Facial recognition technology is mostly associated with uses such as surveillance and the authentication of human faces, but scientists believe they've found a new use for it -- saving seals. A research team at Colgate University has developed SealNet, a database of seal faces created by taking pictures of dozens of harbor seals in Maine's Casco Bay. The team found the tool's accuracy in identifying the marine mammals is close to 100%, which is no small accomplishment in an ecosystem home to thousands of seals. The researchers are working on expanding their database to make it available to other scientists, said Krista Ingram, a biology professor at Colgate and a team member. Broadening the database to include rare species such as the Mediterranean monk seal and Hawaiian monk seal could help inform conservation efforts to save those species, she said.

Today's world is full of opportunities for software engineers and programmers. But the skills needed to be successful today are different from decades ago. Python seems to be the "hot" language, but why? Coders are expected to write code that is freer from bugs than in the past. To learn more about the challenges facing modern software practitioners, Design News reached out to two veterans in the space: Larry Smithmier, Practice Lead, Consultant, at Cognizant Softvision, and Anders Holmberg, Chief Technology Officer at IAR Systems. Here is a portion of that discussion. Design News: What skills do software engineers and programmers need to succeed now and in the near future?

Anyone working in data management and data science can attest to the challenge and time-consuming nature of mapping a set of data from a new source into a platform where it can be cleaned, validated, and ultimately analyzed and used to train algorithms. After all, your algorithms are only as good as the data used to train them. Now imagine if these data sets are coming from hundreds of external users who have employed any number of systems to collect this data, from Excel files to actual shoeboxes full of photos. That is the challenge that non-profit wildlife conservation machine learning and artificial intelligence service provider Wild Me has faced over its more than a decade of operation. The organization builds open software and AI for the conservation research community.

To the untrained eye, zebras in Kenya probably all look alike. But each animal's black and white markings are like a fingerprint, distinct -- and invaluable for scientists who need to track the animals and information about them, including their births, deaths, health and migration patterns. Traditionally, getting this kind of information has been an invasive and labor-intensive process. But breakthroughs in artificial intelligence (AI) and crowdsourcing of photos of individual animals are beginning to change the conservation game. Portland, Oregon-based nonprofit Wild Me has developed AI to pick out identifying markers -- the stripes on a zebra, the spots on a giraffe, the contours of a flukewhale's fin -- and catalog animals much faster than a human can.

Give Jason Holmberg 10,000 zebra photos and he'll find the specific individual zebra you're looking for, no problem. "It could take two minutes," he said. Holmberg is executive director of the nonprofit Wild Me. The Portland-based organization has developed a digital tool called Wildbook that uses artificial intelligence and machine learning to expedite wildlife identification. In tandem with citizen science, Wildbook is able to condense years of human work -- like photographing thousands of animals and identifying each by hand -- into a matter of weeks.

Give Jason Holmberg 10,000 zebra photos and he'll find the specific individual zebra you're looking for, no problem. "It could take two minutes," he said. Holmberg is executive director of the nonprofit Wild Me. The Portland-based organization has developed a digital tool called Wildbook that uses artificial intelligence and machine learning to expedite wildlife identification. In tandem with citizen science, Wildbook is able to condense years of human work -- like photographing thousands of animals and identifying each by hand -- into a matter of weeks.

Give Jason Holmberg 10,000 zebra photos and he'll find the specific individual zebra you're looking for, no problem. "It could take two minutes," he said. Holmberg is executive director of the nonprofit Wild Me. The Portland-based organization has developed a digital tool called Wildbook that uses artificial intelligence and machine learning to expedite wildlife identification. In tandem with citizen science, Wildbook is able to condense years of human work -- like photographing thousands of animals and identifying each by hand -- into a matter of weeks.

Conservationists use data collecting technologies and artificial intelligence to turn whale watching into scientific research, gathering photos of whale encounters from citizen scientists to help protect the mammals. After centuries of whaling and habitat destruction, saving whales is one of modern science's great ambitions. Researchers are turning to technology like artificial intelligence (AI), cloud computing and crowd sourced data to better understand and protect these magnificent, mysterious creatures. Increasingly, research biologists use digital technologies to help track, document and analyze animal populations and their migrations. The technology even enables weekend whale watchers to become citizen scientists in whale tracking.

When it comes to Big Data, machines can only do so much. At least that's what startup Spare5 Inc. is betting with the launch of what it calls an "Intelligent Crowdsourcing Platform" that leverages a community of specialists to process Big Data tasks that require a human touch. Crowdsourcing services today run the gamut from the mundane (Amazon.com's Spare5 sits somewhere in the middle, but its special sauce is a machine learning algorithm that rates the skills and preferences of crowd members. The platform is useful for "pretty much anything that involves getting structured data out of unstructured data," said Matt Bencke, founder and CEO.