from the world's big
A new AI passes the smell test almost 100% of the time
Our remarkable olfactory senses are modeled in a new research chip.
- Two researchers have created an algorithm that can accurately identify 10 different smells.
- The AI algorithm runs on an Intel chip that has 130,000 silicon "neurons."
- The natural mammalian olfactory bulb grows new neurons even in adults.
Our noses are busy beasts. At any given moment, multiple smells are competing for our attention, and somehow the brain can tell when it's smelling an orange even against a backdrop of other scents, say perfume or soap. The brain's olfactory bulb has hundreds of receptors tracking odors all the time, and yet somehow keeps everything straight. A scientist at Cornell University working with a researcher at Intel has just created an AI algorithm trained to recognize 10 scents by mimicking the mammalian olfactory bulb (MOB). Give the algorithm a computer chip to run on and it can learn to identify new odors.
Simulating the brain
Image source: GiroScience/Shutterstock
Thomas Cleland, senior author of "Rapid Learning and Robust Recall in a Neuromorphic Olfactory Circuit" published in Nature Machine Intelligence says, "This is a result of over a decade of studying olfactory bulb circuitry in rodents and trying to figure out essentially how it works, with an eye towards things we know animals can do that our machines can't."
"We now know enough to make this work," says Cleland speaking with Cornell Chronicle. "We've built this computational model based on this circuitry, guided heavily by things we know about the biological systems' connectivity and dynamics. Then we say, if this were so, this would work. And the interesting part is that it does work."
Cleland's co-author, Intel intern Nabil Imam, has the AI running on an Intel research chip called Loihi. The chip is something of a wonder all by itself. It's designed to perform neuromorphic computing inspired by the brain, sporting some 130,000 silicon "neurons." Like our own neurons, each can fire independently of the others, sending pulsed signals to its neighbors, changing their electrical states. In addition, Loihi can accept inputs from a variety of physical sensors, such as the metal-oxide chemical sensors that Cleland and Imam used, allowing the entire structure to simulate the natural learning process that occurs when the mammalian brain is fed various sensory inputs.
What the AI knows
In the MOB, there are a couple of important neuron types: mitral cells that switch on to signify a smell has been detected but don't identify it, and granule cells that learn to become specialized and pinpoint chemicals in the smell. This is the process Cleland and Imam have programmed Loihi to imitate when odors are presented to the system's sensors.
The researchers have trained the algorithm to identify 10 chemical smells: acetone, acetaldehyde, ammonia, butanol, ethylene, methane, methanol, carbon monoxide, benzene, and toluene. The idea is that in the presence of an odor, Loihi verifies the scent's presence and patterns of firing neurons identify exactly which smell it is.
Over the course of five cycles of exposure to each odor, the AI was eventually able to associate specific neural firing patterns with specific smells. The AI correctly identified eight of the smells 100 percent of the time, and the remaining two with 90 percent accuracy.
Additional simulations were run in which the target odor was masked 80 percent by other smells, the way they'd often be in the real word. In these tests, accuracy dropped down to just 30 percent, though that's still pretty impressive for such a "young" AI. Says Cleland, "The pattern of the signal has been substantially destroyed, and yet the system is able to recover it."
The sweet smell of success
Image source: Patrick J. Lynch, wikimedia
As AI and machine learning do, Cleland's and Imam's algorithm would be expected to get better with more training. Machine smell-detection for use in bomb-sniffing, for example, is clearly not just around the corner. Still, the research offers new insights about learning.
Due to the normally finite number of neurons available for storage of new memories in an adult brain, and the fact that "when you learn something, it permanently differentiates neurons," as Cleland says, storing new information means changing the information already encoded in neurons. However, the mammalian olfactory bulb is able to continually learn smells — hundreds or thousands of them —without losing knowledge of already-learned odors. It's one of the few areas of the brain that can keep creating new neurons through adulthood.
The researchers' experience with Loihi underscores the value of the olfactory bulb's unusual neuronal expandability. "The computational model turns into a biological hypothesis for why adult neurogenesis is important," Cleland says, "because it does this thing that otherwise would make the system not work. So in that sense, the model is feeding back into biology. And in this other sense, it's the basis for a set of devices for artificial olfactory systems that can be constructed commercially."
