How to tell if your child has a future in computer science

Are you smarter than a supercomputer? 4-year-olds are

New research from the University of Illinois pitted an advance AI against children's IQ test

Microsoft CEO Announces $75 Million for Computer Science education expansion

West Seattle and Sealth High Schools will benefit from TEALS program

Microsoft CEO Satya Nadella announced on Sept. 16 a new commitment of $75 million in community investments over the next three years to increase access to computer science (CS) education for all youth, and especially for those from under-represented backgrounds.

This new investment has a significant impact in Washington State, particularly in West Seattle:
· As part of this investment, Microsoft will expand its Technology Education and Literacy in Schools (TEALS) program to 11 new schools in Washington state this fall, including Chief Sealth High School and West Seattle High School. This brings Washington’s number of TEALS schools to 57, up from 46 last school year.

· The program’s local growth is part of Microsoft’s nationwide expansion of TEALS. The U.S. program, which started in 2009, aims to grow five-fold over the next three years, with the goal of working with 2,000 tech industry volunteers to reach 30,000 students in nearly 700 schools across 33 states.

TEALS is a Microsoft YouthSpark program that recruits, trains, mentors and places high-tech professionals who are passionate about bringing computer science education into high schools as volunteer teachers in a team teaching model.

· TEALS provides schools with both curricula and highly qualified volunteer teachers for computer science courses without any training or development costs to the schools themselves.

· Because TEALS teachers always team teach with a school teacher, the school teachers can learn the course material and further down the line, teach some of the courses by themselves.

· In Washington:
o During the TEALS pilot year in Washington state, 10 TEALS volunteers partnered with four Puget Sound area high schools, reaching 250 students.
o Today, TEALS is in 57 Washington state high schools.

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How to delete Microsoft’s unwanted Windows 10 download files

Yesterday, we discussed how Microsoft now downloads Windows 10 to local devices whether users have chosen to do so or not. Here, we’ll walk you through the process of reclaiming that space. The surest way to tell if you’ve been affected by the stealth download is to navigate to your C:\Windows directory. Once there, you’ll want to configure Explorer to show hidden files and folders.

In Windows 7, you do this by clicking on “Tools,” then “Folder Options,” and finally “Show Hidden Files and Folders,” as shown below. In Windows 8/8.1, click on the View tab and then select the “Hidden items” check box.

Once this is done, check your Windows directory for a directory named $WINDOWS.~BT. The icon may be translucent, since the folder is normally hidden, so check carefully. You can delete this folder if you wish, but doing so won’t actually prevent Microsoft from downloading the setup program again. Once the OS has decided that you’re going to install Windows 10, it’s downright pushy about having the data locally. The only solution, according to various sources, is to actually remove a specific Windows Update: KB3035583.

KB3035583 is described by Microsoft as installing “the Get Windows 10 app, which helps users understand their Windows 10 upgrade options and device readiness.” It can be uninstalled by navigating to Windows Update from within the Control Panel, choosing “Programs and Features,” and then selecting the “View Installed Updates” option. Remove this update and then delete the folder, and you’ll reclaim your lost disk space.

KB 3035583 can then be blocked from installing again by hiding the update from within the Windows Update setting in Control Panel.

An uncertain situation

There are facets to this situation that aren’t fully understood as yet. My own Windows Update history shows that I installed KB3035583 on the 26th of July, as shown below.

Despite this, there’s no sign that my system ever downloaded Windows 10, and I have no record of failed W10 installations (another reported commonality) in my own Windows Update history. In some cases, this MS update clearly triggers a download process, but in others, it does not seem to do so. I personally run Windows 7 Professional, but IE11 and Windows Update have both been incessantly nagging me to upgrade.

One potential reason for this is that I keep Windows set to “Check for updates but let me choose whether to download and install them.” It’s possible that this setting keeps Windows 10 from downloading whether you’ve installed KB 3035583 or not.

Why we cover topics like this

Several readers have asked why we continue to cover topics like this and implied that ET (or myself) have a bias against Windows 10. I won’t deny that I disagree with Microsoft’s new approach to privacy controls, patch disclosure, and software updates, but that’s not why we’ve continued covering these topics. Whether you agree or disagree that some of Microsoft’s new policies are problematic, the fact is, they represent a marked change from the status quo.

A 6GB OS download isn’t a big deal if you have a 500GB drive, but if you’re running an older Windows installation on a 128-256GB SSD, that can wind up being a significant chunk of space. More to the point, however, it’s something Microsoft hasn’t previously done. The thinking, in this case, is obvious — by downloading Windows 10 behind-the-scenes, Microsoft guarantees a faster upgrade process for end users.

The problem, once again, isn’t that Microsoft is evil. The problem is that Microsoft either failed to consider the needs of its users or dismissed them as unimportant. We’ve already heard from people who went over their metered bandwidth for the month because of background Windows 10 downloads. One of our staff had an HTPC surprise-upgrade itself to Windows 10 while he was on vacation. These are problems that Microsoft could address with a simple checkbox asking users if they’d like to download Windows 10 now so they can start the upgrade process immediately when they choose to do so.

Graphics processors accelerate pattern discovery

Repeating patterns in complex biological networks can now be found hundreds of times faster using an algorithm that exploits the parallel computing capacity of modern graphics adapters1. The A*STAR-led breakthrough opens the possibility of rapid genome scans for discrete molecular structures.

A network motif is a statistically significant connection of nodes that appears more frequently than chance would allow. In the gene transcription network for the bacteria Escherichia coli, for example, a simple network motif arises in the process by which atranscription factor responds to itself, known as negative auto-regulation. Such a motif occurs repeatedly in the transcriptome.

“This negative auto-regulation process has essential biological functions,” explains Wenqing Lin from the A*STAR Institute for Infocomm Research. “Searching for these repeating ‘graphs’ is of particular importance in the study of network functionality.”

These searches, however, are a significant computational drain and increasing the rate of motif discovery is a steep mathematical challenge. “Even state-of-the-art solutions require several days to derive network motifs from networks with only a few thousand vertices,” says Lin.

The research team harnessed the capabilities of the modern computer graphics processors to overcome the limitations of existing network motif search algorithms. Graphics processing units often comprise thousands of computing cores, allowing Lin’s team to adapt a large number of the computational tasks involved in graph mining. This can significantly reduce computation time.

By developing a parallelized code that utilizes the capabilities of graphical processing units (GPUs), including simultaneous execution of code on multiple GPU cores and efficient memory access patterns, the team was able to expedite the search by up to 100 times — the improved rate was confirmed through extensive experiments on a variety of biological networks.

The study demonstrates the feasibility of using GPUs for network motif search tasks. GPUs are also around 20 times cheaper than computer processors for equivalent performance, highlighting the potential for large-scale search projects.

Network motif discovery has many applications beyond biology, including pattern detection in digital circuits and other non-random networks. “Our research results can also be applied to solving the problems of enumerating all subgraphs of a large network, and finding the matches for a given subgraph in a large network,” says Lin. “Both of these problems are fundamental aspects of graph mining and graph databases.”

The A*STAR-affiliated researchers contributing to this research are from the Institute for Infocomm Research

Reference

1. Lin, W., Xiao, X., Xie, X. & Li, X.-L. Network motif discovery: A GPU approach. IEEE 31st International Conference on Data Engineering (ICDE), 831–842 (2015).