Speed reading apps help to speed you up
As we all consume more and more information every day, speed reading has become an extremely helpful tool in many busy professionals’ lives. Using mobile devices like smartphones and tablets, various apps have emerged to meet the need.
Below are eight speed reading apps, some for iOS, others for Windows, Android, and even the web. Some of these apps are trainers with exercises, others use the content you’re already reading, some are free, and others cost a few dollars.
1. Spreed (for the web)
Spreed is designed to allow you to copy and paste any text into your browser, and keyboard commands allow you to speed up and slow down the pace as it presents one word at a time, a very popular method of speed reading, allowing your brain to minimize distractions.
2. ReadQuick (for iOS)
If you can get past your sensitivities about the name (grammar nerds know what we mean), ReadQuick is useful in that you can pull in stories from both Instapaper and Pocket where you’ve bookmarked them, and set the pace at which you’d like to zip through them.
3. Speed Reader (for Android)
Speed Reader uses a method called Rapid Serial Visual Presentation, encouraging you to view the center of the screen without saying the words in your head. What sets this app apart is support for most file formats including .txt, .pdf, .html and others, so it’s not just news you can learn to speed read, it can be your documents or manuals you have to get through.
4. Fastr (for iOS)
Faster is an ebook reader with speed reading tools, allowing you to track your progress, highlight and share text, and gives you control over the number of words to display on the screen.
5. Speed Reading (for Windows 8)
Speed Reading is available for Windows 8 devices (desktop, tablet, or smartphone) for free and offers exercises to improve your word speed. The app also keeps track of your progress with improving your speed as you go along.
6. Velocity (for iOS)
Velocity is one of the most popular options, the tech world’s current speed reading darling, and while it is not free, it has one of the most attractive user interfaces and requires no tech savviness to use. Pull in articles from your Pocket, Instapaper, or browser and adjust the speed, either in black and white or white and black.
7. Speed Reading Trainer (for Android)
Speed Reading Trainer offers a diagnostic tool for progress checks and comes with reading materials to practice with so you can improve your comprehension levels while speeding up your reading.
8. QuickReader (for iOS)
Quick Reader isn’t the sexiest app on the planet, but it is extremely well rated with hundreds of reviewers claiming their reading speeds improved, and more than doubled in many cases. Like some of the others, it tracks progress and comes with access to millions of books.
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.
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.
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.”
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.
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.
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.
Social Media2 weeks ago
This non-judgmental app can help you switch to a plant-based diet
Business Finance2 weeks ago
7 ways spending habits have changed since COVID-19
Tech News2 weeks ago
Samsung unveils the latest in holographic tech for smartphones
Opinion Editorials2 weeks ago
4 simple tips to ease friction with your boss while working remotely
Tech News2 weeks ago
The wait is over! mmhmm launches on Mac today
Business News2 weeks ago
Walmart partners with GM for next venture: Driverless delivery
Opinion Editorials1 week ago
Improve UX design by tracking your users’ eye movements
Tech News2 weeks ago
Deepfakes of musicians raise all kinds of moral quandaries