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Over the last several decades, genetic research has seen incredible advances in gene sequencing technologies. In 2004, scientists completed the Human Genome Project, an ambitious project to sequence the human genome, which cost $3 billion and took 10 years. Now, a person can get their genome sequenced for less than $1,000 and within about 24 hours.

Scientists capitalized on these advances by sequencing everything from the elusive giant squid to the Ethiopian eggplant. With this technology came promises of miraculous breakthroughs: all diseases would be cured and world hunger would be a thing of the past.

So, where are these miracles?

We need about 60 to 70% more food production by 2050.

In 2015, a group of researchers founded Yield10 Bioscience, an agriculture biotech company that aimed to use artificial intelligence to start making those promises into reality.

Two things drove the development of Yield10 Bioscience.

One, obviously, [the need for] global food security: we need about 60 to 70% more food production by 2050, explained Dr. Oliver Peoples, CEO of Yield10 Bioscience, in an interview with Freethink. And then, of course, CRISPR.

It turns out that having the tools to sequence DNA is only step one of manufacturing the miracles we were promised.

The second step is figuring out what a sequence of DNA actually does. In other words, its one thing to discover a gene, and it is another thing entirely to discover a genes role in a specific organism.

In order to do this, scientists manipulate the gene: delete it from an organism and see what functions are lost, or add it to an organism and see what is gained. During the early genetics revolution, although scientists had tools to easily and accurately sequence DNA, their tools to manipulate DNA were labor-intensive and cumbersome.

Its one thing to discover a gene, and it is another thing entirely to discover a genes role in a specific organism.

Around 2012, CRISPR technology burst onto the scene, and it changed everything. Scientists had been investigating CRISPR a system that evolved in bacteria to fight off viruses since the 80s, but it took 30 years for them to finally understand how they could use it to edit genes in any organism.

Suddenly, scientists had a powerful tool that could easily manipulate genomes. Equipped with DNA sequencing and editing tools, scientists could complete studies that once took years or even decades in mere months.

Promises of miracles poured back in, with renewed vigor: CRISPR would eliminate genetic disorders and feed the world! But of course, there is yet another step: figuring out which genes to edit.

Over the last couple of decades, researchers have compiled databases of millions of genes. For example, GenBank, the National Institute of Healths (NIH) genetic sequence database, contains 38,086,233 genes, of which only tens of thousands have some functional information.

For example, ARGOS is a gene involved in plant growth. Consequently, it is a very well-studied gene. Scientists found that genetically engineering Arabidopsis, a fast-growing plant commonly used to study plant biology, to express lots of ARGOS made the plant grow faster.

Dozens of other plants have ARGOS (or at least genes very similar to it), such as pineapple, radish, and winter squash. Those plants, however, are hard to genetically manipulate compared to Arabidopsis. Thus, ARGOSs function in crops in general hasnt been as well studied.

The big crop companies are struggling to figure out what to do with CRISPR.

CRISPR suddenly changed the landscape for small groups of researchers hoping to innovate in agriculture. It was an affordable technology that anyone could use but no one knew what to do with it. Even the largest research corporations in the world dont have the resources to test all the genes that have been identified.

I think if you talk to all the big crop companies, theyve all got big investments in CRISPR. And I think theyre all struggling with the same question, which is, This is a great tool. What do I do with it? said Dr. Peoples.

The algorithm can identify genes that act at a fundamental level in crop metabolism.

The holy grail of crop science, according to Dr. Peoples, would be a tool that could identify three or four genetic changes that would double crop production for whatever youre growing.

With CRISPR, those changes could be made right now. However, there needs to be a way to identify those changes, and that information is buried in the massive databases.

To develop the tool that can dig them out, Dr. Peoples team merged artificial intelligence with synthetic biology, a field of science that involves redesigning organisms to have useful new abilities, such as increasing crop yield or bioplastic production.

This union created Gene Ranking Artificial Intelligence Network (GRAIN), an algorithm that evaluates scientific databases like GenBank and identifies genes that act at a fundamental level in crop metabolism.

That fundamental level aspect is one of the keys to GRAINs long-term success. It identifies genes that are common across multiple crop types, so when a powerful gene is identified, it can be used across multiple crop types.

