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Artificial intelligence has exploded across our news feeds, with ChatGPT and related AI technologies becoming the focus of broad public scrutiny. Beyond popular chatbots, biologists are finding ways to leverage AI to probe the core functions of our genes.

Previously, University of California San Diego researchers who investigate DNA sequences that switch genes on used artificial intelligence to identify an enigmatic puzzle piece tied to gene activation, a fundamental process involved in growth, development and disease. Using machine learning, a type of artificial intelligence, School of Biological Sciences Professor James T. Kadonaga and his colleagues discovered the downstream core promoter region (DPR), a "gateway" DNA activation code that's involved in the operation of up to a third of our genes.

Building from this discovery, Kadonaga and researchers Long Vo ngoc and Torrey E. Rhyne have now used machine learning to identify "synthetic extreme" DNA sequences with specifically designed functions in gene activation.

Publishing in the journal Genes & Development, the researchers tested millions of different DNA sequences through machine learning (AI) by comparing the DPR gene activation element in humans versus fruit flies (Drosophila). By using AI, they were able to find rare, custom-tailored DPR sequences that are active in humans but not fruit flies and vice versa. More generally, this approach could now be used to identify synthetic DNA sequences with activities that could be useful in biotechnology and medicine.

"In the future, this strategy could be used to identify synthetic extreme DNA sequences with practical and useful applications. Instead of comparing humans (condition X) versus fruit flies (condition Y) we could test the ability of drug A (condition X) but not drug B (condition Y) to activate a gene," said Kadonaga, a distinguished professor in the Department of Molecular Biology.

"This method could also be used to find custom-tailored DNA sequences that activate a gene in tissue 1 (condition X) but not in tissue 2 (condition Y). There are countless practical applications of this AI-based approach. The synthetic extreme DNA sequences might be very rare, perhaps one-in-a-million if they exist they could be found by using AI."

Machine learning is a branch of AI in which computer systems continually improve and learn based on data and experience. In the new research, Kadonaga, Vo ngoc (a former UC San Diego postdoctoral researcher now at Velia Therapeutics) and Rhyne (a staff research associate) used a method known as support vector regression to train machine learning models with 200,000 established DNA sequences based on data from real-world laboratory experiments. These were the targets presented as examples for the machine learning system. They then fed 50 million test DNA sequences into the machine learning systems for humans and fruit flies and asked them to compare the sequences and identify unique sequences within the two enormous data sets.

While the machine learning systems showed that human and fruit fly sequences largely overlapped, the researchers focused on the core question of whether the AI models could identify rare instances where gene activation is highly active in humans but not in fruit flies. The answer was a resounding "yes." The machine learning models succeeded in identifying human-specific (and fruit fly-specific) DNA sequences. Importantly, the AI-predicted functions of the extreme sequences were verified in Kadonaga's laboratory by using conventional (wet lab) testing methods.

"Before embarking on this work, we didn't know if the AI models were 'intelligent' enough to predict the activities of 50 million sequences, particularly outlier 'extreme' sequences with unusual activities. So, it's very impressive and quite remarkable that the AI models could predict the activities of the rare one-in-a-million extreme sequences," said Kadonaga, who added that it would be essentially impossible to conduct the comparable 100 million wet lab experiments that the machine learning technology analyzed since each wet lab experiment would take nearly three weeks to complete.

The rare sequences identified by the machine learning system serve as a successful demonstration and set the stage for other uses of machine learning and other AI technologies in biology.

"In everyday life, people are finding new applications for AI tools such as ChatGPT. Here, we've demonstrated the use of AI for the design of customized DNA elements in gene activation. This method should have practical applications in biotechnology and biomedical research," said Kadonaga. "More broadly, biologists are probably at the very beginning of tapping into the power of AI technology."

