As the 2021 year comes to a close and we anticipate what’s to come in 2022, it’s with great appreciation and honor to announce that Dogtown Media has received a global accolade from the major digital rating agency, Clutch.co, as a Top Global B2B Company for 2021.

After 10 years in the mobile app space, reaching a highly regarded and recognized global accolade is a major accomplishment and points to the continued dedication of Dogtown Media to their global client base and their hyper-focus on producing high-quality applications. 

Dogtown Media is Los Angeles’ leading mobile application company, working with organizations in nearly every vertical to bring their unique ideas and solutions to the app market. Dogtown Media prides itself on the satisfaction, approval, and happiness of our clients. And aims to create cutting-edge solutions that are pushing the boundaries of what’s thought o be possible in the mobile application space.

the mobile application space.

And for those who may be unaware, this Clutch.co accolade is only one in a series of major accolades awarded to Dogtown Media such as Top 2021 B2B Leader in Artificial Intelligence for Robotics, a top 2020 Service Provider, and the 27th Best B2B Service Provider in the World in 2019. All of these great accolades point to the dedication to craft and customer, and only scratch the surface of their long laundry list of accolades from Clutch and other prominent rating agencies in the mobile app space. 

“This recognition feels surreal and we are lost for words”, notes founder Marc Fischer. “We feel truly honored to be recognized by such a prestigious rating firm, and hope to continue to provide high-quality, meaningful applications for our clients today and far into the future. “

Here are some of the quotes that stood out most to us:

Here are some of the quotes that stood out most to us:

“They were an effective team, met deadlines, and created a great end product.“. — Director, Risk Comm Lab, Temple University

“They built an intuitive and simple design, and the team works quickly to address bugs and solve problems.”— Senior Ops Manager, Hospital Innovation Lab

Let’s build something amazing together! Connect with us and get a free tech consultation.

Mobile is the future. At Dogtown Media, we help you build your dream apps and technologies. Known as Los Angeles’ finest, we’ve delivered brilliantly created and intuitive products that help companies digitally transform. We are a proud team that puts our money where our mouths are.

With that in mind, we are absolutely excited to announce that we have teamed up with Top Design Firms, a creative portfolio site, for their inaugural launch!

Brought by the creators of Clutch, Top Design Firms is a new platform that is designed to help companies stay in the know about different industries and services providers. The site encompasses the IT, design, development, and marketing spaces, helping users find the right firm to help their unique needs.

According to Top Design Firms, we rank among the top 100 in 2021 in the category of artificial intelligence app development. As service providers, this highlight means a lot to us. Our team’s growth, dedication, and excellence is paying off, and this new partnership will take all those to a whole new level.

Want to know how we made it on their list? The Top Design Firms’ team evaluated our company based on a set of criteria, screening our past projects, recognitions, and market position. Our strong presence on Clutch also allowed us to rank highly.

With 27 reviews as of press time, Dogtown Media is honored to be a top-performer on Clutch. Here are some of our clients’ phenomenal reviews:

The fact that they’ve done this before for several other health systems is great. They know exactly how to tailor their product and what to ask the client. Their team has really perfected the art of this. They’re responsive and quick to make any improvements or changes. Dogtown Media is great to work with.”

— Senior Management Associate, Atrium Health

“As a program manager, having Dogtown Media always deliver on their promises is a big plus. They’ve never let me down. I also appreciated their ability to generate a report in the fashion requested. It serves everyone who works on the detailed aspects of the project and gives staff at the senior management level an overview of progress. We were very pleased with their work.” 

— Engineering Consultant, Biotronik

Ready to transform and innovate? Get in touch with Dogtown Media and let’s work hand in hand to bring your ideas into reality. Send us a message today and schedule a free consultation with our team. 

In late 2020, Alphabet – the parent company of Google – solved one of biology’s most challenging problems with the help of AI – predicting the structure of proteins. Alphabet’s DeepMind – a branch of Alphabet dedicated to the development and progress of AI – built AlphaFold, an AI designed specifically for this task and to everyone’s surprise…it worked.

Alphabet’s attempt to develop an AI that could predict protein structures was hugely successful when AlphaFold won a biennial protein-predicting challenge called CASP; something that hasn’t happened before in the history of mankind. Founder of the competition, John Moult, a computational biologist at the University of Maryland was astounded by the results noting “It was the first time a serious scientific problem had been solved by AI.”

