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CAPTCHAs aren’t as secure as we thought

(TECH NEWS) CAPTCHA once the lead the way in internet security but now they can be solved by bots, just like everything else.

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We’ve all been online, trying to purchase some tickets for a show or log into Facebook when that obnoxious box pops up asking us to prove we’re not a robot by just clicking a checkbox or typing in some letters.

Most commonly we see a CAPTCHA, which is a rough acronym for Completely Automated Public Turing Test To Tell Computers and Humans Apart (yeah, CAPTCHA is easier).

So you roll your eyes, type the letters, occasionally cursing under your breath wondering why you have to do something so trivial just to post on your wall or send out that subtweet you’ve been stewing on.

Well, this may not be so simple anymore. According to research recently published in Science magazine, scientists have now have found a way to build an AI that can actually read the CAPTCHA’s you see in your browser AND break the test, allowing them to access a site despite being, well, a robot.

This is not unprecedented; around a decade ago Ticketmaster sued a company that was able to bypass its CAPTCHA system to buy tickets in bulk. That case, however, appeared to be simply an exploitation of a Ticketmaster’s defenses.

The claim is that this new tech will be able to break down the CAPTCHA by deconstructing the text in a much more complex and thorough way, with less specific instructions.

Scientists have been working with AI to try to give it the ability to think like a human (oh no) and they do this using a technique called deep learning. This process is about teaching the AI to look through layers of information, taking each new finding and applying it to its next layer, learning and remembering each time.

This informs the AI’s next decision, and so on. This all, as we’ve seen in films and on television for years, is just a way to get AI to “think” as much like a human brain as possible.

While this isn’t quite to the interrogating-a-possible-replicant level (see Blade Runner), this could be a huge security concern for web developers moving forward. According to a study done with this new AI, the model “was able to solve reCAPTCHAs at an accuracy rate of 66.6% …, BotDetect at 64.4%, Yahoo at 57.4% and PayPal at 57.1%.”

Time to start paying for things with cash again, am I right?

All this research is not only for learning how to break into websites, but for learning how the human’s think and applying that knowledge to building code that will function as closely as possible to the human brain.

Companies like Google have already moved on from basic CAPTCHA’s and it’s hard to say what impact this new discovery will actually have on information security, but this is just the way technology is moving.

While those CAPTCHA’s may be annoying, I’m willing to put in a couple extra seconds to prove I’m human. If AI continues to get smarter, so will the tests that determine who is human or not.

Will hails from Northern California, earned a B.A. in English from Texas A&M University, and now calls Austin, Texas home where he works at a tech startup. He likes riding his bike an ungodly amount of miles and his favorite aesthetic is an open road. If you see him around he'll likely be reading a classic American novel and drinking a Topo Chico.

Tech News

4 ways startups prove their investment in upcoming technology trends

(TECH NEWS) Want to see into the future? Just take a look at what technology the tech field is exploring and investing in today — that’s the stuff that will make up the world of tomorrow.

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Woman testing VR technology

Big companies scout like for small ones that have proven ideas and prototypes, rather than take the initial risk on themselves. So startups have to stay ahead of technology by their very nature, in order to be stand-out candidates when selling their ideas to investors.

Innovation Leader, in partnership with KPMG LLP, recently conducted a study that sheds light onto the bleeding edge of tech: The technologies that the biggest companies are most interested in building right now.

The study asked its respondents to group 16 technologies into four categorical buckets, which Innovation Leader CEO Scott Kirsner refers to as “commitment level.”

The highest commitment level, “in-market or accelerating investment,” basically means that technology is already mainstream. For optimum tech-clairvoyance, keep your eyes on the technologies which land in the middle of the ranking.

“Investing or piloting” represents the second-highest commitment level – that means they have offerings that are approaching market-readiness.

The standout in this category is Advanced Analytics. That’s a pretty vague title, but it generally refers to the automated interpretation and prediction on data sets, and has overlap with Machine learning.

Wearables, on the other hand, are self explanatory. From smart watches to location trackers for children, these devices often pick up on input from the body, such heart rate.

The “Internet of Things” is finding new and improved ways to embed sensor and network capabilities into objects within the home, the workplace, and the world at large. (Hopefully that doesn’t mean anyone’s out there trying to reinvent Juicero, though.)

Collaboration tools and cloud computing also land on this list. That’s no shock, given the continuous pandemic.

The next tier is “learning and exploring”— that represents lower commitment, but a high level of curiosity. These technologies will take a longer time to become common, but only because they have an abundance of unexplored potential.