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Richard Feynman once asked a silly question. Two MIT students just answered it.
Here's a fun experiment to try. Go to your pantry and see if you have a box of spaghetti. If you do, take out a noodle. Grab both ends of it and bend it until it breaks in half. How many pieces did it break into? If you got two large pieces and at least one small piece you're not alone.
But science loves a good challenge<p>The mystery remained unsolved until 2005, when French scientists <a href="http://www.lmm.jussieu.fr/~audoly/" target="_blank">Basile Audoly</a> and <a href="http://www.lmm.jussieu.fr/~neukirch/" target="_blank">Sebastien Neukirch </a>won an <a href="https://www.improbable.com/ig/" target="_blank">Ig Nobel Prize</a>, an award given to scientists for real work which is of a less serious nature than the discoveries that win Nobel prizes, for finally determining why this happens. <a href="http://www.lmm.jussieu.fr/spaghetti/audoly_neukirch_fragmentation.pdf" target="_blank">Their paper describing the effect is wonderfully funny to read</a>, as it takes such a banal issue so seriously. </p><p>They demonstrated that when a rod is bent past a certain point, such as when spaghetti is snapped in half by bending it at the ends, a "snapback effect" is created. This causes energy to reverberate from the initial break to other parts of the rod, often leading to a second break elsewhere.</p><p>While this settled the issue of <em>why </em>spaghetti noodles break into three or more pieces, it didn't establish if they always had to break this way. The question of if the snapback could be regulated remained unsettled.</p>
Physicists, being themselves, immediately wanted to try and break pasta into two pieces using this info<p><a href="https://roheiss.wordpress.com/fun/" target="_blank">Ronald Heisser</a> and <a href="https://math.mit.edu/directory/profile.php?pid=1787" target="_blank">Vishal Patil</a>, two graduate students currently at Cornell and MIT respectively, read about Feynman's night of noodle snapping in class and were inspired to try and find what could be done to make sure the pasta always broke in two.</p><p><a href="http://news.mit.edu/2018/mit-mathematicians-solve-age-old-spaghetti-mystery-0813" target="_blank">By placing the noodles in a special machine</a> built for the task and recording the bending with a high-powered camera, the young scientists were able to observe in extreme detail exactly what each change in their snapping method did to the pasta. After breaking more than 500 noodles, they found the solution.</p>
The apparatus the MIT researchers built specifically for the task of snapping hundreds of spaghetti sticks.
(Courtesy of the researchers)
What possible application could this have?<p>The snapback effect is not limited to uncooked pasta noodles and can be applied to rods of all sorts. The discovery of how to cleanly break them in two could be applied to future engineering projects.</p><p>Likewise, knowing how things fragment and fail is always handy to know when you're trying to build things. Carbon Nanotubes, <a href="https://bigthink.com/ideafeed/carbon-nanotube-space-elevator" target="_self">super strong cylinders often hailed as the building material of the future</a>, are also rods which can be better understood thanks to this odd experiment.</p><p>Sometimes big discoveries can be inspired by silly questions. If it hadn't been for Richard Feynman bending noodles seventy years ago, we wouldn't know what we know now about how energy is dispersed through rods and how to control their fracturing. While not all silly questions will lead to such a significant discovery, they can all help us learn.</p>
A study looks at the performance benefits delivered by asthma drugs when they're taken by athletes who don't have asthma.
- One on hand, the most common health condition among Olympic athletes is asthma. On the other, asthmatic athletes regularly outperform their non-asthmatic counterparts.
- A new study assesses the performance-enhancement effects of asthma medication for non-asthmatics.
- The analysis looks at the effects of both allowed and banned asthma medications.