Today, being able to predict protein structures in a repeatable verifiable method will undoubtedly accelerate the development of drugs and vaccines, reshape how organizations engage artificial intelligence app development and provide key insight into how diseases work, all thanks to AI.

AI and the Fight Against Chagas and Leishmaniasis

Flash forward 9 months, Alphabet’s DeepMind is on the hunt for another biological breakthrough, this time targeting some of the world’s most challenging diseases Chagas and Leishmaniasis. Chagas and Leishmaniasis are two of the world’s deadliest parasitic diseases transmitted by hosts known as assassin bugs. These two diseases alone are known to affect up to 23 million people worldwide.

The Challenges Associated with Deadly Parasitic Diseases

Unfortunately, today’s drugs and therapeutics are widely ineffective at treating both of these diseases and even worse “patients affected by neglected diseases like Leishmaniasis and Chagas disease rely on outdated treatments that are sometimes toxic, have serious side-effects, and are often not fit for purpose,” London-based Alphabet-owned lab known as Drugs for Neglected Diseases initiative lead Ben Perry said.

For those affected, Chegas and Leishmaniasis can produce flu-like symptoms, rash, loss of appetite, Diarrhea, vomiting and in extreme cases without medical attention, death or permanent health complications. Understandably with 23 million people affected each year, primarily in underserved and neglected communities around the world, a more advanced medication or therapeutic to treat these parasitic diseases could be a game changer.

AI and the Future of Medicine

Now, after the massive scientific discovery made by AlphaFold related to predicting protein structures in late 2020, DeepMind may have the needed key to providing new advanced medication and therapeutics to fight changas and Leishmaniasis. Many diseases including these two deadly parasitic diseases are linked to the roles of proteins in catalysing chemical reactions and fighting diseases. By being able to predict and understand protein structures – specifically related to these parasitic diseases – DeepMind’s Drugs for Neglected Diseases initiative now has the insight to provide medication or even a cure for these diseases. And AI isn’t only accelerating discovery in the world of biology and protein structures.

Just this week a new AI designed by the UAE has been proven to improve breast cancer detection, avoid unnecessary biopsies, and improve patient experience. The AI known as Mammography Intelligent Assessment (Mia) is the first AI-enabled monogram reader for breast cancer screening that is available commercially. By training the advanced AI Mia with millions of mammogram images, Mia is now producing mammogram readings that are as effective as a mammogram reading delivered by a consulting radiologist. Also Los Angeles-based UCLA’s Deepcell looks to build on these advances in AI-driven medical diagnostics to expand cell morphology to identify and sort cancer cells from clinical cytology cells.

Of course, this has far reaching implications for the medical industry, medical personnel and radiologists. Will AI augment how Radiologists diagnose and offer medical services, or will AI offer a low-cost alternative to diagnostics?

As AI continues to uncover the answers to biology’s biggest mysteries, what can we expect for the future? Could AI tackle some of mankind’s most challenging medical challenges such as cancer, aging or vaccines for tomorrow’s novel virus? It seems that only AI will be able to provide the answer to that question. With AI sweeping the competition at CASP and cracking the code of Leishmaniasis and Chagas, we are optimistic that we will continue to see massive medical and biological breakthroughs in the near future.

A new artificial intelligence (AI) algorithm is testing just how important attractiveness is by attempting to figure out who you’ll find attractive and why you find that person attractive. A team comprised of researchers from the University of Helsinki and Copenhagen University generated images of fake faces that they then asked people to rate for attractiveness. It then used that feedback to further tune the AI algorithm, making it perform even better at generating fake attractive faces.

Adversarial Strengths

The application, which uses a machine learning development algorithm called generative adversarial network (GAN), creates fake faces by pitting two “adversarial” algorithms against one another. Adversarial means the two algorithms have differing goals: one, called the generator, creates images based on what it learned during its training phase, and the other (called the discriminator) tries to figure out which of the generated images are fake or real. The latter algorithm is tested with photos of real people and fake faces.

The two algorithms eventually start training each other in a loop that allows the generator and discriminator to improve their performance greatly with each cycle. The generator improves its ability to create realistic images, and the discriminator gets better at finding fake faces. This symbiotic relationship may first sound unproductive, but the algorithms work well together and also successfully test each other.

