The wave of neural network engines that AlphaZero inspired have impacted chess preparation, opening theory, and middlegame concepts. We can see this impact most clearly at the elite level because top grandmasters prepare openings and get ideas by working with modern engines. For instance, Carlsen cited AlphaZero as a source of inspiration for his remarkable play in 2019.
Neural network engines like AlphaZero learn from experience by developing patterns through numerous games against itself (known as self-play reinforcement learning) and understanding which ideas work well in different types of positions. This pattern recognition ability suggests that they are especially strong in openings and strategic middlegames where long-term factors must be assessed accurately. In these areas of chess, their experience allows them to steer the game towards positions that provide relatively high probabilities of winning.
I have always been very interested in building objects and creating robots, but who isn’t? Robots are the coolest. I’ve always thought they were great and wanted to work on them, but it took me a while to get to robotics.
I was very interested in the arts early on and in high school I was more focused on computer graphics and photography. But when I went to college I began to wonder how good at art I really was and whether it was perhaps more of a hobby, so I fell back on math. I then worked for three years as a data scientist for an insurance company. That is not exciting; there are no robots there!
At 25, I went back to school and studied computer science and robotics. It was what I had always wanted to do but it took me a while to realize that I could do it. It seems kind of daunting, like you must have to be a child prodigy at coding. That’s not true—at least I hope it’s not!
Fortune; François Candelon , Su Min Ha , and Colleen McDonald
from
Sadly, companies, especially those that have started using A.I. in the workplace, tend to focus only on the technology and almost forget about the human aspects while trying to optimize productivity. CEOs, we believe, must tackle four challenges to get the most out of combining employees and A.I.
Excessive oversight
Companies can use digital technologies to collect data on (almost) everything that their employees do. Doing so usually leads to executives micromanaging employees so much that the process often borders on the invasion of their privacy. Besides, using A.I. to ensure that people are working every second will increase the productivity only of those who need constant supervision. It will never inspire creativity and innovation—the capabilities that differentiate humans from machines.
But you’d be much better off taking a class in operating systems or cryptography instead. Or almost any other subject you were genuinely interested in.
Calvin will serve in this capacity under the Intergovernmental Personnel Act Mobility Program, which provides for the temporary assignment of personnel between the federal government and state and local governments, colleges and universities, Indian tribal governments, federally funded research and development centers, and other eligible organizations.
Since 2008, Calvin has been an Earth scientist at the Pacific Northwest National Laboratory’s Joint Global Change Research Institute (JGCRI) in College Park, Maryland.
Machine vision incorporates a variety of technologies and increasingly relies on software in the form of machine learning and AI to interpret and process data from 2D sensors that would have been unachievable even a short time ago.
With this increasing reliance on software comes an interesting shift away from highly specialized sensors like LiDAR, long a staple for robots operating in semi-structured and unstructured environments. Robotics experts marrying the relationship between humans and AI software are coming to find that LiDAR isn’t actually necessary. Rather, machine vision is providing higher quality mapping\at a more affordable cost, especially when it comes to indoor robotics and automation.
University of Louisville faculty, staff and students are in an uproar over the administration’s refusal to allow classes to be taught remotely.
As the new semester began Monday, more than 500 professors, staff, students, parents and other community members have signed a petition to allow courses to be offered online.
One of the signers, an administrator in the Speed School, wrote the “wish for normalcy should not supersede the need for safety,” while a graduate teaching assistant said, “Please be dedicated to BEING SAFE, not dedicated to being in person.”
For seasonal coronaviruses & flu, we see a pattern of ‘antigenic turnover’ over time – circulating viruses give rise to new variants that escape prior immunity against infection, immunity builds against these new variants, then these in turn spawn new variants… 2/
When infections evolve to escape immunity like this, we typically end up with an evolutionary tree that looks like a lopsided ladder as new variants sequentially replace their ‘parent’ variant lineages (below from: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1002947) 3/
President Joe Biden’s administration last week ordered federal agencies to draft uniform policies describing the outside sources of funding that scientists must disclose when they apply for federal grants, and the penalties for failing to do so. Research groups welcome the directive, but wish it had also specified what kinds of foreign collaborations might get a scientist in trouble.