WADA uncertainty<img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yMzUzNzU0OS9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTYxMDc4NjUwN30.fFTvRR0yJDLtFhaYiixh5Fa7NK1t1T4CzUM0Yh6KYiA/img.jpg?width=980" id="01b1b" class="rm-shortcode" data-rm-shortcode-id="2fd91a47d91e4d5083449b258a2fd63f" data-rm-shortcode-name="rebelmouse-image" alt="urine sample for drug test" />
Image source: joel bubble ben/Shutterstock<p>When inhaled β-agonists first came out just before the 1972 Olympics, they were immediately banned altogether by the WADA as possible doping substances. Over the years, the WADA has reexamined their use and refined the organization's stance, evidence of the thorniness of finding an equitable position regarding their use. As of January 2020, only three β-agonists are allowed — salbutamol, formoterol, and salmeterol —and only in inhaled form. Oral consumption appears to have a greater effect on performance.</p>
The study<img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yMzUzNzU0Ny9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTY1MTIzMDQyMX0.Gk4v-7PCA7NohvJjw12L15p7SumPCY0tLdsSlMrLlGs/img.jpg?width=980" id="d3141" class="rm-shortcode" data-rm-shortcode-id="ebe7b30a315aeffcb4fe739095cf0767" data-rm-shortcode-name="rebelmouse-image" alt="runner at starting position on track" />
Image source: MinDof/Shutterstock<p>Of primary interest to the authors of the study is confirming and measuring the performance improvement to be gained from β-agonists when they're ingested by athletes who don't have asthma.</p><p>The researchers performed a meta-analysis of 34 existing studies documenting 44 randomized trials reporting on 472 participants. The pool of individuals included was broad, encompassing both untrained and elite athletes. In addition, lab tests, as opposed to actual competitions, tracked performance. The authors of the study therefore recommend taking its conclusions with just a grain of salt.</p><p>The effects of both WADA-banned and approved β-agonists were assessed.</p>
Approved β-agonists and non-asthmatic athletes<img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yMzUzNzU1MC9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTYxMzkxODk0M30.3RssFwk_tWkHRkEl_tIee02rdq2tLuAePifnngqcIr8/img.jpg?width=980" id="39a99" class="rm-shortcode" data-rm-shortcode-id="b1fe4a580c6d4f8a0fd021d7d6570e2a" data-rm-shortcode-name="rebelmouse-image" alt="vaulter clearing pole" />
Image source: Andrey Yurlov/Shutterstock<p>What the meta-analysis showed is that the currently approved β-agonists didn't significantly improve athletic performance among those without asthma — what very slight benefit they <em>may</em> produce is just enough to prompt the study's authors to write that "it is still uncertain whether approved doses improve anaerobic performance." They note that the tiny effect did increase slightly over multiple weeks of β-agonist intake.</p>
Banned β-agonist and non-asthmatic athletes<img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yMzUzNzU1Mi9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTYzNjI3ODU5Mn0.vyoxSE5EYjPGc2ZEbBN8d5F79nSEIiC6TUzTt0ycVqc/img.jpg?width=980" id="de095" class="rm-shortcode" data-rm-shortcode-id="02fdd42dfda8e3665a7b547bb88007ef" data-rm-shortcode-name="rebelmouse-image" alt="swimmer mid stroke" />
Image source: Nejron Photo/Shutterstock<p>The study found that for athletes without asthma, however, the use of currently banned β-agonists did indeed result in enhanced performance. The authors write, "Our meta-analysis shows that β2-agonists improve anaerobic performance by 5%, an improvement that would change the outcome of most athletic competitions."</p><p>That 5 percent is an average: 70-meter sprint performance was improved by 3 percent, while strength performance, MVC (maximal voluntary contraction), was improved by 6 percent.</p><p>The analysis also revealed that different results were produced by different methods of ingestion. The percentages cited above were seen when a β-agonist was ingested orally. The effect was less pronounced when the banned substances were inhaled.</p><p>Given the difference between the results for allowed and banned β-agonists, the study's conclusions suggest that the WADA has it about right, at least in terms of selection of allowable β-agonists, as well as the allowable dosage method.</p>
Takeaway<p>The study, say its authors, "should be of interest to WADA and anyone who is interested in equal opportunities in competitive sports." Its results clearly support vigilance, with the report concluding: "The use of β2-agonists in athletes should be regulated and limited to those with an asthma diagnosis documented with objective tests."</p>
Certain water beetles can escape from frogs after being consumed.
- A Japanese scientist shows that some beetles can wiggle out of frog's butts after being eaten whole.
- The research suggests the beetle can get out in as little as 7 minutes.
- Most of the beetles swallowed in the experiment survived with no complications after being excreted.