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Archivo del Autor: Belen De Leon

Fortnite season 5, week 3 challenges and how to complete them – CNET

Celebrate Fortnite’s birthday update by beating this week’s challenges.
Source: CNET

Congress members demand answers from Amazon about facial recognition software

When we called the ACLU’s Amazon’s Rekognition press release an “attention-grabbing stunt” when we wrote about it earlier today, well, consider that attention grabbed. Several Democratic members of Congress have responded with a strongly worded letter to founder Jeff Bezos.

Reps. Jimmy Gomez and John Lewis issued a letter to Bezos, after the ACLU noted that the facial recognition software falsely associated 28 images of Congress members with mugshots in a criminal database. Lewis, a pivotal figure in America’s civil rights moment, was among those falsely matched in the ACLU’s testing — particularly notable as the testing appeared to have a particular bias against people of color.

“The results of the ACLU’s test of Amazon’s ‘Rekognition’ software are deeply troubling,” Lewis wrote in a statement. “As a society, we need technology to help resolve human problems, not to add to the mountain of injustices presently facing people of color in this country. Black and brown people are already unjustly targeted through a discriminatory sentencing system that has led to mass incarceration and devastated millions of families.”

A trio of Congress members (Sen. Ed Markey and Reps. Luis Gutiérrez and Mark DeSaulnier), meanwhile, wrote a letter addressed to Bezos with a series of questions about the technology:

While facial recognition services might provide a valuable law enforcement tool, the efficacy and impact of the technology are not yet fully understood. In particular, serious concerns have been raised about the dangers facial recognition can pose to privacy and civil rights, especially when it is used as a tool of government surveillance, as well as the accuracy of the technology and its disproportionate impact on communities of color.

Amazon for its part, both defended Rekognition and disputed the ACLU’s methods. “We remain excited about how image and video analysis can be a driver for good in the world, including in the public sector and law enforcement,” the company wrote in a statement provided to TechCrunch.

With regard to testing, it says:

[W]e think that the results could probably be improved by following best practices around setting the confidence thresholds (this is the percentage likelihood that Rekognition found a match) used in the test. While 80% confidence is an acceptable threshold for photos of hot dogs, chairs, animals, or other social media use cases, it wouldn’t be appropriate for identifying individuals with a reasonable level of certainty. When using facial recognition for law enforcement activities, we guide customers to set a threshold of at least 95% or higher.

The company also reiterated an earlier statement that the results are intended to be used to narrow down results, rather than lead directly to arrests.

Regardless, the ACLU’s stunt certainly got the attention the organization was seeking, both with regard to the aforementioned biases and broader security implications of facial scanning for law enforcement.


Source: TechCrunch

Much of the US Electric Grid Could Go the Way of the Landline Phone

As renewable energy picks up and electricity demand drops, it’s getting way more expensive for a large part of grid to produce electricity, and that’s a problem for everyone.
Source: Wired

Slack forms key alliance as Atlassian throws in the towel on enterprise chat

With today’s announcement from Atlassian that it was selling to Slack the IP assets of its two enterprise communications tools, HipChat and Stride, it closes the book on one of the earliest competitors in the modern enterprise chat space. It also was a clear signal that Slack is not afraid to take on its giant competitors by forming key alliances.

That the announcement came from Slack co-founder and CEO Stewart Butterfield on Twitter only exacerbated that fact. Atlassian has a set of popular developer tools like Jira, Confluence and Bitbucket. At this point, HipChat and Stride had really become superfluous to the company and they sold the IP to their competitor.

Not only is Slack buying the assets and Atlassian is effectively shutting down these products, Atlassian is also investing in Slack, a move that shows it’s throwing its financial weight behind the company, as well, and forming an alliance with them.

Slack has been burning it up since in launched in 2014 with just 16,000 daily active users. At last count, in May, the company was reporting 8 million active users, 3 million of which were paid. That’s up from 6 million DAUs and 2 million paid users in September 2017. At the time, the company was reporting $200 million in annual recurring revenue. It’s a fair bet with the number of paid users growing by one-third at last count, that revenue number has increased significantly, as well.