The GAN algorithm was trained on 200,000 images of celebrities, who usually have attractive faces—at least, according to Hollywood standards.

Testing Attractiveness

After the training phase, the generative algorithm developed hundreds of unique faces of people who it believed were of similar attractiveness as the celebrities it “knew” to be attractive. These fake faces were shown to real people who wore brain-computer interfacing equipment hooked up to an EEG (electroencephalography) reader. Using this data, the researchers could measure each person’s brain activity for each photo they saw, down to the neuron’s exact moment of firing.

When a participant saw an image of an attractive face, there was a marked increase in brain activity. This could be partially attributed to the fact that the participants were told to focus harder on faces they thought were attractive. The participants weren’t asked to articulate what specifically they found attractive about any of the images. Instead, the AI stored the EEG datapoints and found the commonalities within each photo.

Those commonalities could be big eyes, high cheekbones, a medium-sized nose, wide-set eyes, small ears, or any other facial feature. The AI found that most participants liked the same aspects of a face in an image. In other words, humans seem to favor most of the same facial features when asked about attractiveness.

Using the common features found by the algorithm, the team distilled this data back down in a format that could be fed to the GAN algorithm. The generative algorithm then took this new information as instruction in making its second batch of attractive faces. Now, the faces had more chiseled jawlines, darker and more mysterious eyes, curlier hair, and more features that we find conventionally more attractive.

Real Looks vs. Fake Faces

When this second round of generated photos was shown to participants, they were instructed to rate the face as attractive or unattractive. For 87% of the newly-generated photos, participants rated the face as attractive. The remaining 13% were either too perfect or there was something that seemed off about their facial features. Even though the participants were told to focus on attractiveness, they were unable to look past how some faces looked fake or off.

AI developers and AI ethics experts worry that this type of well-performing technology could be used to generate faces that look realistic for the purposes of deepfake videos or fake images. Not only do the faces not need to be real, they don’t need to be attractive to cause issues for people or even nations. And the consequences don’t need to be so far-reaching: even social media accounts used for a malicious purpose could use AI-generated fake faces to blend in with the crowd. They might even look normal and real at a quick glance. After all, how much detail can you see in a small circular avatar?

The Future of Dating?

The future of this type of technology extends far beyond dating and social media. It could be used for political gain or even start a war. The research team is interested in advancing the technology, and it has some ideas for how to use their application in a productive and non-malicious way. Associate professor at the University of Helsinki, Tuukka Ruotsalo, says that the team hopes to dig deeper into attractiveness, as well as explore stereotypes, biases, preferences, and individual differences.

Have you come across an AI-generated face that was attractive but looked off? How did it make you feel? Let us know in the comments below!

Chatbots are a natural fit for enhancing customer service, especially in an online or mobile setting, and we run into them on websites, in hospitals, on social media, and in mobile apps. There is room for this AI-enabled application in almost every business vertical, but there are pros and cons to be aware of when developing your first chatbot.

Chatbots in Customer Support

Customer support can be grueling. It requires businesses to provide friendly, responsive, and quick help at almost any time of the day. Because of the large investment involved in hiring people and building resources, it is difficult to build an excellent customer support team overnight.

It takes a lot of constant training and ongoing optimization to finetune your support representatives to meet all key performance indicators, like time-to-first-response, time-to-close-ticket, and customer satisfaction or feedback. Instead of skimping on one of your most important customer-facing departments, consider what a chatbot can unlock for you and your customers. Whether your company is a Fortune 500 company, doctor’s office, or a corner grocery store, your business can create and deploy a chatbot quickly and easily without a massive investment.

Benefits of Chatbots in Business

Increase Customer Happiness

Every company is in the business of making their customers happy. It’s what keeps profits steady and brand recognition strong. Thankfully, chatbots fit right into that notion as they are 100% customer-centric.

Chatbots work to answer user questions as fast as possible to reach a resolution on the question at hand. They help customers with the same efficiency and response rate, unlike humans which respond to various queries with different response times. This reliability can give customers more consistent expectations of interacting with your company.

If done right, chatbots can improve customer satisfaction. For example, an customer service representative based in Los Angeles may not be able to speak Japanese to help a customer, but a chatbot can easily switch to a different language on the fly. This unlocks the added benefit of reaching many more customers without having to hire interpreters or native speakers.

