Connect with us

Tech News

Lambda wants you to learn to code without paying immediately

(TECH NEWS) Lambda coding program wants you to focus on learning code rather than focus on paying to learn to code. This program gives you options.

Published

on

remote workforce

Learn to code

Computer programing is in, and those of us who majored in Coffeehouse Ethics or Philosophy of Matcha are taking notice.

bar
Regrettably, those same fields aren’t renowned for being particularly lucrative, which is why Lambda’s decision to offer a comprehensive, six-month coding bootcamp for no up-front charge comes as a refreshing relief.

Free Until It’s Not

To be clear, the education itself isn’t free—the total charge for a six-month full-time course is $20,000. However, Lambda offers several different reimbursement programs, starting at $0 up-front. Once you complete the course and get a job, you pay back your tuition with 17 percent of your salary for two years.

There are varying degrees of reimbursement as well.

For example, you can opt to pay half of the tuition after you complete the course, thereby lowering your reimbursement period to one year of paying 17 percent of your salary.

Finally, the maximum amount that Lambda will accept from you caps out at $30,000, meaning that you don’t have to worry about losing a huge chunk of a high-paying salary.

Full-Time Coding

When in the program, you’ll spend the hours of 9:00 AM through 6:00 PM PST learning the ins and outs of basic C++ and JavaScript programming in multiple different fields, including mobile platforms. The idea is that, after six months of specific direction from live instructors, you will have a firm grasp of computer programming fundamentals.

The lack of an up-front fee makes this full-time coding schedule all the more alluring, since one is unlikely to have a full-time job in conjunction with eight-plus hours per day of intensive coding instruction.

Positive Reception

A glance at Course Report’s Lambda page shows how overwhelmingly positive this experience has been for students thus far. Rarely does any educational institution amass five-star reviews with little in the way of criticism, but Lambda’s program seems to be legitimate enough to warrant working with the Y Combinator seed accelerator—a feat that speaks volumes for Lambda’s credibility.

If you’re even remotely interested in computer programming and you’d like to dip your toes in the water, Lambda’s program may be the opportunity you need to start your programming career.

#LambdaCoding

Jack Lloyd has a BA in Creative Writing from Forest Grove's Pacific University; he spends his writing days using his degree to pursue semicolons, freelance writing and editing, oxford commas, and enough coffee to kill a bear. His infatuation with rain is matched only by his dry sense of humor.

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.

Published

on

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.

Continue Reading

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.”

Published

on

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.

Continue Reading

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.

Published

on

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.

Continue Reading

Emerging Stories

Get The American Genius
neatly in your inbox

Subscribe to get business and tech updates, breaking stories, and more!