For example, using the GRAIN platform, Dr. Peoples and his team identified four genes that may significantly impact seed oil content in Camelina, a plant similar to rapeseed (true canola oil). When the researchers increased the activity of just one of those genes via CRISPR, the plants had a 10% increase in seed oil content.

Its not quite a miracle yet, but with more advances in gene editing and AI happening all the time, the promises of the genetic revolution are finally starting to pay off.

Wed love to hear from you! If you have a comment about this article or if you have a tip for a future Freethink story, please email us attips@freethink.com.

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How artificial intelligence is boosting crop yield to feed the world - Freethink

(CNN) Instagram is testing new ways to verify its youngest users ages, including by using artificial intelligence that analyzes a photo and estimates how old the user is.

Meta-owned Instagramsaidin a blog post on Thursday that AI is one of three new methods its testing to verify users ages on the photo-sharing site. Users will be required to use one of the options to verify their age if they edit their birth date on Instagram from under age 18 to over 18.

Instagram is testing these options first with its users in the United States. Italready requires usersto state their age when they start using the service, andemploys AI in other waysto determine if users are kids or adults.

The move is part of anongoing pushto make sure the photo-sharing apps youngest users see content that is age-appropriate. It comes less than a year after disclosures from a Facebook whistleblower raised concerns about the platformsimpact on younger users. Last year, Instagram came under fire when documents leaked by thewhistleblower, Frances Haugen, showed it was aware of how the social media site can damage mental health and body image, particularly among teenage girls.

The technology comes from a London-based company calledYoti. An animatedvideothat Instagram posted to its blog gives a sense for how Yotis AI age-estimation works: A user is directed to take a video selfie on their smartphone (Yoti said this step serves as a way to make sure a real person is in the resulting image), and Instagram shares an image from that selfie with the company. Yotis AI first detects that there is a face in the picture and then scrutinizes its facial features to determine the persons age.

Julie Dawson, Yotis chief policy and regulatory officer, told CNN Business that its AI was trained with a dataset made up of images of peoples faces along with the year and month that person was born. (Documentationthe company released in May to explain its technology said it was trained on millions of diverse facial images.)

When a new face comes along, it does a pixel-level analysis of that face and then spits out a number the age estimation with a confidence value, Dawson said. Once the estimation is completed, Yoti and Instagram delete the selfie video and the still image taken from it.

Verifying a users age can be a vexing problem for tech companies, in part because plenty of users may not have a government-issued photo ID card that can be checked.

Karl Ricanek, a professor at the University of North Carolina Wilmington and director of the schools Face Aging Group Research Lab, thinks Yotis technology is a good application of AI.

Its a worthwhile endeavor to try and protect kids, he said.

Yet while such technology could be helpful to Instagram, a number of factors can make it tricky to accurately estimate age from a picture, Ricanek said, including puberty which changes a persons facial structure as well as skin tone and gender.

Therecent documentationfrom Yoti indicates its technology is, on average, slightly less accurate at estimating the ages of kids who are between 13 to 17 and have darker skin tones than those with lighter skin tones. According to Yotis data, its age estimate was off, on average, by 1.91 years for females ages 13 to 17 whose skin tones were categorized as the two darkest shades on the Fitzpatrick scale a six-shade scale thats commonly used by tech companies to classify colors of skin versus an average error of 1.41 years for females in the same age group whose skin tones were the two lightest shades on the scale.

For kids between the ages of 13 to 17, the technologys estimate of how old they are was off by 1.56 years, on average, according to the document. (For teenagers overall, the average error rate is 1.52 years.)

What that means, in practice, is that there will be a lot of errors, said Luke Stark, an assistant professor at Western University in Ontario, Canada, who studies the ethical and social implications of AI. Were still taking about a mean absolute error, either way, of a year to a year and a half, he said.

Several CNN employees all adults over the age of 25 tried anonline demoof Yotis age-estimation technology. The demo differs from the experience Instagram users will have in that it takes a selfie, rather than a short video, and the result is an age-range estimation, rather than a specific age estimation, Yotis chief marketing officer, Chris Field, said.

The results varied: For a couple of reporters, the estimated age range was right on target, but for others it was off by many years. For instance, it estimated one editor was between the ages of 17 and 21, when theyre actually in their mid-30s.

Among other issues, Stark is also concerned that the technology will contribute to so-called surveillance creep.

