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Leahy, Russo represent MHS at National Women and Girls in Sports Day
On May 19, the Massachusetts Interscholastic Athletic Association hosted the annual celebration of National Women and Girls in Sports Day at Faneuil Hall in Boston. This event recognizes two exceptional female athletes from each high school in the state. It’s designed to honor their contributions to their respective sports, commitment to sportsmanship and excellence in
Can researchers trust that AI models won’t leak their ideas?
Research funders are asking how they can stop confidential scientific ideas in grant proposals from leaking out through large language models (LLMs), for example if reviewers use AI to help them judge applications. Last week, a row erupted in mathematics after OpenAI announced it had solved a notoriously difficult problem, only for another mathematician to demand answers over whether the company had used ideas he had fed into its models. The spat, and the broader issue of idea leakage through AI models, was discussed by funders at an R&D policy conference held in Paris on September 14. At worst, it threatens to undermine the correct attribution of breakthroughs, one of the foundations of modern science. The mathematics dispute around OpenAI is “certainly something we're looking at” Jason Gallo, head of the newly established Office of Metascience at the US National Science Foundation (NSF), told the Blue Sky Forum, hosted by the Organisation for Economic Co-operation and Development. The controversy started on September 8, when OpenAI announced it had cracked a mathematical problem that had gone unsolved for 90 years. Using a swarm of AI agents, millions of dollars’ worth of computing power and a new internal model, the company said it had finally proved that a long-used formula for modelling fluid dynamics breaks down under certain conditions. However, Tristan Buckmaster, a New York University mathematician who had been independently working with collaborators on the same problem using OpenAI’s Codex tool, hit back with a statement questioning whether the company had snooped on his Codex sessions to gain an advantage. OpenAI has always denied it looked up the “specific user data” of Buckmaster and colleagues. However, the company initially admitted that “while unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models,” although its proofs “differ significantly” from Buckmaster’s. The firm later said that, following an investigation, it concluded that Buckmaster’s Codex prompts “could not have influenced the [OpenAI] system in any way, including through training.”Funder concernYet OpenAI’s initial admission that its model might have ingested Buckmaster’s ideas, then spat them out to its own mathematicians, has scientistsworriedthat their work could leak out if shared with AI. Some AI tools give users an opt-out option to stop their sessions from training the model. If such guarantees can be trusted, this gives scientists some confidence they can use an LLM to develop an idea without the risk of it leaking out.But there’s a bigger potential vulnerability. To win money to investigate ideas, scientists have to share them with funding bodies. These grant proposals are normally kept strictly confidential, to prevent other scientists from scooping them, or to protect commercially valuable intellectual property. To preserve this confidentiality, when the NSF uses AI models, “we have to be sure that it's not making server calls out to an external party, leaking that data,” said Gallo to delegates in Paris. Leaks through reviewersHowever, funders normally use external academic reviewers to assess proposals. And there are growing worries that these reviewers are feeding grant ideas into AI models to help them make a judgement. Research funders have noticed that peer review reports and funding recommendations have “suddenly become much longer, more detailed and complex,” said Diogo Machado, head of the data science unit at Technopolis, a science and technology-focused consultancy. “The sense is that reviewers are increasingly using generative AI in their review work, even where guidelines sometimes forbid it,” he told Science|Business. “This is very difficult for funders to control or prove.” Happening at scaleThis sharing of confidential proposals with AI models is “happening at scale already,” said James Wilson, executive director of the Research on Research Institute, based at University College London, during the debate in Paris. In response, Gallo said the NSF had “strict guidance” around the uploading of proposals to AI models. But he added the NSF was mulling new types of assessment to make sure applicants were truly the originators of their ideas, such as following a short-form proposal with an oral presentation, which would allow the foundation to “really interrogate the investigator on their intellectual contribution.” Related articlesHow can Europe cope with a flood of AI-assisted research grant proposals?The risks and benefits of AI in screening research grant proposals Viewpoint: AI could make scientific overload worse“For us as funders, a lot of the ways to ensure that the application remains the applicant's own intellectual contribution, those ways are quite regressive,” Peter Clifford, head of strategy at Research Ireland, told delegates. “They're maybe ten or 15 or 20 years old, and they don't scale particularly well.” Disputes over the origin of ideas are as old as modern science. Isaac Newton and Gottfried Wilhelm Leibniz spent more than a decade arguing over who invented calculus, for example. And long before LLMs emerged, academics would agonise over how much of their early work to reveal at conferences, in case their colleagues scooped them, Jack Leahy, a senior metascience advisor to the UK government, told delegates. But AI was “accelerating” the “problems of the system,” he said.
