global catastrophes could scupper any progress towards the techno-utopia that the utopians dream of. And a society with entrenched inequality is no utopia at all.

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Posted in Human Robots

#432539 10 Amazing Things You Can Learn From ...

Hardly a day goes by without a research study or article published talking sh*t—or more precisely, talking about the gut microbiome. When it comes to cutting-edge innovations in medicine, all signs point to the microbiome. Maybe we should have listened to Hippocrates: “All disease begins in the gut.”

Your microbiome is mostly located in your gut and contains trillions of little guys and gals called microbes. If you want to optimize your health, biohack your body, make progress against chronic disease, or know which foods are right for you—almost all of this information can be found in your microbiome.

My company, Viome, offers technology to measure your microscopic organisms and their behavior at a molecular level. Think of it as the Instagram of your inner world. A snapshot of what’s happening inside your body. New research about the microbiome is changing our understanding of who we are as humans and how the human body functions.

It turns out the microbiome may be mission control for your body and mind. Your healthy microbiome is part best friend, part power converter, part engine, and part pharmacist. At Viome, we’re working to analyze these microbial functions and recommend a list of personalized food and supplements to keep these internal complex machines in a finely tuned balance.

We now have more information than ever before about what your microbiome is doing, and it’s going to help you and the rest of the world do a whole lot better. The new insights emerging from microbiome research are changing our perception of what keeps us healthy and what makes us sick. This new understanding of the microbiome activities may put an end to conflicting food advice and make fad diets a thing of the past.

What are these new insights showing us? The information is nothing short of mind-blowing. The value of your poop just got an upgrade.

Here are some of the amazing things we’ve learned from our work at Viome.

1. Was Popeye wrong? Why “health food” isn’t necessarily healthy.
Each week there is a new fad diet released, discussed, and followed. The newest “research” shows that this is now the superfood to eat for everyone. But, too often, the fad diet is just a regurgitation of what worked for one person and shouldn’t be followed by everyone else.

For example, we’ve been told to eat our greens and that greens and nuts are “anti-inflammatory,” but this is actually not always true. Spinach, bran, rhubarb, beets, nuts, and nut butters all contain oxalate. We now know that oxalate-containing food can be harmful, unless you have the microbes present that can metabolize it into a non-harmful substance.

30% of Viome customers do not have the microbes to metabolize oxalates properly. In other words, “healthy foods” like spinach are actually not healthy for these people.

Looks like not everyone should follow Popeye’s food plan.

2. Aren’t foods containing “antioxidants” always good for everyone?
Just like oxalates, polyphenols in foods are usually considered very healthy, but unless you have microbes that utilize specific polyphenols, you may not get full benefit from them. One example is a substance found in these foods called ellagic acid. We can detect if your microbiome is metabolizing ellagic acid and converting it into urolithin A. It is only the urolithin A that has anti-inflammatory and antioxidant effects. Without the microbes to do this conversion you will not benefit from the ellagic acid in foods.

Examples: Walnuts, raspberries, pomegranate, blackberries, pecans, and cranberries all contain ellagic acid.

We have analyzed tens of thousands of people, and only about 50% of the people actually benefit from eating more foods containing ellagic acid.

3. You’re probably eating too much protein (and it may be causing inflammation).
When you think high-protein diet, you think paleo, keto, and high-performance diets.

Protein is considered good for you. It helps build muscle and provide energy—but if you eat too much, it can cause inflammation and decrease longevity.

We can analyze the activity of your microbiome to determine if you are eating too much protein that feeds protein-fermenting bacteria like Alistipes putredinis and Tannerella forsythia, and if these organisms are producing harmful substances such as ammonia, hydrogen sulfide, p-cresol, or putrescine. These substances can damage your gut lining and lead to things like leaky gut.

4. Something’s fishy. Are “healthy foods” causing heart disease?
Choline in certain foods can get converted by bacteria into a substance called trimethylamine (TMA) that is associated with heart disease when it gets absorbed into your body and converted to TMAO. However, TMA conversion doesn’t happen in individuals without these types of bacteria in their microbiome.

We can see the TMA production pathways and many of the gammaproteobacteria that do this conversion.

What foods contain choline? Liver, salmon, chickpeas, split peas, eggs, navy beans, peanuts, and many others.

Before you decide to go full-on pescatarian or paleo, you may want to check if your microbiome is producing TMA with that salmon or steak.

5. Hold up, Iron Man. We can see inflammation from too much iron.
Minerals like iron in your food can, in certain inflammatory microbial environments, promote growth of pathogens like Esherichia, Shigella, and Salmonella.

Maybe it wasn’t just that raw chicken that gave you food poisoning, but your toxic microbiome that made you sick.

On the other hand, when you don’t have enough iron, you could become anemic leading to weakness and shortness of breath.

So, just like Iron Man, it’s about finding your balance so that you can fly.

6. Are you anxious or stressed? Your poop will tell you.
Our gut and brain are connected via the vagus nerve. A large majority of neurotransmitters are either produced or consumed by our microbiome. In fact, some 90% of all serotonin (a feel-good neurotransmitter) is produced by your gut microbiome and not by your brain.

