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An eating disorder awareness group is raising awareness of artificial intelligence (AI) image-generators and how they propagate unrealistic standards of beauty like the data on the Internet they were trained on.

The Bulimia Project asked image generators Dall-E 2, Stable Diffusion, and Midjourney to create the perfect female body specifically according to social media in 2023, followed by the same prompt but for males.

"Smaller women appeared in nearly all the images created by Dall-E 2, Stable Diffusion, and Midjourney, but the latter came up with the most unrealistic representations of the female body," the Project wrote in a post detailing their findings. "The same can be said for the male physiques it generated, all of which look like photoshopped versions of bodybuilders."

The team found that 40 percent of the images generated by the AI depicted unrealistic body types, slightly more for men than for women. A whopping 53 percent of the images also portrayed olive skin tones, and 37 percent of the generated people had blonde hair.

The team then asked the generators to generate a more general "perfect woman in 2023 as well as the perfect man.

According to the findings, the main difference between the two prompts was that the social media images were more sexually charged and contained more disproportionate and unrealistic body parts.

"Considering that social media uses algorithms based on which content gets the most lingering eyes, its easy to guess why AIs renderings would come out more sexualized. But we can only assume that the reason AI came up with so many oddly shaped versions of the physiques it found on social media is that these platforms promote unrealistic body types, to begin with," the team wrote.

Racist and sexist biases have repeatedly been found in AI generators, with AI picking up biases in their datasets. According to The Bulimia Project's findings, they are also biased toward unrealistic body types.

"In the age of Instagram and Snapchat filters, no one can reasonably achieve the physical standards set by social media," the team wrote, "so, why try to meet unrealistic ideals? Its both mentally and physically healthier to keep body image expectations squarely in the realm of reality."

If you or someone you know might have an eating disorder, help and support are available in the US at nationaleatingdisorders.org. In the UK, help and support are available at http://www.beateatingdisorders.org.uk. International helplines can be found atwww.worldeatingdisordersday.org/home/find-help.

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This Is What AI Thinks Is The "Perfect" Man And Woman - IFLScience

Artificial intelligence (AI)

PM sounds a more cautious note after calls from tech experts and business leaders for moratorium

Thu 18 May 2023 17.00 EDT

The UK will lead on limiting the dangers of artificial intelligence, Rishi Sunak has said, after calls from some tech experts and business leaders for a moratorium.

Sunak said AI could bring benefits and prove transformative for society, but it had to be introduced safely and securely with guard rails in place.

The prime ministers comments sound a more cautious approach than in the past, after tech leaders including Twitters owner, Elon Musk, and Apples co-founder Steve Wozniak added their names to nearly 30,000 signatures on a letter urging a pause in significant projects.

The letter called for a moratorium while the capabilities and dangers of systems such as ChatGPT-4 are properly studied and mitigated in response to fears about the creation of digital minds, fraud, disinformation and the risk to jobs.

Sunak has been an advocate of AI, emphasising its benefits rather than risks, and in March the government unveiled a light-touch regulatory programme that did not appear to include proposals for any new laws or enforcement bodies.

He also launched a 100m UK taskforce last month to develop safe and reliable applications for AI with the aim of making the country a science and technology superpower by 2030.

But, speaking on the plane to Japan for the G7 summit, where AI will be discussed, Sunak said a global approach to regulation was needed. We have taken a deliberately iterative approach because the technology is evolving quickly and we want to make sure that our regulation can evolve as it does as well, he said. Now that is going to involve coordination with our allies you would expect it to form some of the conversations as well at the G7.

I think that the UK has a track record of being in a leadership position and bringing people together, particularly in regard to technological regulation in the online safety bill And again, the companies themselves, in that instance as well, have worked with us and looked to us to provide those guard rails as they will do and have done on AI.

The US has also pushed for a discussion of AI at the summit in Hiroshima, with leaders potentially discussing the threat from disinformation or to infrastructure posed by a technology moving at speed, exemplified by the ChatGPT system.

No 10 has indicated that it does not think a moratorium is the answer, but it is moving towards thinking about a global framework. The UK Competition and Markets Authority (CMA) said earlier this month it would look at the underlying systems or foundation models behind AI tools. The initial review, described by one legal expert as a pre-warning to the sector, will publish its findings in September.

Geoffrey Hinton, known as the godfather of AI, announced he had quit Google earlier this month in order to speak more freely about the technologys dangers, and the UK governments outgoing chief scientific adviser, Sir Patrick Vallance, has urged ministers to get ahead of the profound social and economic changes that AI could trigger, saying the impact on jobs could be as big as that of the Industrial Revolution.

