Preventing a Honeybee Fallout

05/14/17 • 17 min

What would the world look like without honeybees? In theory, if there were no honeybees, it could drastically change our lives. Bjorn Lagerman, though, never wants to know the actual answer to that question. but the honeybees current worst foe, Varroa Destructor, is killing off honeybee hives at intense rates. Bjorn's in the middle of a machine learning project to save the bees from the vampirish Varroa.Below is a partial transcript. For the full interview, listen to the podcast episode by selecting the Play button above or by selecting this link or you can also listen to the podcast through iTunes, Google Play, Stitcher, and Overcast.Bjorn Lagerman: “My name is Bjorn Lagerman. I live in the middle of Sweden. When I look back in my younger days, I remember, I sat in school, looked outside the window and decided I wanted to be outside. You know, I was raised in a stone desert in the middle of Stockholm in the old town; that's a medieval town. And inside the blocks, there were sort of an oasis of water and fountains and green in this stone desert, but the streets were very old streets. And then the contrast was that in the summertime, I spent that in the countryside, and that was total freedom—you kow, lakes, rivers, forests, and my parents let us do what we wished during all the days, just come home for dinner. So when I was 22, I thought bees might be a reason to spend more time in nature. So I went to the nearest beekeeper, . . . and he sold me my first colony, and from there on, I was really hooked.”Ginette: “I’m Ginette.”Curtis: “And I’m Curtis.”Ginette: “And you are listening to Data Crunch.”Curtis: “A podcast about how data and prediction shape our world.”Ginette: “A Vault Analytics production.”Curtis: “This episode is brought to you by data.world, the social network for data people. Discover and share cool data, connect with interesting people, and work together to solve problems faster at data.world. A complex dataset with a ton of files can quickly become scary and unwieldy, but you need not fear! Now you can use file labels and descriptions to manage and organize your many files on data.world. With file labels and descriptions, you can quickly see what type of file it is, view a short description, and also filter down by file type. Wanna see an example of how data.world users are using file labels and descriptions to keep their dataset organized? Search ‘data4democracy/drug-spending’ on data.world.”Ginette: “Imagine for a minute what the world would look like without bees. The image is potentially pretty bleak: we’d have much less guacamole, fruit smoothies, chocolate everything, various vegetables, pumpkin pie, peach cobbler, almond butter, cashews, watermelons, coconuts, lemon, limes, and many more food products. Let’s not forget the obvious—we wouldn’t have honey, which man can’t replicate well. “But fruits, vegetables, and chocolate aren’t the only food stuffs that would be affected. Bees support other animal life. They pollinate alfalfa, which helps feed dairy cows and boost their milk production, and on a more limited basis, alfalfa helps feed beef cows, sheep, and goats. Statistics vary, but bee pollination affects somewhere between one to two thirds of food on American’s plates. Beyond food, bees help grow cotton, so without bees, we’d have to rely more on synthetics for our cloth.“Honeybees in particular are incredibly hard workers. They pollinate 85 percent of all flowering plants. They collect from just one flower specie at a time, and in turn, the pollen they carry fertilizes the flower’s egg cells. One industrious honeybee worker can pollinate up to 5,000 flowers a day. One honeybee hive worth of workers can visit up to 500 million flowers a year. “With a reduced bee population, it gets harder to produce food. Let’s take an example. California grows 85 percent of the world’s almonds, and it takes at least 1.7 million hives to pollinate them,