More information: Long Vo ngoc et al, Analysis of the Drosophila and human DPR elements reveals a distinct human variant whose specificity can be enhanced by machine learning, Genes & Development (2023). DOI: 10.1101/gad.350572.123

Journal information: Genes & Development

Originally posted here:
Artificial intelligence catalyzes gene activation research and uncovers rare DNA sequences - Phys.org

A laboratory in Lawrenceville is harnessing the intellectual talent of Pittsburgh's research institutions to target cancer. We speak with a man on a mission to help cancer patients by using artificial intelligence. It starts with the cryogenically frozen tumor. Predictive Oncology CEO Raymond Vennare doesn't like the term tumor to refer to the cancer they study.I refer to them as human beings. These human beings are repurposing their lives for us for a purpose, to be able to find cures to help their descendants; that's their legacy, Vennare said. Vennare is not a scientist. He's a businessman who builds biotech companies. He's had a bullseye on cancer for 15 years.What's different about this venture? The mission: to get cancer drugs that work to market, years faster.And what would have taken three to five years and millions of dollars, we were able to do in a couple of cycles in 11, 12, 13 weeks, Vennare said.In pre-trial drug development tumor heterogeneity, patient heterogeneity isn't introduced early enough, said Amy Ewing, a senior scientist at Predictive Oncology.Translation: Predictive Oncology's scientists are focusing on cell biology, molecular biology, computational biology and bioinformatics to determine how cancer drugs work on real human tumor tissue.A bank of invaluable tumor samples allows them to crunch that data faster.Remember, those samples are people.When I think about cancer, I see their faces, Vennare said. I don't see cells on a computer screen.Vennare sees his brother, Alfred.He was my first best friend. I grew up, Al, Alfred was always there. And whenever I needed something, Alfred was always there.He also thinks of his parents.In my case, my mother and my father and my brother sequentially died of cancer, which means I was the caregiver. My family was the caregiver, my siblings and my sister were caregivers for five consecutive years, he said.Ewing thinks of her father.I lost my father to prostate cancer about a year ago, she said. So to me, I have a deeper understanding now of what it means to have another day, or another month, or another year. I think that's really what gets me up in the morning now is to say that I want to carry on his legacy and help somebody else have more time with their family members.With a board of scientific advisors that includes an astronaut and some of the top scientists in the country, Vennare says ethics is part of the ongoing artificial intelligence conversation."The purpose is to make the job of the scientist easier, so they can expedite the process of discovery, he said. It's not AI that's going to do that, it's the scientists that are going to do that.Venarre says Predictive Oncology is agnostic, meaning this company seeks to help drug companies quickly zero in on effective drugs for all kinds of cancer.

A laboratory in Lawrenceville is harnessing the intellectual talent of Pittsburgh's research institutions to target cancer. We speak with a man on a mission to help cancer patients by using artificial intelligence.

It starts with the cryogenically frozen tumor. Predictive Oncology CEO Raymond Vennare doesn't like the term tumor to refer to the cancer they study.

I refer to them as human beings. These human beings are repurposing their lives for us for a purpose, to be able to find cures to help their descendants; that's their legacy, Vennare said.

Vennare is not a scientist. He's a businessman who builds biotech companies. He's had a bullseye on cancer for 15 years.

What's different about this venture? The mission: to get cancer drugs that work to market, years faster.

And what would have taken three to five years and millions of dollars, we were able to do in a couple of cycles in 11, 12, 13 weeks, Vennare said.

In pre-trial drug development tumor heterogeneity, patient heterogeneity isn't introduced early enough, said Amy Ewing, a senior scientist at Predictive Oncology.

Translation: Predictive Oncology's scientists are focusing on cell biology, molecular biology, computational biology and bioinformatics to determine how cancer drugs work on real human tumor tissue.

A bank of invaluable tumor samples allows them to crunch that data faster.

Remember, those samples are people.

When I think about cancer, I see their faces, Vennare said. I don't see cells on a computer screen.

Vennare sees his brother, Alfred.

He was my first best friend. [When] I grew up, Al, Alfred was always there. And whenever I needed something, Alfred was always there.

He also thinks of his parents.

In my case, my mother and my father and my brother sequentially died of cancer, which means I was the caregiver. My family was the caregiver, my siblings and my sister were caregivers for five consecutive years, he said.

Ewing thinks of her father.

I lost my father to prostate cancer about a year ago, she said. So to me, I have a deeper understanding now of what it means to have another day, or another month, or another year. I think that's really what gets me up in the morning now is to say that I want to carry on his legacy and help somebody else have more time with their family members.