St. Louis Cardinals vs Cincinnati Reds Game Discussion Tuesday
It’s game 3 of the St. Louis Cardinals vs the Cincinnati Reds as they’ll clash again Tuesday night. Kyle Leahy will make the start for the Cardinals while Andrew Abbott is the scheduled starter for the Reds. First pitch at Great American Ball Park is set for 5:40pm central time.
Cardinals start 3-game series with the Brewers
Milwaukee Brewers (18-15, fourth in the NL Central) vs. St. Louis Cardinals (20-14, third in the NL Central) St. Louis; Monday, 7:45 p.m. EDT PITCHING PROBABLES: Brewers: Chad Patrick (2-1, 2.57 ERA, 1.25 WHIP, 16 strikeouts); Cardinals: Kyle Leahy (3-3, 5.52 ERA, 1.67 WHIP, 22 strikeouts) LINE: Brewers -115, Cardinals -105; over/under is 8 1/2 runs BOTTOM LINE: The St. Louis Cardinals host the Milwaukee Brewers to start a three-game series. St. Louis is 20-14 overall and 9-9 at home.
St. Louis Cardinals vs Pittsburgh Pirates Game Discussion Saturday
The St. Louis Cardinals and Pittsburgh Pirates will convene again Saturday afternoon for game 2 of their weekend series. Kyle Leahy is the scheduled starter for the Cardinals while the Pirates will send RHP Lake Bachar to the mound. First pitch is 1:15pm central time with the game broadcast available via Cardinals.tv.
A profile of St. Louis Cardinals starter Kyle Leahy
This 29-year-old pitcher took a long route to being an MLB starting pitcher
St. Louis Cardinals vs Colorado Rockies Game Discussion Sunday
The St. Louis Cardinals wrap up their Colorado vacation against the Rockies Sunday afternoon at Coors Field. Kyle Leahy will pitch at least the first couple of innings for the Cardinals while the Rockies give the ball to RHP Tanner Gordon. First pitch set for 2:10pm central time and the game broadcast will be available […]
St. Louis Cardinals vs Chicago White Sox Game Discussion Saturday
After a rousing St. Louis Cardinals Hall of Fame ceremony where Albert Pujols, Yadier Molina and Bill Sherdel were immortalized, the team will take the field and do battle with the Chicago White Sox Saturday night. Kyle Leahy will get the start (for a couple innings at least) while Chicago sends Luis Castillo to the […]
Royals look to end slide in matchup with the Cardinals
Kansas City Royals (19-26, fifth in the AL Central) vs. St. Louis Cardinals (26-18, third in the NL Central) St. Louis; Saturday, 2:15 p.m. EDT PITCHING PROBABLES: Royals: Noah Cameron (2-2, 5.55 ERA, 1.63 WHIP, 32 strikeouts); Cardinals: Kyle Leahy (4-3, 4.31 ERA, 1.59 WHIP, 32 strikeouts) LINE: Royals -112, Cardinals -106; over/under is 8 1/2 runs BOTTOM LINE: The Kansas City Royals aim to end a five-game slide with a victory over the St. Louis Cardinals. St. Louis has an 11-10 record in home games and a 26-18 record overall.
Who should be the Cardinals’ next Kyle Leahy?
After matching his shortest start of the season, Kyle Leahy is nearing the end of his first season as a starter for the St. Louis Cardinals. Despite early struggles that caused some fans to laughably demand his removal from the rotation, Leahy had the lowest ERA among starters since the All-Star Break with the lightened […]