The new directive, issued on 4 January by the White House Office of Science and Technology Policy (OSTP), feeds into a roiling political debate about how to protect federally funded research from attempted theft by some foreign governments. In recent years, the federal government has prosecuted some two dozen academics for failing to disclose financial ties to China, which critics say has criminalized minor violations of often confusing federal rules and chilled research collaborations.
Sixteen Ivy League and elite U.S. universities were sued in federal court for allegedly illegally conspiring to eliminate competitive financial aid offers to students in a price fixing scheme.
The suit alleges the conspiracy artificially inflated the cost of attendance for all students receiving financial aid and resulted in the overcharging of “over 170,000 financial-aid recipients by at least hundreds of millions of dollars.”
The demand for a class action jury trial, filed on Sunday in an Illinois federal court by five former Vanderbilt, Northwestern and Duke University students, seeks to compensate people who received financial aid packages that did not fully cover the cost of tuition, room and board from one of the 16 self-described “need-blind” universities since 2003.
When Rebecca Doerge became dean of Carnegie Mellon University’s College of Science in August 2016, the statistician was handed a big challenge: elevate the reputation of the College of Science to the same level of recognition as the university’s engineering and computer science departments.
Doerge responded to the challenge with somewhat of a gamble, deciding to invest $40 million to build the world’s first university cloud lab. In the new field of “life science as a service,” the comprehensive laboratory in the cloud can be accessed and controlled remotely by computer interface, allowing students and researchers to conduct multiple experiments at once without setting foot in an actual laboratory. Proof of concept results have already demonstrated that three years of research can be accurately reproduced in just two weeks with this technology.
On Thursday, January 6th, the Midwest Quantum Collaboratory was officially launched. Press releases were issued by University of Michigan, Michigan State University and Purdue University.
Bulletin of the Atomic Scientists, Susan D'Agostino
from
“Few other researchers have generated as much excitement in the AI field as David Silver,” Association for Computing Machinery President Cherri M. Pancake said at the time. “His insights into deep reinforcement learning are already being applied in areas such as improving the efficiency of the UK’s power grid, reducing power consumption at Google’s data centers, and planning the trajectories of space probes for the European Space Agency.” Silver is also an elected Fellow of the Royal Society and was the first recipient of the Mensa Foundation Prize for the best scientific discovery in the field of artificial intelligence.
Silver’s stardom contrasts with his quiet, unassuming nature. In this condensed, edited, from-the-heart interview, I talk with Silver about games, the meaning of creativity, and AI’s potential to avert disasters such as climate change, human-made pathogens, mass poverty, and environmental catastrophe.
While the hyperscalers and cloud builders have built ever-more-efficient infrastructure, according to data compiled by Statista, in 2015 these two groups together consumed 93.1 terawatt-hours of juice in 2015 compared to 97.6 terawatt hours for traditional, enterprise datacenters as a group. Power usage by traditional datacenters has fallen by two-thirds by 2021, to a mere 32.6 terawatt-hours, but power usage by the hyperscalers and cloud builders has climbed by 70 percent over that same time to reach 158.2 terawatt-hours. With Moore’s Law running out of juice and devices getting hotter as they drive higher performance, datacenter power consumption can only keep rising.
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And that is the impetus behind the Treehouse project, which bills itself as a means to make datacenter software “carbon-aware” in keeping with the common language used among those who (rightly) espouse energy efficiency.
2/ Following @YouTube
‘s most recent move to remove the dislike count from public view and @instagram
‘s option to hide the like count, studies on the behavioral impact of social media are becoming increasingly important.
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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.
Knowledge graphs and machine learning are both major hypes in technology land. This blog post will give an explanation of the relationship between the two.