With a board of scientific advisors that includes an astronaut and some of the top scientists in the country, Vennare says ethics is part of the ongoing artificial intelligence conversation.

"The purpose is to make the job of the scientist easier, so they can expedite the process of discovery, he said. It's not AI that's going to do that, it's the scientists that are going to do that.

Venarre says Predictive Oncology is agnostic, meaning this company seeks to help drug companies quickly zero in on effective drugs for all kinds of cancer.

Read more:
Pittsburgh researchers using artificial intelligence to help cancer patients - WTAE Pittsburgh

Investment from Tech Entrepreneur and UMass Boston Alumnus Will Fund Campus-Wide Initiative

UMass Boston today announced the creation of The Paul English Applied Artificial Intelligence (AI) Institute, conceived and funded by tech entrepreneur and UMass Boston alumnus Paul English. The new Institute will be the first of its kind and will be embedded in academic study across campus and include a focus on the social, ethical and diversity challenges and opportunities associated with AI. The goal of the initiative is to give UMass Boston students in every fieldwho overwhelmingly join the Massachusetts workforce after graduationthe tools to shape the increasingly AI-powered world of work.

English, who earned his bachelors and masters degrees in computer science at UMass Boston, has committed $5 million to establish the Institute, as well as an associated scholarship fund. It will formally launch during the academic year 20232024, funded with the investment from English plus a $2 million match from the UMass Foundation.

We are at the dawn of a new era. Like the agricultural revolution, the development of the steam engine, the invention of the computer and the introduction of the smartphone, the birth of artificial intelligence is fundamentally changing how we live and work, said UMass Boston Chancellor Marcelo Surez-Orozco. Like any transformative technology, AI is also raising social, ethical and diversity questions that UMass Boston is ideally suited to explore. As we train the next generation of Massachusetts workers, we are grateful for Pauls continued leadership, and understanding of our unique role in the Massachusetts economy.

Ive had the privilege of visiting dozens of universities over my career, said Paul English. What stands out about UMass Boston is its pragmatism, grit, and diversity. It is these things that will propel UMB to lead on Applied AI. The new generation of AI will change the jobs of everyone who uses a computer, and I will work closely with UMB as they leverage and develop AI tools across all their disciplines.

The Paul English Applied Artificial Intelligence Institute will catalyze UMass Bostons efforts to organize significant expertise and activity around AI. It will gather experts from the full spectrum of UMass Bostons schools and colleges, as well as the Venture Development Center, to lead the universitys ambitious teaching, learning, workforce development, community engagement, and research agenda around AI. It will incorporate AI competencies into the curriculum, giving each student the applied AI skills they need to join tomorrows workforce.

The Institute will promote the democratization of artificial intelligence by empowering every UMass Boston student to graduate with fluencyand a competitive edgein ethically leveragingevolving AI-powered tools to improve processes and outcomes in their chosen professional field, said UMass Boston Provost Joseph Berger. We hope that Pauls far-sighted commitment inspires others to support this important initiative and the opportunity it offers Bostons public university students.

English 87, G89, H19 is the founder or co-founder of several technology companies, including Boston Venture Studio, Deets, Kayak, Moonbeam, Reki, Xiangqi.com, FunContact, Lola, GetHuman, Boston Light and Intermute. He has also co-founded several non-profit organizations, including Embrace Boston, Summits Education in Haiti, Winter Walk for Homelessness and the Bipolar Social Club. His many speaking and media engagements include a TEDx Talk and an appearance on "How I Built This" with Guy Raz on NPR.

About UMass Boston

The University of Massachusetts Boston is deeply rooted in the city's history yet poised to address the challenges of the future. Recognized for innovative research, metropolitan Bostons public university offers its diverse student population both an intimate learning environment and the rich experience of a great American city. UMass Bostons colleges and graduate schools serve 16,000 students while engaging local and global constituents through academic programs, research centers, and public service. To learn more, visit http://www.umb.edu.