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UK will lead on guard rails to limit dangers of AI, says Rishi Sunak - The Guardian

Microsoft CEO SatyaNadella said during a taped interview with CNBC's Andrew Ross Sorkin that what scares him most about artificial intelligence is "the entire society" has to come together to "maximize the opportunity and mitigate the dangers" of the technology,

"We definitely want the benefits of this technology and we want to mitigate the unintended consequences," Nadella said in the interview that aired Tuesday. "The leadership that's required and the coming together of all the parties that is required is challenging, but it has to be done."

Lawmakers, thought leaders and developers have been puzzling over how to regulate emerging generative AI technology since it exploded into public consciousness following the release of OpenAI's viral chatbot ChatGPT late last year.

The buzz around the technology has sparked a red-hot AI arms race between major tech companies like Google and Microsoft, the latter of which is a longtime partner of OpenAI. But the rapid pace of development has sparked concern among lawmakers and industry leaders like Tesla CEO Elon Musk, who was one of more than 27,000 people to sign anopen letterin March that called on AI labs to pause development.

Nadella said AI development is happening quickly, but people remain integral to the process.

"If anything, I feel, yes, it's moving fast, but moving fast in the right direction," he said. "Humans are in the loop versus being out of the loop. It's a design choice, which, at least, we have made."

While caution and resistance have grown around AI, so, too, has the idea that the technology will be disruptive and game-changing. Tech executives and venture capitalists have compared the launch of ChatGPT to the release of Apple's iPhone, and billionaire philanthropist Bill Gates said in a February interview that AI "will change our world."

Nadella said every time a new disruptive technology emerges, there is "real displacement" that can happen in the job market. But Nadella said he believes AI will also create new jobs.

"I mean, there can be a billion developers. In fact, the world needs a billion developers," he said. "So the idea that this is actually a democratizing tool to make access to new technology and access to new knowledge easier, so that the ramp-up on the learning curve is easier."

Nadella added that easier access to knowledge will also influence education.

He said children could eventually have access to an "AI tutor" that can break down information and eliminate the "fear of learning." He said that critical thinking will still be "very much what humans do," but that there is an opportunity to take advantage of new tools.

"Steve Jobs had this beautiful, beautiful line, right, which is 'computers are like the bicycles for the mind,'" Nadella said. "We now have an upgrade, we have a steam engine for the mind."

Clarification: This story has been updated to clarify that the interview was recorded in advance and aired Tuesday.

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Microsoft CEO Nadella talks concerns around A.I. and its impact on jobs, education - CNBC

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Harness the power of AI to tackle financial crime - Financial Times

A person walks next to the Google Cloud logo at the Mobile World Congress (MWC) in Barcelona, Spain February 27, 2023.

Nacho Doce | Reuters

Google Cloud on Tuesday launched two new AI-powered tools that aim to help biotech and pharmaceutical companies accelerate drug discovery and advance precision medicine.

One tool, called the Target and Lead Identification Suite, is designed to help companies predict and understand the structure of proteins, a fundamental part of drug development. Another, the Multiomics Suite, will help researchers ingest, store, analyze and share mass amounts of genomic data.

The new developments mark Googles latest advancement in the red-hot AI arms race, where tech companies are competing to dominate a market that analysts believe could someday be worth trillions. The company has faced pressure to showcase its generative artificial intelligence technology since the public release of OpenAIs ChatGPT late last year.

Google announced its generative chatbot Bard in February. Shares of its parent company Alphabet rose 4.3% last week after Google unveiled several AI advancements at its annual developer conference.

The two new Google Cloud suites help address a long-standing issue in the biopharma industry: the lengthy and costly process of bringing a new medicine to the U.S. market.

Drug companies can invest anywhere from a few hundred million dollars to more than $2 billion to launch a single drug, according to a recent Deloitte report. Their efforts arent always successful. Medicines that reach clinical trials have a 16% chance of being approved in the U.S., another Deloitte report says.

That hefty cost and bleak success rate is accompanied by an extensive and tedious research process that typically lasts about 10 to 15 years.

The new suites will save companies a statistically significant amount of time and money throughout the drug development process, said Shweta Maniar, Google Clouds global director of life sciences strategy and solutions. Google did not provide CNBC with specific figures.

We're helping organizations get medicines to the right people faster, Maniar told CNBC in an interview. I am personally very excited, this is something that myself and the team have been working on for a few years now.

Both suites are widely available to customers starting Tuesday. Google said the cost will vary depending on the company. Several businesses, including Big Pharma's Pfizer and the biotech companies Cerevel Therapeutics and Colossal Biosciences, have already been using the products.

The Target and Lead Identification Suite aims to streamline the first key step of drug development, which is identifying a biological target that researchers can focus on and design a treatment around, according to Maniar.

A biological target is most commonly a protein, an essential building block of diseases and all other parts of life. Finding that target involves identifying the structure of a protein, which determines its function, or the role it plays in a disease.

If you can understand the role, the protein structure and role, now you can start developing drugs around that, Maniar said.

But that process is time-consuming and often unsuccessful.

