Epstein's shadow: Why Bill Gates pulled out of Modi's AI summit Microsoft founder Bill Gates has cancelled his keynote speech at India's flagship AI summit just hours before he was due to take the stage on Thursday. Gates, who has faced renewed scrutiny over his past ties to the late sex offender Jeffrey Epstein, withdrew to "ensure the focus remains on the AI Summit's key priorities", the Gates Foundation said in a statement. India's Prime Minister Narendra Modi had billed the summit as an opportunity for India to shape the future of AI, drawing high-profile attendees, including French President Emmanuel Macron and Brazilian President Luiz Inacio Lula da Silva. Instead, it has been dogged by controversy, from Gates's abrupt exit to an incident in which an Indian university tried to pass off a Chinese-made robotic dog as its own innovation. So, what exactly went wrong at India's flagship AI gathering and why has it drawn such intense scrutiny?

Bill Gates pulls out of India's AI summit amid Epstein files controversy Bill Gates will not deliver his keynote address at the India AI Impact Summit in Delhi, his philanthropic organisation said hours before the Microsoft co-founder was due to speak. The Gates Foundation said the decision was made after careful consideration and to ensure the focus remains on the [summit's] key priorities, but did not elaborate. Gates's withdrawal comes amid a controversy over his ties to the late sex offender Jeffrey Epstein after he was named in new files released by the US Department of Justice in January. Gates's spokesperson has called the claims in the files absolutely absurd and completely false, and the billionaire has said he regretted spending time with Epstein . Gates has not been accused of wrongdoing by any of Epstein's victims and the appearance of his name in the files does not imply criminal activity of any kind.

Earlier this week, I wrote about the history of progressive math education, the culture wars it has inspired over the past hundred years, and the controversy over the California Math Framework. Today, I want to start with a much broader question: What do we really know about how to teach math to children? The answer is not all that much--and what little we do know is highly contested. An American math education usually proceeds in a linear fashion, with the idea that one subject prepares you for the next. Take, for example, the typical path through mathematics for a relatively advanced student.

Bill Gates has called for greater investment in engineered crops that can adapt to climate change and resist agricultural pests, in an effort to solve world hunger. In the latest annual Goalkeepers Report from the Bill & Melinda Gates Foundation, Gates says the global hunger crisis is so immense that food aid cannot fully address the problem. What's also needed, he argues, are innovations in farming technology that can help to reverse the crisis. Gates points in particular to a breakthrough he calls'magic seeds' - including maize that has been bred to be more resistant to hotter, drier climates, and rice that requires three fewer weeks in the field. These innovations will allow agricultural productivity to increase despite the changing climate, he argues.

Collaborating with Google, Lumen Bioscience applied Bayesian black-box optimisation, a machine learning approach, to increase spirulina biomanufacturing productivity. A new paper shows that applying machine learning (ML) to bioproduction can significantly increase recombinant protein production and thus advance the scalability of spirulina-based biologic drugs. Under a research collaboration funded in part by the Bill & Melinda Gates Foundation, Lumen Bioscience worked with Google Accelerated Science to apply ML to increase the productivity of Arthrospira platensis (spirulina) using Bayesian black-box optimisation. The results of the collaboration, which are pending peer-review, have been published in pre-print on the bioRxiv server. The paper describes how the ML approach of Bayesian black-box optimisation was used to guide experiments in 96 photobioreactors, exploring the relationship between production outcomes and 17 environmental variables, including pH, temperature and light intensity.

An artificial intelligence-enabled synthetic data generator that converts clinical data of any kind into equivalent, mock versions that don't expose sensitive patient-identifying details is being put to use as a component of the National Institutes of Health-steered National COVID Cohort Collaborative, or N3C effort. "The NIH's N3C initiative is a result of the urgent need for understanding of COVID both to develop better patient care and understand the impacts on individuals and the health system as a whole," Dr. Michael D. Lesh told Nextgov this week. Lesh--the co-founder and CEO of Syntegra, the company behind the synthetic data engine--shed light on how the tool works, and a new partnership between the business, NIH and the Bill and Melinda Gates Foundation that underpins this fresh endeavor. In June 2020, not long after the novel coronavirus pandemic disrupted nearly every aspect of American life, NIH launched N3C to accelerate COVID-19 research and new medical breakthroughs. The collaborative pursuit, according to a June press release, intends to systematically capture relevant data from participating health care providers across the country, aggregate that data into accessible formats, and in-turn help approved users harness research insights from that harmonized information, via the NCATS N3C Data Enclave.

Background: Misinformation spread through social media is a growing problem, and the emergence of COVID-19 has caused an explosion in new activity and renewed focus on the resulting threat to public health. Given this increased visibility, in-depth analysis of COVID-19 misinformation spread is critical to understanding the evolution of ideas with potential negative public health impact. Methods: Using a curated data set of COVID-19 tweets (N ~120 million tweets) spanning late January to early May 2020, we applied methods including regular expression filtering, supervised machine learning, sentiment analysis, geospatial analysis, and dynamic topic modeling to trace the spread of misinformation and to characterize novel features of COVID-19 conspiracy theories. Results: Random forest models for four major misinformation topics provided mixed results, with narrowly-defined conspiracy theories achieving F1 scores of 0.804 and 0.857, while more broad theories performed measurably worse, with scores of 0.654 and 0.347. Despite this, analysis using model-labeled data was beneficial for increasing the proportion of data matching misinformation indicators. We were able to identify distinct increases in negative sentiment, theory-specific trends in geospatial spread, and the evolution of conspiracy theory topics and subtopics over time. Conclusions: COVID-19 related conspiracy theories show that history frequently repeats itself, with the same conspiracy theories being recycled for new situations. We use a combination of supervised learning, unsupervised learning, and natural language processing techniques to look at the evolution of theories over the first four months of the COVID-19 outbreak, how these theories intertwine, and to hypothesize on more effective public health messaging to combat misinformation in online spaces.

More children are being vaccinated around the world today than ever before, and the prevalence of many vaccine-preventable diseases has dropped over the last decade. Despite these encouraging signs, however, the availability of essential vaccines has stagnated globally in recent years, according the World Health Organization. One problem, particularly in low-resource settings, is the difficulty of predicting how many children will show up for vaccinations at each health clinic. This leads to vaccine shortages, leaving children without critical immunizations, or to surpluses that can't be used. The startup macro-eyes is seeking to solve that problem with a vaccine forecasting tool that leverages a unique combination of real-time data sources, including new insights from front-line health workers.

Every day, Massachusetts seventh-grader Kaylyn Wilson takes a break from doing homework online and opens an app on her phone for a half-hour foreign language lesson. "The boy has three green bikes and an egg," the 12-year-old announced to her family in French at the start of her third week using the mobile app from Rosetta Stone, the language-learning software giant. Wilson doesn't yet need to study a language for credit. But during the school shutdowns to contain the coronavirus, her father saw Rosetta Stone advertise free accounts for students – an offer other language-learning software companies have made as well. Wilson decided to give it a go.

SAN FRANCISCO/NEW YORK – Bill Gates is stepping down from the board of Microsoft Corp., the company he co-founded in 1975 and built into the world's largest software maker, to devote more time to philanthropy. Gates, 64, has been scaling back his involvement in the company for more than a decade. Most recently he had been serving as an adviser to current Chief Executive Officer Satya Nadella on technology areas including productivity, health software and artificial intelligence, and he will continue to do so."Microsoft "I feel more optimistic than ever about the progress the company is making and how it can continue to benefit the world." Gates hasn't been active in a day-to-day role since 2008, Microsoft said in a statement.