Blockchain was the highest ranked under this category. Not surprising, considering it’s the OG of making people go “wait, what?”

Augmented & virtual reality has been hyped up particularly hard recently and is in high demand (again, due to the pandemic forcing us to seek new ways to interact without human contact.)

And notably, AI & machine learning appears on rankings for both second and third commitment levels, indicating it’s possibly in transition between these categories.

The lowest level is “not exploring or investing,” which represents little to no interest.

Quantum computing is the standout selection for this category of technology. But there’s reason to believe that it, too, is just waiting for the right breakthroughs to happen.

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Tech News

Internet of Things and deep learning: How your devices are getting smarter

(TECH NEWS) The latest neural network from Massachusetts Institute of Technology shows a great bound forward for deep learning and the “Internet of Things.”

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Woman using smart phone to control other devices in home, connected to deep learning networks

The deep learning that modifies your social media and gives you Google search results is coming to your thermostat.

Researchers at the Massachusetts Institute of Technology (MIT) have developed a deep learning system of neural networks that can be used in the “Internet of Things” (IoT). Named MCUNet, the system designs small neural networks that allow for previously unseen speed and accuracy for deep learning on IoT devices. Benefits of the system include energy savings and improved data security for devices.

Created in the early 1980s, the IoT is essentially a large group of everyday household objects that have become increasingly connected through the internet. They include smart fridges, wearable heart monitors, thermostats, and other “smart” devices. These gadgets run on microcontrollers, or computer chips with no processing system, that have very little processing power and memory. This has traditionally made it hard for deep learning to occur on IoT devices.

“How do we deploy neural nets directly on these tiny devices? It’s a new research area that’s getting very hot,” said Song Han, Assistant Professor of Computer Science at MIT who is a part of the project, “Companies like Google and ARM are all working in this direction.”

In order to achieve deep learning for IoT connected machines, Han’s group designed two specific components. The first is TinyEngine, an inference engine that directs resource management similar to an operating system would. The other is Tiny NAS, a neural architecture search algorithm. For those not well-versed in such technical terms, think of these things like a mini Windows 10 and machine learning for that smart fridge you own.

The results of these new components are promising. According to Han, MCUNet could become the new industry standard, stating that “It has huge potential.” He envisions the system has one that could help smartwatches not just monitor heartbeat and blood pressure but help analyze and explain to users what that means. It could also lead to making IoT devices far more secure than they are currently.

“A key advantage is preserving privacy,” says Han. “You don’t need to transmit the data to the cloud.”

It will still be a while until we see smart devices with deep learning capabilities, but it is all but inevitable at this point—the future we’ve all heard about is definitely on the horizon.

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Tech News

Google is giving back some privacy control? (You read that right)

(TECH NEWS) In a bizarre twist, Google is giving you the option to opt out of data collection – for real this time.

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Open laptop on desk, open to map privacy options

It’s strange to hear “Google” and “privacy” in the same sentence without “concerns” following along, yet here we are. In a twist that’s definitely not related to various controversies involving the tech company, Google is giving back some control over data sharing—even if it isn’t much.

Starting soon, you will be able to opt out of Google’s data-reliant “smart” features (Smart Compose and Smart Reply) across the G-Suite of pertinent products: Gmail, Chat, and Meet. Opting out would, in this case, prevent Google from using your data to formulate responses based on your previous activity; it would also turn off the “smart” features.

One might observe that users have had the option to turn off “smart” features before, but doing so didn’t disable Google’s data collection—just the features themselves. For Google to include the option to opt out of data collection completely is relatively unprecedented—and perhaps exactly what people have been clamoring for on the heels of recent lawsuits against the tech giant.

In addition to being able to close off “smart” features, Google will also allow you to opt out of data collection for things like the Google Assistant, Google Maps, and other Google-related services that lean into your Gmail Inbox, Meet, and Chat activity. Since Google knowing what your favorite restaurant is or when to recommend tickets to you can be unnerving, this is a welcome change of pace.

Keep in mind that opting out of data collection for “smart” features will automatically disable other “smart” options from Google, including those Assistant reminders and customized Maps. At the time of this writing, Google has made it clear that you can’t opt out of one and keep the other—while you can go back and toggle on data collection again, you won’t be able to use these features without Google analyzing your Meet, Chat, and Gmail contents and behavior.

It will be interesting to see what the short-term ramifications of this decision are. If Google stops collecting data for a small period of time at your request and then you turn back on the “smart” features that use said data, will the predictive text and suggestions suffer? Only time will tell. For now, keep an eye out for this updated privacy option—it should be rolling out in the next few weeks.

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