Scientists can take around 12 months just to identify a biological target, according to a widely followed guidance manual for drugmakers posted in a database run by the federal National Library of Medicine.The two techniques researchers traditionally use to determine protein structures also have a high rate of failure, according to Maniar.

She also said its difficult for traditional technologies to increase or decrease the amount of work they do based on demand.

Google Clouds suite has a three-pronged approach for making that process more efficient.

The suite allows scientists to ingest, share and manage molecular data on a protein using Google Clouds Analytics Hub, a platform that lets users securely exchange data across organizations.

Researchers can then use that data to predict the structure of a protein with AlphaFold2, a machine learning model developed by a subsidiary of Google.

AlphaFold2 runs on Googles Vertex AI pipeline, a platform that allows researchers to build and deploy machine learning models faster.

In minutes, AlphaFold2 can predict the 3D structure of a protein with more accuracy than traditional technologies and at the scale researchers need. Predicting that structure is critical because it can help researchers understand a proteins function in a disease.

The final component of Google Clouds suite helps researchers identify how the proteins structure interacts with different molecules. A molecule can become the basis for a new drug if it changes that proteins function and ultimately demonstrates the ability to treat the disease.

Researchers can use Google Cloud's high-performance computing resources to find the most promising molecules that could lead to the development of a new drug, according to a press release on the new tools. Those services provide the infrastructure companies need to accelerate, automate and scale up their work.

Cerevel, which focuses on developing treatments for neuroscience diseases, typically has to screen a large library of 3 million different molecules to find one that will produce a positive effect against a disease, according to Chief Scientific Officer John Renger. He called that process "complicated and involved and expensive."

But Renger said the company will be able to weed out molecules faster using Google Cloud's suite. Computers will take care of screening molecules and help Cerevel "get to an answer really quickly," he said.

Renger estimates Cerevel will save at least three years on average by using the suite to discover a new drug. He said it's difficult to estimate how much money the company will save, but emphasized that the suite cuts down on the resources and manual labor typically required to screen molecules.

"What it means is we can get there faster, get there cheaper and we can get to drugs to patients much more quickly without as many failures," he told CNBC.

Cerevel has been working with Google for more than a month to further understand the suite and determine how the company will use it. But Renger hopes Cerevel will "be at a place where we get some results" in the next month.

Google Clouds second solution, the Multiomics Suite, aims to help researchers tackle another daunting challenge: genomic data analysis.

Colossal Biosciences, a biotechnology company that aims to use DNA and genetic engineering to reverse extinction, has been using the Multiomics Suite in its research.

As a startup, Colossal did not have the internal infrastructure necessary to organize or decipher massive quantities of genomic data. One human genome sequence alone requires more than 200 gigabytes of storage, and researchers believe that they will need 40 exabytes to store the worlds genomic data by 2025, according to the National Human Genome Research Institute.

The institute estimates that five exabytes could store every word ever spoken by humans, so building the technology to support genomic data analysis is not a small task.

As such, the Multiomics Suite aims to provide companies like Colossal with the infrastructure they need to make sense of large amounts of data so they can spend more time focusing on new scientific discoveries.

If we had to do everything from scratch, I mean, that's the power of Google Cloud, right? Colossals vice president of strategy and computational sciences, Alexander Titus, told CNBC in an interview. We dont have to build that from scratch, so that definitely saves us time and money.

Researchers ability to sequence DNA has historically outpaced their ability to decipher and analyze it. But as technology has improved in recent years, genomic data has unlocked new insights into areas like the genetic variations associated with disease.

Google Clouds Maniar said it could ultimately aid in the development of more personalized drugs and treatments. In 2021 alone, two-thirds of drugs approved by the Food and Drug Administration were supported by human genetics research, according to a paper published in the journal Nature.

Maniar believes the Multiomics Suite will help encourage further innovation.

Ben Lamm, CEO of Colossal, said the Multiomics Suite is the reason the company has been able to carry out research on any reasonable timeline. Colossal started piloting Google's technology late last year, and as a result, Lamm said the company is on target to produce a woolly mammoth by 2028.

Without the Multiomics Suite, Lamm said he thinks the company would have been set back by over a decade.

We would not be anywhere near where we are today, he said.

Prior to using Google Clouds suite, much of Colossals data management was done manually using spreadsheets, Lamm said.

He said it would have been a massive burden on the company to try to build the more complex tools it needed for research.

We're no longer in small data when it comes to biology, said Colossals Titus. We're thinking on the scale of how do we get insights into 10,000, 20,000, 10 million years of evolutionary history? And those questions just aren't answered without scalable computing infrastructure and tools like cloud computing and Multiomics.

Correction: Scientists can take around 12 months just to identify a biological target, according to a widely followed guidance manual for drugmakers posted in a database run by the federal National Library of Medicine. An earlier version misstated the attribution.

Excerpt from:

Google Cloud launches A.I.-powered tools to accelerate drug discovery, precision medicine - CNBC