The Google Health Studies platform is already enrolling Android users in a 100,000-person investigation of acute respiratory illnesses, conducted alongside Boston Children’s Hospital and Harvard Medical School researchers.
Tiny lab-grown livers, with blood- and bile-carrying systems, have shown promising results when transplanted into mice with failing livers, and scientists at the University of Pittsburgh School of Medicine are hoping that an algorithm used to engineer the “organoids” can be applied to future organ research.
The “machine learning” method is “a new way that can help us to build better tissues, to make more mature tissues. The good part of it is that we are just testing that in the liver, but it is not limited to that,” said Dr. Mo Ebrahimkhani, lead author of the study published Monday in Cell Systems.
“What does it mean to be a liver? What does it mean to be a brain? [The] computational algorithm compare tissues with the final organ,” said Dr. Ebrahimkhani, an associate professor of pathology at Pitt. “What is the path, what are the specific genes that are missing, turn them on and off and program your tissue.”
Remember ROAR data? Two years ago, it was quietly evolving as part of JPMorgan’s project to develop “an online platform to host prediction competitions and challenges among public participants.”
It apparently came to nothing, but the ROAR concept has not died.
Peter Cotton, the JPMorgan data scientist behind ROAR has been busy building a new crowdsourced data platform called Microprediction.
It’s been a busy few days at NeurIPS 2020 so far with all manner of talks, workshops, tutorials and socials on offer. This selection of tweets gives a flavour of the various events and discussions taking place.
Synthetic voices have become ubiquitous. They feed us directions in the morning, shepherd us through phone calls by day and broadcast the news on smart speakers at night. And as the technology used to make them improves, these voices are becoming more and more human-sounding. This is the final frontier in synthetic speech: replicating not just what we say but how we say it.
Rupal Patel heads a research group at Northeastern University that studies speech prosody—the changes in pitch, loudness and duration that we use to convey intent and emotion through voice. “Sometimes people think of it as the icing on the cake,” she explains. “You have the message, and now it’s how you modulate that message, but I really think it’s the scaffolding that gives meaning to the message itself.”
The COVID era has made it clear that as a species, humans need help adapting to swift change and solving big problems. The truth is that many of the problems that we face as a civilization or as a collective are simply beyond the capacity of the unaided human brain to solve. We have relatively little understanding of how the brain even works.
If we want to feed the poor by optimizing agriculture around the world, cure cancers by knowing how cancer cells populate, or develop cheap and clean energy with fusion engines, humanity needs far more powerful tools than what we have today. Humans have always required more complex tools to solve ever more complex problems.
Necessity is the mother of invention, and Artificial Intelligence (AI) has been a tremendous enabling force in the fight against COVID. Like never before, private companies, non-profits, and government agencies have come together to point GPUs at speeding scientific research and work toward a cure. Early in the pandemic, we saw tech giants including Microsoft and Google partner with government agencies and nonprofits such as the White House, NIH, The CDC, and the Allen Institute for AI. Through collaboration, the best minds and best technology worked together to begin to solve the biological puzzle of COVID-19.
On Wednesday, New York Attorney General Letitia James announced a massive antitrust lawsuit against Facebook, claiming the social media giant has harmed competition by buying up smaller companies like Instagram and WhatsApp to squash the threat they posed to its business. Forty-seven other state and regional attorneys general are joining the suit.
The lawsuit centers on Facebook’s acquisitions, particularly its $1 billion purchase of Instagram in 2011. In addition to its acquisition strategy, the attorneys general allege that Facebook used the power and reach of its platform to stifle user growth for competing services.
France’s data protection agency, the CNIL, has slapped Google and Amazon with fines for dropping tracking cookies without consent.
Google has been hit with a total of €100 million ($120 million) for dropping cookies on Google.fr and Amazon €35 million (~$42 million) for doing so on the Amazon .fr domain under the penalty notices issued today.
The regulator carried out investigations of the websites over the past year and found tracking cookies were automatically dropped when a user visited the domains in breach of the country’s Data Protection Act.
In Google’s case the CNIL has found three consent violations related to dropping non-essential cookies.
Adobe has released the final scheduled update to its Flash Player plugin, weeks before Flash’s official retirement. As noted on Adobe’s site, yesterday marked the last update for Flash outside mainland China, which has a separate version of the software. Adobe will stop supporting Flash on December 31st, 2020, and it will block Flash content from running on January 12th, 2021.
Adobe offered a brief farewell in its release notes. “We want to take a moment to thank all of our customers and developers who have used and created amazing Flash Player content over the last two decades,” the note says. “We are proud that Flash had a crucial role in evolving web content across animation, interactivity, audio, and video. We are excited to help lead the next era of digital experiences.”