Slack and products of its ilk like Workplace by Facebook, Google Hangouts and Microsoft Teams are trying to revolutionize the way we communicate and collaborate inside organizations. Slack has managed to advance the idea of enterprise communications that began in the early 2000s with chat clients, advanced to Enterprise 2.0 tools like Yammer and Jive in the mid-2000s and finally evolved into modern tools like Slack we are using today in the mobile-cloud era.

Slack has been able to succeed so well in business because it does much more than provide a channel to communicate. It has built a platform on top of which companies can plug in an assortment of tools they are using every day to do their jobs, like ServiceNow for help desk tickets, Salesforce for CRM and marketing data and Zendesk for customer service information.

This ability to provide a simple way to do all of your business in one place without a lot of task switching has been a Holy Grail of sorts in the enterprise for years. The two previously mentioned iterations, chat clients and Enterprise 2.0 tools, tried and failed to achieve this, but Slack has managed to create this single platform and made it easy for companies to integrate services.

This has been automated even further by the use of bots, which can act as trusted assistants inside of Slack, providing additional information and performing tasks for you on your behalf when it makes sense.

Slack has an otherworldly valuation of more than $5 billion right now, and is on its way to an eventual IPO. Atlassian might have thrown in the towel on enterprise communications, but it has opened the door to getting a piece of that IPO action while giving its customers what they want and forming a strong bond with Slack.

Others like Facebook and Microsoft also have a strong presence in this space and continue to build out their products. It’s not as though anyone else is showing signs of throwing up their hands just yet. In fact, just today Facebook bought Redkix to enhance its offering by giving users the ability to collaborate via email or the Workplace by Facebook interface, but Atlassian’s acquiescence is a strong signal that if you had any doubt, Slack is a leader here — and they got a big boost with today’s announcement.


Source: TechCrunch

You can buy the NES Classic and SNES Classic on Amazon now

If you missed the first few rounds of excitement about Nintendo’s mini nostalgia machines, you’ve got another shot at paying a normal price.

Nintendo’s NES and SNES Classic consoles aren’t always easy to find, but they’re now available from Amazon for $59.99 (NES Classic) and $79.99 (SNES Classic). You can place an order for either right now, though be aware that the NES Classic won’t ship until it’s back in stock on August 12 and the SNES Classic looks like it’ll be back on August 3 — a pretty reasonable wait for a sure thing.

Update: It looks like Amazon’s stock of the NES Classic may have already run out in the course of the last few minutes, though the SNES version is still available at its normal retail price of $79.99 (and let’s be real, it was the best console). They seem to be dropping in and out of availability, so try refreshing!

When they were first introduced, the reimagined versions of two of the best-loved consoles of all-time arrived to feverish demand. Back in 2016, the NES Classic was difficult to hunt down, and when it hit in August 2017, the SNES followed suit, managing to even outpace interest in its own progenitor. (Naturally, scarcity is the perfect fuel for a nostalgia-powered fire.)

Nintendo originally didn’t intend for either console to be restocked indefinitely, but after observing the “unbridled enthusiasm” of the retro gaming boxes it decided to keep them around. The consoles reappeared in May and June but sold out quickly.

Even with the repeat appearances, it’s been hard to keep track of when and where the things go on sale. If you’re reading this and you’ve yet to score a one-way ticket to nostalgic 8- or 16-bit euphoria, the Amazon listings look like a sure bet — for the moment, anyhow.