Continued here:
UMass Boston Launches The Paul English Applied Artificial ... - University of Massachusetts Boston

On May 17, as bodies lined up in the rain outside the Cannes Film Festival Palais for the chance to watch a short film directed byPedro Almodvar, an auteur known most of all for his humanism, a different kind of gathering was underway below the theater. Inside the March, a panel of technologists convened to tell an audience of film professionals how they might deploy artificial intelligence for creating scripts, characters, videos, voices and graphics.

The ideas discussed at the Cannes Next panel AI Apocalypse or Revolution? Rethinking Creativity, Content and Cinema in the Age of Artificial Intelligence make the scene of the Almodvar crowd seem almost poignant, like seeing a species blissfully ignorant of their own coming extinction, dinosaurs contentedly chewing on their dinners 10 minutes before the asteroid hits.

More from The Hollywood Reporter

The only people who should be afraid are the ones who arent going to use these tools, said panelistAnder Saar, a futurist and strategy consultant for Red Bull Media House, the media arm of the parent company of Red Bull energy drinks. Fifty to 70 percent of a film budget goes to labor. If we can make that more efficient, we can do much bigger films at bigger budgets, or do more films.

The panel also includedHovhannes Avoyan, the CEO of Picsart, an image-editing developer powered by AI, andAnna Bulakh, head of ethics and partnerships at Respeecher, an AI startup that makes technology that allows one person to speak using the voice of another person. The audience of about 150 people was full of AI early adopters through a show of hands, about 75 percent said they had an account for ChatGPT, the AI language processing tool.

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The panelists had more technologies for them to try. Bulakhs company re-createdJames Earl Jones Darth Vader voice as it sounded in 1977 for the 2022 Disney+ seriesObi-Wan Kenobi, andVince Lombardis voice for a 2021 NFL ad that aired during the Super Bowl. Bulakh drew a distinction between Respeechers work and AI that is created to manipulate, otherwise known as deepfakes. We dont allow you to re-create someones voice without permission, and we as a company are pushing for this as a best practice worldwide, Bulakh said. She also spoke about how productions already use Respeechers tools as a form of insurance when actors cant use their voices, and about how actors could potentially grow their revenue streams using AI.

Avoyan said he created his company for his daughter, an artist, and his intention is, he said, democratizing creativity. Its a tool, he said. Dont be afraid. It will help you in your job.

The optimistic conversation unfolding beside the French Riviera felt light years away from the WGA strike taking place in Hollywood, in which writers and studios are at odds over the use of AI, with studios considering such ideas as having human writers punch up drafts of AI-generated scripts, or using AI to create new scripts based on a writers previous work. During contract negotiations, the AMPTP refused union requests for protection from AI use, offering instead, annual meetings to discuss advancements in technology. The March talk also felt far from the warnings of a growing chorus of experts likeEric Horvitz, chief scientific officer at Microsoft, and AI pioneerGeoffrey Hinton, who resigned from his job at Google this month in order to speak freely about AIs risks, which he says include the potential for deliberate misuse, mass unemployment and human extinction.

Are these kinds of worries just moral panic? mused the moderator and head of Cannes NextSten Kristian-Saluveer. That seemed to be the panelists view. Saar dismissed the concerns, comparing the changes AI will bring to adaptations brought by the automobile or the calculator. When calculators came, it didnt mean we dont know how to do math, he said.

One of the panel buzz phrases was hyper-personalized IP, meaning that well all create our own individual entertainment using AI tools. Saar shared a video from a company he is advising, in which a childs drawings came to life and surrounded her on video screens. The characters in the future will be created by the kids themselves, he says. Avoyan said the line between creator and audience will narrow in such a way that we will all just be making our own movies. You dont even need a distribution house, he said.

A German producer and self-described AI enthusiast in the audience said, If the cost of the means of production goes to zero, the amount of produced material is going up exponentially. We all still only have 24 hours. Who or what, the producer wanted to know, would be the gatekeepers for content in this new era? Well, the algorithm, of course. A lot of creators are blaming the algorithm for not getting views, saying the algorithm is burying my video, Saar said. The reality is most of the content is just not good and doesnt deserve an audience.

What wasnt discussed at the panel was what might be lost in a future that looks like this. Will a generation raised on watching videos created from their own drawings, or from an algorithms determination of what kinds of images they will like, take a chance on discovering something new? Will they line up in the rain with people from all over the world to watch a movie made by someone else?