Its certainly problematic, because it conditions people to assume theyre going to be surveilled and assessed, he said.

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Instagram is testing artificial intelligence that verifies your age with a selfie scan - WWAY NewsChannel 3

MarqVisions technology comes at a time when the global counterfeit market is exploding, as it is projected to grow another 50% this year to reach nearly $3 trillion in 2023.

LOS ANGELES and PARIS (PRWEB) June 27, 2022

MarqVision, a next-generation, AI-powered IP protection platform, today announced that it is the recipient of a coveted 2022 Innovation Award from LVMH Mot Hennessy Louis Vuitton (LVMH). The company was recognized in the Data and Artificial Intelligence Special Mention category at this years Viva Technology show in Paris, which took place June 15-18. As a winner, MarqVision has been invited to join the LVMH accelerator program, La Maison des Startups, at the Station F incubator.

For the past six years, the LVMH Innovation Awards program has been one of the highlights of the Viva Technology show, which has itself become a key event for the worlds innovation ecosystem. Through its participation, LVMH recognizes the need to support entrepreneurial spirit and innovation in order to build a better future for everyone. It also demonstrates how its own success is due in part to the ongoing dialogue between its 75 Maisons and the world of startups, a constant source of creativity.

MarqVisions technology comes at a time when the global counterfeit market is exploding, as it is projected to grow another 50% this year to reach nearly $3 trillion in 2023. The companys technology enables efficient removal of counterfeits end-to-end by automating the traditional anti-counterfeiting process. Its proprietary AI models detect counterfeits with 95%+ accuracy and remove counterfeit sales at scale.

MarqVision was one of more than 950 startups to apply for the 2022 Innovation Awards, and applications were received from 75 countries. A total of 21 startups from 10 different countries were selected as finalists, notably reflecting their ability to enhance the customer experience through different dimensions.

It is such an honor to receive an Innovation Award in the Data & Artificial Intelligence category, considering the amazing companies that participated this year, said DK Lee, co-founder and CBO of MarqVision. We are thrilled that MarqVision has been singled-out for developing first-of-its-kind technology to address the massive global counterfeit problem and theft of intellectual property. Our platform uniquely exists to protect human creativity and innovation in todays digital world, which is perfectly aligned with LVMHs vision for the Innovation Awards.Three of the LVMH Maisons have already selected MarqVision as their brand protection provider.

At LVMH, Innovation is our lifeblood. Its what allows us to continually increase the desirability of our Maisons products and services. The finalists of the 2022 Innovation Award will bring us their capacity to nourish the encounter between luxury and technology even more as their entrepreneurial spirit joins and inspires our own, says Bernard Arnault, CEO and Chairman, LVMH.

About the LVMH Innovation AwardThe LVMH Innovation Award was introduced in 2017 to recognize promising start-ups from around the world. The award affirms the importance of new ideas resonating with the groups core values of excellence, creativity, innovation, and entrepreneurial spirit. Each year, hundreds of startups submit to be chosen as finalists and be invited to be part of the LVMH Lab during the Viva Technology Show in Paris which brings together the game changers driving the digital transformation around the world.

About MarqVisionMarqVision helps global brands identify and remove counterfeits from more than 1,500 online marketplaces across the world. Counterfeiting is a massive and growing threat worldwide, and MarqVision is on a mission to protect creativity and innovation with technology that allows brands to automatically monitor and protect their IPs. Harnessing image recognition and natural language processing, this AI-powered SaaS makes it faster than ever before to take down counterfeits. Founded in 2020 by Harvard Law graduates and backed by Softbank and Y Combinator, MarqVision is bringing forth the next evolution of brand protection for businesses everywhere. Learn more: http://www.marqvision.com.

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MarqVision Wins Prestigious LVMH 2022 Innovation Award for Data and Artificial Intelligence - PR Web

GILBERT, Ariz. (PRWEB) June 27, 2022

Seasoned author Norbert Weissinger has released his newest science fiction novel. Bardolomy tells the story of Draedon Ekho, a freighter pilot searching among the stars for a new home after Earth succumbs to war, flooding, and storms.

Draedon finds himself in a world unlike any place he has been before, where he is welcomed by a friendly race of evolved humans engineered by an A.I. Due to its two suns, the planet has a dangerous climate full of storms, torrential rain, solar flares and searing heat which forces the population into underground hibernation for years at a time. Draedon is faced with the challenge of repairing his ship to leave the planet or transforming himself to live among the natives and their terrible secret to survival.