Source: TechCrunch

Just Some Other Totally Legit Microbes That Will Definitely (Not) Make Your Tech Startup a Unicorn

A study this week got people thinking that infection by *Toxoplasma gondii*, a parasite found in cat poop, could be used to prime people for entrepreneurship. We’ve got some ~~better~~ equally terrible ideas.
Source: Wired

Hallados cientos de robots mal asegurados y vulnerables a los hackers

Una investigación ha sido capaz de acceder al sistema e incluso controlar los movimientos de más de un centenar de máquinas conectadas al sistema operativo ROS. Esto podría tener consecuencias fatales si un hacker malintencionado accede a alguno de ellos 
Source: MIT

Un ojo recién arrancado puede burlar un control de seguridad ocular

Un algoritmo ha aprendido a distinguir un iris vivo de uno muerto con una precisión increíble. Pero estas diferencias no aparecen hasta 16 horas del fallecimiento, lo que da un breve espacio de tiempo para que los hackers engañen un escáner de iris con ojo recién robado 
Source: MIT

This 3D-printed AI construct analyzes by bending light

Machine learning is everywhere these days, but it’s usually more or less invisible: it sits in the background, optimizing audio or picking out faces in images. But this new system is not only visible, but physical: it performs AI-type analysis not by crunching numbers, but by bending light. It’s weird and unique, but counter-intuitively, it’s an excellent demonstration of how deceptively simple these “artificial intelligence” systems are.

Machine learning systems, which we frequently refer to as a form of artificial intelligence, at their heart are just a series of calculations made on a set of data, each building on the last or feeding back into a loop. The calculations themselves aren’t particularly complex — though they aren’t the kind of math you’d want to do with a pen and paper. Ultimately all that simple math produces a probability that the data going in is a match for various patterns it has “learned” to recognize.

The thing is, though, that once these “layers” have been “trained” and the math finalized, in many ways it’s performing the same calculations over and over again. Usually that just means it can be optimized and won’t take up that much space or CPU power. But researchers from UCLA show that it can literally be solidified, the layers themselves actual 3D-printed layers of transparent material, imprinted with complex diffraction patterns that do to light going through them what the math would have done to numbers.

If that’s a bit much to wrap your head around, think of a mechanical calculator. Nowadays it’s all done digitally in computer logic, but back in the day calculators used actual mechanical pieces moving around — something adding up to 10 would literally cause some piece to move to a new position. In a way this “diffractive deep neural network” is a lot like that: it uses and manipulates physical representations of numbers rather than electronic ones.

As the researchers put it:

Each point on a given layer either transmits or reflects an incoming wave, which represents an artificial neuron that is connected to other neurons of the following layers through optical diffraction. By altering the phase and amplitude, each “neuron” is tunable.

“Our all-optical deep learning framework can perform, at the speed of light, various complex functions that computer-based neural networks can implement,” write the researchers in the paper describing their system, published today in Science.

To demonstrate it they trained a deep learning model to recognize handwritten numerals. Once it was final, they took the layers of matrix math and converted it into a series of optical transformations. For example, a layer might add values together by refocusing the light from both onto a single area of the next layer — the real calculations are much more complex, but hopefully you get the idea.

By arranging millions of these tiny transformations on the printed plates, the light that enters one end comes out the other structured in such a way that the system can tell whether it’s a 1, 2, 3 and so on with better than 90 percent accuracy.

What use is that, you ask? Well, none in its current form. But neural networks are extremely flexible tools, and it would be perfectly possible to have a system recognize letters instead of numbers, making an optical character recognition system work totally in hardware with almost no power or calculation required. And why not basic face or figure recognition, no CPU necessary? How useful would that be to have in your camera?

The real limitations here are manufacturing ones: it’s difficult to create the diffractive plates with the level of precision required to perform some of the more demanding processing. After all, if you need to calculate something to the seventh decimal place, but the printed version is only accurate to the third, you’re going to run into trouble.

This is only a proof of concept — there’s no dire need for giant number-recognition machines — but it’s a fascinating one. The idea could prove to be influential in camera and machine learning technology — structuring light and data in the physical world rather than the digital one. It may feel like it’s going backwards, but perhaps the pendulum is simply swinging back the other direction.


Source: TechCrunch

Amazon's Facial Recognition System Mistakes Members of Congress for Mugshots

Amazon has marketed its Rekognition facial recognition system to law enforcement. But in a new ACLU study, the technology confused 28 members of Congress with publicly available arrest photos.
Source: Wired

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