Best of The Hollywood Reporter

Click here to read the full article.

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Cannes Diary: Will Artificial Intelligence Democratize Creativity or Lead to Certain Doom? - Yahoo News

In case youve somehow missed the flurry of articles describing the dramatic advance of artificial intelligence, we appear to be at the dawn of a new era. How long will it be before an AI tool can prepare our tax returns?

Up the Learning Curve

Since its public debut in November, ChatGPT has taken off like a rocket, reaching a million users in five days, 100 million users in under two months and 1.16 billion users in five months. It may disrupt multiple fields. But could it actually conquer taxes?

Consider recent AI developments in law, accounting, and management. Earlier versions of ChatGPT got about one in three questions wrong on the law school entrance exam (LSAT) (falling short of scores needed for admission to a top-14 law school), gave 100% wrong answers in a TaxBuzz test of actual questions on a tax practitioner technical support forum, and flopped in accounting (being outscored 77-47 percent by students answering 28,000 exam questions at 186 educational institutions worldwide and flunking the CPA exam).

But the more advanced ChatGPT-4 was able to pass the bar exam with a score in the 90th percentile, pass 13 of 15 Advanced Placement exams, and get a near perfect score on the GRE Verbal grad school test. And developers instructing ChatGPT-4 that it was to operate as TaxGPT were able to do simple tax calculations, as shown on their video (at 19:00 to 22.05).

Law, Accounting, and Tax Firms Invest

Tax, accounting, and consulting firms are moving quickly to take advantage of the technology. Professionals in 250 firms have partnered with Blue J Tax, an AI tool for tax research, analysis, and planning that aids in analyzing legislation and litigation to predict tax scenario outcomes with speed and accuracy. Developers claim AI can analyze thousands of past decisions, expedite research, find supporting directives, weigh alternatives, anticipate court rulings, and quantify risk.

The experimentation has been going on for some time. In 2017, H&R Block partnered with IBMs Watson. The program lasted two years and then quietly disappeared. Watson apparently was a slow learner. Or perhaps it just wasnt quite ready for prime time.

Intuit used AI during the 2022 tax filing season to match customers with the right human tax professional for its TurboTax Live assisted preparation. It claimed a one-hour reduction in service time compared to the year before. Still, in a blog asking Can ChatGPT do your taxes? Intuit said it would require years of tax AI expertise.

A Potential Tool for Tax Administrators

Similar to tech leaders open letter calling for a pause in AI development to allow for more safety protocols, a bipartisan group of senators recently wrote to IRS Commissioner Danny Werfel with concerns about AI powering cybercriminals and tax scams.

But what about enabling the IRS to defeat fraudsters, or plug tax loopholes that other AI users may be trying to manipulate or create?

Tax authorities in Greece and France have used AI to cross-check property tax registries and satellite photos of homes to find tax cheaters who dont declare assets like swimming pools. And Johns Hopkins University computer scientists are creating Shelter Check to enable Congress, the IRS, or courts to scan legislation or rulings for loopholes. In a recent test, ChatGPT and GPT-3 were completely baffled by the tax code, but GPT-4 is showing promise.

All this may presage an AI arms race between aggressive tax planners seeking to exploit or expand loopholes and lawmakers or tax authorities seeking to curb or end them.

But summarizing reports, generating insights, writing poetry or code, preparing legal documents, or even offering financial or tax advice are not the same as answering real-life tax questions or optimally completing a tax return.

A Work in Progress

ChatGPT is still a work in progress, missing critical analytical and quantitative skills. It is flummoxed by translating our convoluted tax code, its regulations, and rulings into tailored decisions. It is prone to error and dependent on internet information only available before 2021.

Plus, even with AI, the burden of preparing a tax return will still involve collecting personal information, entering data that may be unavailable in public records, and weighing decisions based on precedent and values.

But as science fiction writer William Gibson once said, The future has arrived its just not evenly distributed yet.

Welcome to our brave new world.

Originally posted here:
Will Artificial Intelligence Be Able to Prepare Our Tax Returns? - Tax Policy Center