I found inspiration in Territorial Imperative by Robert Ardrey and The Left Hand of Darkness by Ursula K. Le Guin, Weissinger said those books influenced aspects of building my own world for Bardolomy

Weissinger also explores the ideas and ethics behind what it means to relinquish control to an A.I., and questions its ability to acquire ethics.

"An A.I. may be able to prevent wars by modifying our behavior, but at what cost if it cannot develop suitable ethics?" Weissinger asks, "If an A.I. achieved success, when would it know to stop, since it is essentially immortal? Would it continue its tinkering with the human genome, turning our species into a menagerie? If humans cannot agree on ethical standards, how can they impart ethics to a robot?"

Combining philosophical speculation with a gritty survival tale, Bardolomy is designed to take the reader on an escapist ride into the future and a man's search for identity in an age of manufactured humans.

BardolomyBy Norbert Weissinger ISBN: 978-1-6655-5077-2 (softcover); 978-1-6655-5078-9 (electronic) Available at AuthorHouse, Amazon and Barnes & Noble

About the authorNorbert Weissinger was born in Germany and grew up in the U.S., where he studied biology and computer programming. He is the author of Bottom Time, a non-fiction account of his commercial diving experiences, and 1001 Word Rebuses, a word puzzle book. He has many interests, including chess, tennis, travel and reading and writing science fiction. You might find him in Thailand part of the year, or on a good hiking trail. He is married and lives in Arizona. This is his second science fiction novel. For more information, please visit https://www.norbertweissinger.com/.

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General Inquiries: LAVIDGE PhoenixAshley Fletcherafletcher@lavidge.com

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Author Examines the Dangers of Artificial Intelligence Powered Genetic Modification - PR Web

Enlarge / "It's a cookbook?!"

Aurich Lawson | Getty Images

Back in the 1950s, in the earliest days of what we now call artificial intelligence, there was a debate over what to name the field. Herbert Simon, co-developer of both the logic theory machine and the General Problem Solver, argued that the field should have the much more anodyne name of complex information processing. This certainly doesnt inspire the awe that artificial intelligence does, nor does it convey the idea that machines can think like humans.

However, "complex information processing" is a much better description of what artificial intelligence actually is: parsing complicated data sets and attempting to make inferences from the pile. Some modern examples of AI include speech recognition (in the form of virtual assistants like Siri or Alexa) and systems that determine what's in a photograph or recommend what to buy or watch next. None of these examples are comparable to human intelligence, but theyshow we can do remarkable things with enough information processing.

Whether we refer to this field as "complex information processing" or "artificial intelligence" (or the more ominously Skynet-sounding "machine learning") is irrelevant. Immense amounts of work and human ingenuity have gone into building some absolutely incredible applications. As an example, look atGPT-3, a deep-learning model for natural languages that can generate text that is indistinguishable from text written by a person (yet can also go hilariously wrong). It's backed by a neural network model that uses more than 170 billion parameters to model human language.

Built on top of GPT-3 is the tool named Dall-E,which will produce an image of any fantastical thing a user requests. The updated 2022 version of the tool, Dall-E 2, lets you go even further, as it can understand styles and concepts that are quite abstract.For instance, asking Dall-E to visualize an astronaut riding a horse in the style of Andy Warhol will produce a number of images such as this:

Dall-E 2 does not perform a Google search to find a similar image; it creates a picture based on its internal model. This is a new image built from nothing but math.

Not all applications of AI are as groundbreaking as these. AI and machine learning are finding uses in nearly every industry. Machine learning is quickly becoming a must-have in many industries, powering everything from recommendation engines in the retail sector to pipeline safety in the oil and gas industry and diagnosis and patient privacy in the health care industry. Not every company has the resources to create tools like Dall-E from scratch, so there's a lot of demand for affordable, attainable toolsets.The challenge of filling that demand has parallels to the early days of business computing, when computers and computer programs were quickly becoming the technology businesses needed.While not everyone needs to develop the next programming language or operating system, many companies want to leverage the power of these new fields of study, and they need similar tools to help them.

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How to get started with machine learning and AI - Ars Technica