Leave an Impression on Customers

Besides serving up a consistent experience that customers can count on, chatbots offer customers the opportunity to “ooh” and “aah” over your company’s use of the most cutting-edge AI and machine learning technology. Many customers enjoy interacting with a chatbot, and engagement rates have been increasing steadily.

In 2019, nearly 40% of retail customers engaged with a chatbot in their search for an answer. When chatbots work well, they can bolster your brand image. They can also help customers see your company as an industry leader.

Available Around-the-Clock

Unlike people, chatbots can be “on” 24/7 without feeling exhausted or needing a break. They can help a customer whenever they need it and from wherever they’re located. Chatbots can stay on indefinitely and use customer feedback to continuously improve their success rates.

Generate Better Leads

Besides helping people with their questions and issues, chatbots can also generate leads. Add in a spam filter, and you can even generate better leads than your contact forms. In on-demand delivery apps, chatbots are often used to take orders and process payments from new customers. This can reduce the amount of time it takes to get a new lead to purchase a product from your company.

More Cost-Effective

Because chatbots don’t require healthcare or sick days, chatbots are much cheaper in the long run compared to a traditional customer support team. They use fewer resources like office space, money, and equipment. Chatbots cost a one-time investment fee, and they need minimal maintenance to continue performing.

Downsides of Chatbots

Talking to a Computer

At the end of the day, most chatbots can’t help customers shake the feeling that they’re talking to an automated AI application. For many customers, their problems can only be solved by a human, and this often includes problems with a purchase, shipping, or credit card charge. For these customers, interacting with a chatbot can feel futile and frustrating.

Although natural language processing technology has come a long way in the past few years, we still haven’t reached a point where chatbots feel human. Fluid language isn’t possible yet. Even the best chatbots can’t make customers feel like they’re talking to a human.

Difficult to Develop

Chatbots can be difficult to design and develop, especially if your company’s use case is complex. When adding machine learning technology into the mix, chatbot development can get downright arduous. As it stands, companies need to spend a lot of time, effort, and server space in creating their chatbot.

Most businesses need chatbots for simpler needs, however, like customer support which can run on pattern-based algorithms. There are already no-code or low-code platforms that offer brands the ability to create a custom chatbot. As technology keeps advancing, it’ll get easier and easier to create and deploy chatbots.

Ongoing Maintenance Schedules

Chatbots require updating and maintenance. Someone should look into the chatbot’s failed customer support tickets to make adjustments where necessary to avoid failing to resolve a ticket about the same topic again. As user questions and issues grow, take some time to add these new topics and their associated solutions into the chatbot’s knowledge bank. The time and effort will be worth it: this work can keep your brand image strong.

Developing Your Chatbot

Creating and deploying a chatbot is getting easier, and more companies are taking advantage of this technology by combining it with AI and machine learning. Don’t get left behind — a well-maintained chatbot with a high success rate in answering questions can strengthen your brand image and leave a great impression on your customers.

Have you interacted with an excellent chatbot? What company’s chatbot was it, and what did you take away from the experience? Let us know in the comments below!

The goal of robotics is to develop and construct meaningful machines that will support and help human processes. The multidisciplinary field fuses technologies such as artificial intelligence and machine learning together to develop innovative solutions.

Dogtown Media is Los Angeles’ leading robotics company, working with enterprises and organizations to help their businesses. Our team prides itself on the satisfaction, approval, and happiness of our clients. We want to create cutting-edge solutions to solve simple frustrations and tackle business hurdles.

Just recently, Dogtown Media was hailed as a top agency on Clutch for its excellence in AI for robotics. If you’re not familiar, Clutch is a B2B review platform based in Washington, DC. The site is well respected in the space for its commitment to providing data-driven content and verifying client reviews.

This recognition feels surreal and we are lost for words. Our team wants to send its sincerest thanks to Clutch for this award. We believe that this award is a great sign for our 2021 run, and we are looking forward to a prosperous year. 

 We know that this recognition was made possible thanks to our clients’ amazing feedback. We owe this success to our clients especially those who left us their review on Clutch. 