Previous Episode

When a Picture Is Worth a Life

What if you found out your infant had eye cancer? That news would rock anyone’s world. But what if you had a tool that helped you catch it early enough that your baby didn’t have to lose his or her eye and didn’t have to go through chemo? You’d probably do almost anything to get it. Bryan Shaw has dedicated his time to helping parents detect this cancer sooner so their children don't have to go through what his son went through—and he’s doing it for free. With computer scientists from Baylor University, he's harnessed the power of a machine learning algorithm to detect cancer that no human eye can detect.Below is a partial transcript. For the full interview, listen to the podcast episode by selecting the Play button above or by selecting this link or you can also listen to the podcast through iTunes, Google Play, Stitcher, and Overcast. Bryan Shaw: “The very first person who ever contacted me because our app helped them was a gentleman in Washington State, and his little girl had myelin retinal nerve fiber layer, which is an abnormal myelination of the retina, and it can cause blindness, but it presents with white eye. And his little girl was five years old, and he kept seeing white-eye pics. He heard our story. He downloaded our app. Our app detected the white-eye pics. That emboldened him enough to grill the child's doctor. You know, 'My camera's telling me this. Look, this app. I heard this story . . .’ The doctor takes a close look. The girl had been 75 percent blind in one of her eyes for years, and nobody had ever caught it.”Ginette: “I’m Ginette.”Curtis: “And I’m Curtis.”Ginette: “And you are listening to Data Crunch.”Curtis: “A podcast about how data and prediction shape our world.”Ginette: “A Vault Analytics production.”Curtis: “Data Crunch is again brought to you by data.world, the social network for data people. Discover and share cool data, connect with interesting people, and work together to solve problems faster at data.world. Did you know that you can add files via URL to your data sets on data.world? Data.world APIs allow you to pull live survey data into your data set, enable automatic file updates, and more. Get the full details on data.world APIs at docs.data.world, or search ‘Austin Cycling Survey’ on data.world to see live survey sync in action in Rafael Pereira's data set!”Ginette: “One quick reminder that our data competition is currently up on data.world. Be sure to post your submissions by May 5.“Okay, now back to the story. If you know someone who’s about to have a child, has a child five or under, or plans to have children, you need to send them this episode, and you’re about to find out why from this man, Bryan Shaw.”Bryan: “When Noah was three-months-old, we started noticing that a lot of his pictures had white pupillary reflections, what doctors call leukocoria, white core, white pupil, and that can be a symptom of a lot of different eye diseases.”Ginette: “You probably put this together, but Noah is Bryan’s son. And to add in Noah’s mom’s perspective here, when she started noticing this strange white reflection in Noah’s eyes, like most moms today, she aggressively searched the Internet for answers. Like Bryan said, leukocoria could indicate a disease, or it could indicate nothing, but the Shaws decided they needed to tell their pediatrician about what they’d found.”Bryan: “Noah passed all his red reflex tests, until we told his pediatrician that we noticed leukocoria, and he had a very good pediatrician—Pearl Riney, Cambridge, Massachusetts. And then she really looked really, really closely. And on that test, she noticed a white pupillary reflection and immediately sent us that afternoon to an opthamologist.”Ginette: “At this point, Bryan’s wife, Elizabeth, was freaking out because she’d done all the research about leukocoria, or white eye, and she knew what white eye might mean for their four-month-old son.”Bryan: “In Noah's case,

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How Artificial Intelligence Might Change Your World

What does the creation of new artificial intelligence products look like today, and what do experts in this field foresee realistically happening in the near future? One thing's for sure, the way we work and function in life will change as a result of growth in this field. Listen and find out more.Below is a partial transcript. For the full interview, listen to the podcast episode by selecting the Play button above or by selecting this link or you can also listen to the podcast through Apple Podcasts, Google Play, Stitcher, and Overcast.TranscriptIrmak Sirer: “It’s kind of like a Where’s Waldo of finding an expert in this entire giant ocean of people.” Ginette: “I’m Ginette.”Curtis: “And I’m Curtis.”Ginette: “And you are listening to Data Crunch.”Curtis: “A podcast about how data and prediction shape our world.”Ginette: “A Vault Analytics production.”Curtis: “Brought to you by data.world, the social network for data people. Discover and share cool data, connect with interesting people, and work together to solve problems faster at data.world. A complex dataset with a ton of files can quickly become scary and unwieldy, but you need not fear! Now you can use file labels and descriptions to manage and organize your many files on data.world. With file labels and descriptions, you can quickly see what type of file it is, view a short description, and also filter down by file type. Wanna see an example of how data.world users are using file labels and descriptions to keep their dataset organized? Search "data4democracy/drug-spending" on data.world.Ginette: “Today we’re taking a closer look at something that is starting to seep into our daily lives. In one of its forms, it’s something Stephen Hawking, Bill Gates, and Elon Musk are concerned will eventually be a threat to mankind. In another form, though, you’re probably already using it, and it’s becoming a major game changer, kind of like the early days of the desktop computer. We’re talking about artificial intelligence. You use AI when you talk to Siri or your in-home assistant, Alexa or Echo, and some people are using it in the form of a self-driving car. “So daily applications of artificial intelligence are on the rise, becoming much more of a staple in our society, but AI’s definition shifts according to the source. Popular movies depict AI as having a consciousness, emotions, and exhibiting human-like characteristics. Usually it’s involved in some sort of world-domination plot to kill all the humans. Although most experts agree that artificial intelligence will never actually think and feel like a human, the existential threat still exists. This kind of apocalyptic AI is known as ‘general AI.’ But that’s a topic for another episode. Today, we’re focusing on the kind of AI that currently exists, otherwise known as narrow AI.”Curtis: “A narrow AI is called narrow because it’s usually focused on one specific task, where as a general AI would be able to be good pretty much any task thrown its way. The Google search bar is probably the most ubiquitous example of a narrow AI that most people use on a daily basis. The process usually goes like this: you give it an input like ‘How to own a llama as a pet.’ It does its processing. It gives you an output in the form of the 10 most relevant web pages to answer your questions (along, of course, with some paid advertisers who are trying to sell you a pet llama).“The simplicity of the interaction belies the complexity of the cognitive work that’s going on behind the scenes. Imagine if you had to do the same cognitive task without the help of Google. What would that actually entail? You would have to individually look at and read every single website, and there are over 1 billion, and peruse them to see if they have anything to do about llamas, not to mention then find the individual pages on those websites that actually answer your questions. “This is a really big task!