As cold-blooded and inhuman as it may sound, animal tests are an integral part of modern-day drug and chemical compounds development and approval procedures. And with good reasons. Scientists can’t still reliably predict the properties of new chemicals, let alone how these compounds might interact with living cells.
But a new paper published in the research journal Toxicological Sciences shows that it is possible to predict the attributes of new compounds using the data we already have about past tests and experiments. The artificially intelligent system was trained to predict the toxicity of tens of thousands of unknown chemicals, based on previous animal tests, and the results are, in some cases, more accurate and reliable than real animal tests.
In mid-July, 52 teachers from Alabama high schools proved that learning and teaching are year-round endeavors as they attended a computer science-focused summer institute hosted by Tuskegee University.
The institute, held on Tuskegee’s campus from July 16-20, trained these educators to teach a new, high school-level computer science course, entitled “Exploring Computer Science.” The course is designed to provide students with a rigorous foundation in authentic computer science topics.
The summer institute is part of a $1 million, multi-institutional partnership grant awarded to Tuskegee by the National Science Foundation that funds “ECS4Alabama” — short for “Exploring Computer Science for Alabama.” It is designed to provide Alabama’s high school students with greater access to computer science education — especially those in rural, high-minority districts.
When the United States pulled out of the Paris Climate Accord last year, 20 states—including New York and California—resolved to form a new, nonfederal agreement to address climate change and greenhouse gas emissions.
According to Purdue University professor of political science Eric Waltenburg, many meaningful policy decisions such as this take place at the state level but are largely ignored by the public. He is collaborating with Dan Goldwasser, assistant professor of computer science, to help people better understand the impact of decisions made at the state level. Together they lead a project focused on developing a forecasting model to predict state legislator voting behavior.
“If our project works like I’m hoping it does, it will open up the policy-making process and people will have a better sense as to what legislative outcomes may be,” Waltenburg said. “It would demystify the state legislative process for the public.”
Foundations of Science, a set of tools that will use machine learning and artificial intelligence to provide personalized support for students in college-level science courses, has taken the top prize in New York University’s inaugural Algorithm for Change competition. The courseware was created by Smart Sparrow in partnership with ACTNext (a multi-disciplinary innovation unit of nonprofit and college readiness exam provider ACT) and Arizona State University’s Center for Education Through Exploration.
The advent of inexpensive, high-quality recording equipment and the maturation of deep learning present an incredible opportunity for neuroscience; but the field needs to develop theoretical frameworks and computational tools to interpret the impending onslaught of data
The New York Times, Julie Creswell, Kevin Draper and Rachel Abrams
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Jared Evans, a member of the Indianapolis City-County Council, is proud that the city is among 20 finalists for one of the most coveted prizes in the country: the planned second headquarters of Amazon.
He does, however, have one small question: What financial incentives did his city dangle in front of Amazon?
“What have I been told?” Mr. Evans said. “Absolutely nothing.”
Across the country, the search for HQ2, as the project has been nicknamed, is shrouded in secrecy. Even civic leaders can’t find out what sort of tax credits and other inducements have been promised to Amazon. And there is a growing legal push to find out, because taxpayers could get saddled with a huge bill and have little chance to stop it.
The Texas Advanced Computing Center (TACC) has won the competition for the NSF’s latest leadership-class supercomputer. The machine is scheduled to be installed at the University of Texas at Austin in 2019 and is expected to be in operation for at least five years.
Yesterday, OpenAI Five won a best-of-three against a team of 99.95th percentile Dota players: Blitz, Cap, Fogged, Merlini, and MoonMeander — four of whom have played Dota professionally — in front of a live audience and 100,000 concurrent livestream viewers. The human team won game three after the audience adversarially selected Five’s heroes. We also showed our preliminary work to introspect Five’s view of the game, including its probability of winning, which made predictions surprising to the human observers. These results show that Five is a step towards advanced AI systems which can handle the complexity and uncertainty of the real world.
Machine learning has gained influence in FX in the last year, although many observers doubt whether the technology has completely mastered the demands of high frequency trading.