Here are some of the quotes that stood out most to us:

“They’re a small shop that’s motivated and offers a comprehensive list of services and capabilities. They’re accountable and willing to work by our side to make the best product possible. The entire team is professional and eager to solve our problems.” — Founder, Mobile Sales Training Company

“Dogtown Media developed a solution for a project considered impossible to do in the tech world. They’ve taken every goal we’ve had and delivered above and beyond our expectations, beating our requirement of achieving a 50% accuracy rating on visual search capabilities with a software that is over 90% accurate.” — CTO, Innovengine

Let’s build something amazing together! Connect with us and get a free tech consultation.

We’ve barely just begun 2021, but it’s already shaping up to be an amazing year for Dogtown Media. We were recently featured as a top machine learning developer by Techreviewer.co! Thanks so much to our clients, team, and community for your continued support — you’re the ones who make this possible.

Techreviewer is a trusted B2B information platform that regularly conducts market research across numerous sectors, such as development, design, and marketing. Its meticulous methodology quickly helps companies identify high-quality services for a variety of complex technical tasks. Whether you’re searching for experts in AI app development, the Internet of Things, or business analysis, Techreviewer’s analysts can expedite the process of finding the best technology partner for your business needs.

For Techreviewer’s list of 2021’s top machine learning companies, the review hub evaluated each contender by examining its demonstrated expertise, experience, quality of services, and reliability to deliver products that went above and beyond clients’ requirements. That last component was especially crucial in elucidating the top players in this sector; the product must leverage key aspects of machine learning to help transform a client’s digital presence.

Over 500 companies were considered for this prestigious award. We’re extremely proud to be able to say that we made the cut after quite a few time-intensive assessments!

Besides being recognized as one of the best machine learning app developers of 2021, we’re also grateful to have been featured as one of 2021’s best iPhone app developers as well as a top mobile app developer in Los Angeles by Digital.com!

With this award, we couldn’t be more excited to see what else is in store for our company in the new year! Thanks to Techreviewer for recognizing our hard work. And thanks again to our clients, team, and community — we couldn’t have done this without you!

About TechReviewer.co

Techreviewer a trusted analytical hub that carries out studies and compiles the lists of top development, design and marketing companies. The platform helps to find the best companies that provide high-quality IT services for technical support, development, system integration, AI, Big Data, and business analysis. As a result of objective market analysis, the Techreviewer platform determines the most successful and reliable IT companies and makes top ratings for each of the service categories. Techreviewer’s ranking lists help organizations select the right technology partner for their business needs.

AppCon 2020 has been underway for the past few weeks. While this year’s conference is completely digital, that hasn’t stopped the many mobile app developers and tech innovators in attendance from opening up meaningful dialogues with political leaders about the impact of emerging technologies on the future of the United States.

So much has happened in such a short amount of time that we thought a blog post covering some of the best highlights of this year’s event so far was warranted. With that said, let’s dive right in!

Week 1: The Future of the U.S. Depends on Internet Access

Besides being an essential utility that sustains the growth of the $1.7 trillion app economy as well as several small businesses in a variety of sectors, widespread internet access also supports hundreds of millions of Americans. With it, they’re able to access healthcare services, educational opportunities, and much more.

Unfortunately, more than 20 million U.S. citizens still lack access to an adequate broadband connection. And unless this is addressed soon, this digital divide will only grow larger with the introduction of new technologies. AppCon ’20 attendees got to speak with Federal Communications Commission (FCC) Commissioner Michael O’Rielly about this very topic.

Commissioner O’Rielly expressed intent in ensuring that broadband exists everywhere in the U.S. and placed special emphasis on getting underserved Americans connected. He stressed the importance of high bandwidth and low latency, and he also noted that how we achieve broadband access for all is less important than actually accomplishing it.

AppCon attendees also spoke with FCC Commissioner Brendan Carr, who was focused on making more spectrum available for use. Whether it’s not having a device to connect with healthcare professionals, being unable to rely on high-speed internet, or not having access to a private space for care, Carr was well-aware of the pain points of Americans across the country. He reassured AppCon attendees that more funding was coming for connected care.

FCC Legal Advisor Umair Javed and Travis Litman, Chief of Staff and Senior Legal Advisor for the FCC’s Wireline Competition Bureau, focused their meetings with AppCon attendees on the digital divide’s effect on education. COVID-19 has pulled back the curtain on just how necessary internet access and devices such as smartphones and laptops are for remote learning. During the meeting, Javed indicated that low power applications carried some potential for closing this gap.