Hyundai Motor will acquire Boston Dynamics. The acquisition will be finalized at Hyundai’s December 10 board meeting. News about the deal was first reported by The Korea Economic Daily, which said the deal is for $921 million (1 trillion won). The Robot Report has also confirmed the news with a source familiar with the deal. The source said the acquisition is for about $1 billion.
For the best in-depth analysis of the concept of the “open core” business model I’ve come across, I highly recommend reading Joseph Jacks’ blog post Open Core — Definition, Examples & Tradeoffs.
The whole idea is insane. No one believes it could possibly work when they first learn about it, and yet dozens of companies like Elastic, D2iQ (formerly Mesosphere), MongoDB and Cloudera have all managed to achieve valuations in the billions of dollars by pursuing this batshit-crazy, reverse-psychology, let-it-all-hang-out strategy. Or, at least, they were open core businesses at some point…maybe not so much today. More on that later.
Today, we’re gathered here on the internet to mourn the death of the open core business model. We’re here to tell stories of the before-times, to reminisce about how smart we thought we were. We went against consensus, and we were wrong. Because, open core is dead.
Stanford University, Stanford Medicine, Scope blog
from
[Alexandria] Boehm studies pathogens in wastewater, oceans and rivers and on surfaces; and she oversees a lab of students and postdoctoral fellows who process samples provided by staff members at 50 wastewater plants around the Bay Area, California and the nation. The researchers extract RNA from the samples and test it for the coronavirus using kits similar to the ones that are used for patient specimens.
Their research has shown that virus levels in the wastewater samples correlate with new COVID-19 infections in the area the wastewater plant serves. As they continue their investigation of wastewater samples, Boehm and her colleagues are talking with public health officials about the best ways to use the information.
Security Magazine, Kelly Rozumalski and Andrew Speirs
from
COVID-19 catalyzed greater connectivity in the healthcare space. Take telehealth, for example. Stay-at-home orders quickly escalated telehealth from a promising innovation to an essential priority. In a matter of months, organizations had to quickly shift their IT budgets, scopes, and schedules to leverage their existing technologies and get providers and patients on board.
We’ve seen impressive statistics in increased adoption in this short timeframe. The Centers for Medicare and Medicaid Services estimated approximately 13,000 telehealth appointments per week before the pandemic and at least 10 million total, breaking down to roughly 625,000 per week from early March through mid-August.
As the world anticipates a new US Congress and a new administration, we need a strategy to reimagine and rebuild communities, industries, companies, and nations. As we battle cascading disruptions from a global pandemic, economic strain, climate-related crises, and unrest over racial injustice, technology should be part of a solution—but technology alone is not enough.
To more evenly spread economic opportunity and resilience, we must democratize “tech intensity,” a combination of tech and people skills—including among citizen developers. This so-called intensity is made up of three dimensions: the adoption of technology, the capability of individuals to use it, and their trust in the organizations deploying it. Tools from cloud computing to AI should be in the hands of every knowledge worker, first-line worker, organization, and public-sector agency around the world.
Harvard T.H. Chan School of Public Health, Department of Biostatistics
from
Online December 17, starting at 12 p.m. Easter time. “This bi-weekly seminar features the latest research that is positioned on the cusp of new understanding and analysis of COVID-19 pandemic data, and promotes data-driven research and decision making to combat COVID-19.” [registration required]
“As the Deputy Assistant Director of NSF’s Social, Behavioral and Economic Sciences directorate, my colleagues and I looked inward as we considered the small number of financial awards that our organization makes each year to minority-serving institutions. As a result, we launched Build and Broaden, a funding opportunity inviting proposals aimed at fostering partnerships and kick-starting research collaborations in the social, behavioral and economic sciences among minority-serving institutions while enhancing the research infrastructure and capacity of those institutions.” Deadline for proposals is March 5, 2021.
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The eScience Institute’s Data Science for Social Good program is now accepting applications for student fellows and project leads for the 2021 summer session. Fellows will work with academic researchers, data scientists and public stakeholder groups on data-intensive research projects that will leverage data science approaches to address societal challenges in areas such as public policy, environmental impacts and more. Student applications due 2/15 – learn more and apply here. DSSG is also soliciting project proposals from academic researchers, public agencies, nonprofit entities and industry who are looking for an opportunity to work closely with data science professionals and students on focused, collaborative projects to make better use of their data. Proposal submissions are due 2/22.
If you subscribe to any feeds, then 50% of the articles in your regular Findka emails will be sampled from those feeds. I added this because, as I mentioned, I’m going to start doing more manual curation to make sure that Findka has a steady stream of new, great essays. I also think it’s a valuable feature for anyone who wants a little more control over their Findka recommendations.
How’s this different from existing RSS aggregators? For one thing, since this is built into Findka, any articles that you like will start to be recommended to other users, too. But there’s more.
Most RSS aggregators keep your feeds separate. Findka instead merges them into a single feed using a bandit algorithm.