Last week, scientists published the biggest-ever study of the genetic influence on educational attainment. By analyzing the DNA of 1.1 million people, the international team discovered more than a thousand genetic variants that accounted—in small part—for how far a person gets through school. It made a lot of people nervous, as they imagined how this new research could be applied in Gattaca-esque testing tools.
But those concerns aren’t new—and neither is the kind of research published last Monday. This sort of correlational work for educational attainment has been in progress since at least 2011. And there is already a consumer product on the market that draws from that early research.
Log onto the Helix DNA marketplace—it’s like the app store for consumer genetic products—and the candy-colored website invites you to “Get started with DNA.” Clicking through takes you to one of Helix’s featured products: the DNAPassport. It was developed by Denver-based HumanCode, which Helix acquired in June, and lets users explore where their ancestors come from, whether they might be sensitive to gluten or lactose, and more than 40 other genetically-influenced traits. One of them is something called “academic achievement.”
Imagine an antenna that could transmit at terahertz frequencies—generally defined as those between 300 gigahertz (GHz) and 3 terahertz (THz). Such an antenna could send and receive data at rates that would be orders of magnitude faster than any device we currently use. Even the 5G networks now being deployed will operate, at best, on frequencies well below 100 GHz.
Now, a team at the Technical University of Munich, headed by Alexander Holleitner and Reinhard Kienberger, has developed a terahertz antenna—but it won’t ever be used to send signals over the air. The TUM team’s antenna is designed to use electrons to transfer data across a minuscule gap on the surface of a chip. Their technique could open the door for much faster on-chip signal generation.
London, England September 26, starting at 6 p.m., SAGE Publishing (1 Oliver’s Yard). Speaker: Pablo Barberá from the London School of Economics. [free, registration required]
“In this tutorial, I will describe a hack that let’s us use PyMC3 to sample a probability density defined using TensorFlow. This isn’t necessarily a Good Idea™, but I’ve found it useful for a few projects so I wanted to share the method. To start, I’ll try to motivate why I decided to attempt this mashup, and then I’ll give a simple example to demonstrate how you might use this technique in your own work.”
Facebook Code; Kyle Nekritz, Subodh Iyengar, Alex Guzman
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We have deployed Fizz and TLS 1.3 globally in our mobile apps, Proxygen, our load balancers, our internal services, and even our QUIC library, mvfst. More than 50 percent of our internet traffic is now secured with TLS 1.3. We also deployed zero round-trip resumption (0-RTT) data, the newest feature of TLS 1.3, with our mobile apps. Fizz now handles millions of TLS 1.3 handshakes every second. We believe this makes it the largest deployment of TLS 1.3 — and early (0-RTT) data — on the internet. Fizz has reduced not only the latency but also the CPU utilization of services that perform trillions of requests a day. We are excited to be open-sourcing Fizz to help speed up deployment of TLS 1.3 across the internet and help others make their apps and services faster and more secure.
“Jupyter Notebook (or Lab) is great for prototyping but not really suited for writing good code. I love Notebooks for trying out new things, plotting, documenting my research, and as an educational tool. However, they don’t help you like an IDE with, for instance, code linting and refactoring. Notebooks written by data scientist are notorious for being unreadable, unreproducible and full of bugs.”
“One solution for writing less terrible code in Notebooks, is to only use an IDE and write no code in Notebooks. But wouldn’t it be great if you could have both the assistance of an IDE and the interactivity of a Notebook?”
“When crises like this occur, DigitalGlobe is committed to supporting the humanitarian community and fulfilling Maxar’s purpose of “Building a better world” by providing critical and actionable information to assist response efforts. As part of our Open Data Program, DigitalGlobe will publicly release pre- and post-event imagery of the affected areas to support disaster response.”
Millions of the trolls’ tweets have since been removed from the service, and while other outlets, most prominently NBC News, have published samplings of them, it has been difficult to get a complete sense of the trolls’ strategy and the scale of their efforts. Until now.