Last but not least, AppCon attendees also got to meet with Evan Swarztrauber, a Policy Advisor of FCC Chairman Ajit Pai. Swarztrauber noted that an increase in rural healthcare budget was sorely needed, and so was an improvement in broadband access for these regions. With COVID-19 forcing aspects of society such as education and healthcare to go remote, folks out in the country will fall behind unless they have fast internet.

Week 2: Telehealth Must Remain Accessible, Even After COVID-19

Telehealth and connected tools have proven invaluable in the U.S. healthcare system’s response to COVID-19. It’s obvious that these technological paradigms are a necessity for all Americans, but unfortunately, some politicians don’t see it that way. Much of AppCon ’20’s Week 2 revolved around attendees meeting with congressional leaders to ensure that digital health remains a cornerstone in our country’s medical system.

Currently, the U.S. has an annual healthcare spend of $3 trillion, with $1 trillion going through Medicare and Medicaid. The country is short by about 30,000 physicians, and this shortage is estimated to grow to 90,000 by 2030. By that same year, 70 million Americans will be over 65, and 80% of them will be dealing with at least one chronic condition.

These statistics make it painfully obvious that telehealth capabilities should become a permanent fixture in the U.S. medical system. But before COVID-19, this technology was wrestling with rules written in the 1990s. Clearly, things have come a long way since then. Unfortunately, the temporary waiver that allows Medicare to cover telehealth is slated to end by November unless fast, meaningful action is taken.

AppCon attendees had the chance to speak with staff from the U.S. Commerce Department. Though 40% of Medicare patients don’t have adequate broadband access at home right now, the department members emphasized that telehealth transformation is definitely beneficial to Medicare. But we must keep the growth and convenience of this technology going without exacerbating health inequities. They also discussed that innovators and legislators must keep what works and let go of anything fraud-laden or inefficient.

To achieve this, the U.S. Commerce Department staff stressed that we need an honest, balanced approach to data management. We should prioritize the most useful data that provides the most positive impact for the fewest taxpayer dollars. We should also focus on delivering services and outcomes, not billing for simply noticing a malady and not treating it.

AppCon attendees also got to speak with Dr. Donald Rucker, the National Coordinator for Health Information Technology at the Office of the National Coordinator for Health IT (ONC). Rucker wants one of the main goals for Congress to be freeing up patients to have agency over their healthcare. And to do this, we must examine the mechanism behind data gathering and usage.

Digital health tools and wearables such as the Apple Watch should strive to put patients back in charge of their information. Rucker believes that patients and the American public have already paid for this data, so they should be in charge of it, not third parties.

Rucker went on to discuss a variety of topics with AppCon attendees, including interoperability, how difficult EMR integration is, HIPAA compliance, and the need to address the incomplete pictures of patient data that physicians have to deal with. He even mentioned that healthcare providers sometimes struggle to access their own data.

Stay Tuned for Our Coverage of Weeks 3 & 4!

While digital this year, AppCon 2020 has done an amazing job of bringing together mobile innovators from Los Angeles, New York City, and everywhere in between! But the party’s not over yet. Stay tuned for our coverage of weeks 3 and 4, where AppCon attendees will get the chance to discuss privacy, encryption, antitrust, and standard-essential patents (SEPs).

As the years pass, IoT will become ubiquitous throughout all of our lives. We’re going to be interacting with IoT systems at home, at work, in retail, and even at the grocery store. Ultimately, many of our devices will become part of an IoT system, whether it’s a smart home set-up or smart office space. So it’s imperative that we all develop an understanding of how IoT functions.

IoT’s Rise in History

Many of us remember the late 90s and early 2000s when we had flip phones, paid per text message and calling minute, and lost reception quite often. Since then, our primary means of communication have markedly evolved and improved with stability, low latency, and the ability to connect our devices with other ones. If you’ve got your phone connected to an Alexa or Google speaker, you can even send a text message through that avenue now.

It has been nothing short of a meteoric rise for devices connecting with each other over Bluetooth, via QR code, or through a single-sign-on login system.