When you have a toxic microbiome that’s producing a large amount of toxins like hydrogen sulfide, the lining of your gut starts to deteriorate into what’s known as leaky gut. Think of leaky gut as your gut not having healthy borders or boundaries. And when this happens, all kinds of disease can emerge. When the barrier of the gut breaks down, it starts a chain reaction causing low-grade chronic inflammation—which has been identified as a potential source of depression and higher levels of anxiety, in addition to many other chronic diseases.

We’re not saying you shouldn’t meditate, but if you want to get the most out of your meditation and really reduce your stress levels, make sure you are eating the right food that promotes a healthy microbiome.

7. Your microbiome is better than Red Bull.
If you want more energy, get your microbiome back into balance.

No you don’t need three pots of coffee to keep you going, you just need a balanced microbiome.

Your microbiome is responsible for calorie extraction, or creating energy, through pathways such as the Tricarboxylic acid cycle. Our bodies depend on the energy that our microbiome produces.

How much energy we get from our food is dependent on how efficient our microbiome is at converting the food into energy. High-performing microbiomes are excellent at converting food into energy. This is great when you are an athlete and need the extra energy, but if you don’t use up the energy it may be the source of some of those unwanted pounds.

If the microbes can’t or won’t metabolize the glucose (sugar) that you eat, it will be stored as fat. If the microbes are extracting too many calories from your food or producing lipopolysaccharides (LPS) and causing metabolic endotoxemia leading to activation of toll-like receptors and insulin resistance you may end up storing what you eat as fat.

Think of your microbiome as Doc Brown’s car from the future—it can take pretty much anything and turn it into fuel if it’s strong and resilient enough.

8. We can see your joint pain in your poop.
Got joint pain? Your microbiome can tell you why.

Lipopolysaccharide (LPS) is a key pro-inflammatory molecule made by some of your microbes. If your microbes are making too much LPS, it can wreak havoc on your immune system by putting it into overdrive. When your immune system goes on the warpath there is often collateral damage to your joints and other body parts.

Perhaps balancing your microbiome is a better solution than reaching for the glucosamine. Think of your microbiome as the top general of your immune army. It puts your immune system through basic training and determines when it goes to war.

Ideally, your immune system wins the quick battle and gets some rest, but sometimes if your microbiome keeps it on constant high alert it becomes a long, drawn-out war resulting in chronic inflammation and chronic diseases.

Are you really “getting older” or is your microbiome just making you “feel” older because it keeps giving warnings to your immune system ultimately leading to chronic pain?

Before you throw in the towel on your favorite activities, check your microbiome. And, if you have anything with “itis” in it, it’s possible that when you balance your microbiome the inflammation from your “itis” will be reduced.

9. Your gut is doing the talking for your mouth.
When you have low stomach acid, your mouth bacteria makes it down to your GI tract.

Stomach acid is there to protect you from the bacteria in your mouth and the parasites and fungi that are in your food. If you don’t have enough of it, the bacteria in your mouth will invade your gut. This invasion is associated with and a risk factor for autoimmune disease and inflammation in the gut.

We are learning that low stomach acid is perhaps one of the major causes of chronic disease. This stomach acid is essential to kill mouth bacteria and help us digest our food.

What kinds of things cause low stomach acid? Stress and antacids like Nexium, Zantac, and Prilosec.

10. Carbs can be protein precursors.
Rejoice! Perhaps carbs aren’t as bad as we thought (as long as your microbiome is up to the task). We can see if some of the starches you eat can be made into amino acids by the microbiome.

Our microbiome makes 20% of our branched-chain amino acids (BCAAs) for us, and it will adapt to make these vital BCAAs for us in almost any way it can.

Essentially, your microbiome is hooking up carbons and hydrogens into different formulations of BCAAs, depending on what you feed it. The microbiome is excellent at adapting and pivoting based on the food you feed it and the environment that it’s in.

So, good news: Carbs are protein precursors, as long as you have the right microbiome.

Stop Talking Sh*t Now
Your microbiome is a world class entrepreneur that can take low-grade sources of food and turn them into valuable and useable energy.

You have a best friend and confidant within you that is working wonders to make sure you have energy and that all of your needs are met.

And, just like a best friend, if you take great care of your microbiome, it will take great care of you.

Given the research emerging daily about the microbiome and its importance on your quality of life, prioritizing the health of your microbiome is essential.

When you have a healthy microbiome, you’ll have a healthy life.

It’s now clear that some of the greatest insights for your health will come from your poop.

It’s time to stop talking sh*t and get your sh*t together. Your life may depend on it.

Viome can help you identify what your microbiome is actually doing. The combination of Viome’s metatranscriptomic technology and cutting-edge artificial intelligence is paving a brand new path forward for microbiome health.

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Posted in Human Robots

#432497 Robots that can learn like humans

Researchers say that artificial intelligence (AI) is now superior to human intelligence in supervised learning using vast amounts of labeled data to perform specific tasks. However, it is considered difficult to realize human-like intelligence using only supervised learning because all supervised labels cannot be obtained for all the sensory information required by robots. Continue reading

Posted in Human Robots