Although, even with this set-up, we’re limiting ourselves greatly. But with IoT, we can add more dimensions, types of devices, and connection methods to our systems. Imagine if you could connect to your car, fridge, local farmer, local city infrastructure, and more. Now imagine if this connection could enable these complex devices to talk with each other.

The fridge might alert your local farmer that you’ll likely pick up some tomatoes at this weekend’s farmer’s market. Your car could navigate red lights around town with efficiency and reroute you during rush hour as needed. These are rudimentary examples, but they point to a greater picture of what IoT bestows upon us in our daily lives.

The Foundation of IoT Systems

IoT connects devices, things, and spaces that are usually “outside” of the Internet to our Internet-connected devices. These remote and cloud-based connections will only stabilize with the implementation of 5G globally, allowing us to generate data, find insights, and even send the analysis back to the main device that needs optimizing.

How is this all possible? A mix of programming, hardware, security protocols, cloud integration, networking, data science, and AI combine seamlessly to produce robust IoT systems. Let’s take a closer look at each component.

Programming

IoT devices are programmed to work and communicate with each other using code that IoT developers often write in C++ or C. For bigger IoT systems or ones that need to scale up eventually, many developers are turning to Python and JavaScript. Even if a developer knows how to code, they must also have a deep knowledge of hardware, like circuit boards, microcontrollers, circuit design, and more.

Hardware

Hardware is one of the most important aspects because it is one of the only physical parts of an IoT system. Interconnected devices, sensors, and controllers help IoT systems understand (and sometimes even control) the world around them. Often, devices are computing on the device itself instead of the cloud (through the help of microcontrollers, system-on-a-chip (SoC), field-programmable gate arrays (FPGAs), etc.), which brings more importance to choosing high-quality, secure, and sturdy devices.

Security Protocols

Security is the most overlooked aspect of any technology application or system. At our Los Angeles-based mobile app development studio, we place security as a high priority on all of our projects. In many IoT systems, security gets layered on top last, making it an afterthought for many developers. On the contrary, security must be developed and thought of at every step of the design and development of IoT systems. Millions of new devices connect to the Internet every day, and the number of viruses and malware is increasing rapidly. When you consider that many IoT systems also house sensitive information, like payment data, trade secrets, machine information, and more, multi-layered security is non-negotiable. And no, you cannot rely on the devices’ built-in security — these have been shown to be behind in industry standards.

Networking and The Cloud

Connecting to the Internet is of utmost importance for IoT devices. Without the connection, it wouldn’t be possible to include the device in an IoT system. Setting up a stable network from the get-go is important, but IoT systems developers need to constantly monitor the network load and bandwidth to ensure more optimization isn’t needed. Having a poor network can cost a company a lot of time and money. On a related note, cloud computing and cloud storage should be monitored closely and optimized accordingly constantly throughout an IoT system’s lifespan.

Data Science

Analyzing data for insights can help companies cut costs without infringing on employees. With the amount of data generated every day in IoT systems, the term “big data” suddenly doesn’t seem to encompass enough. But this data is multi-dimensional and valuable. A good data analyst or scientist can elucidate new insights, patterns, and optimizations out of tons of data. And a great analyst or scientist can help trim down data points that are useless to the company’s bottom line, thereby improving network bandwidth, cloud computing credits, and storage costs.

AI and Machine Learning

AI and ML can work together to automate data scientists’ manual work. They can also help watch for patterns constantly to alert analysts for deeper analysis. Over time, AI can produce predictive analytics and even make small decisions without human oversight.

IoT Is an Integral Part of Our Future

IoT will continue improving as it expands. As with any emerging technology, its complexities will only grow with so many moving parts within and outside of the system.

Yes, “The Internet of Things” sounds vague, complex, and all-encompassing. But it all breaks down to a handful of features working together seamlessly.

We hope you’ve gained a deeper understanding of how IoT works from this article! What aspects would you like to learn more about? Let us know in the comments below!

What will it take to make a trip to Mars viable? Relativity Space thinks it has the answer: Huge 3D printers, massive robotic arms, and, of course, some artificial intelligence (AI) development to tie it all together. If the company is correct, it could reinvent how we build rockets to reach the stars — and return to Earth.

Rethinking Rockets from the Ground Up

Tucked away next to Keanu Reeves’ stunt gym and across the street from one of Snoop Dogg’s recording studios is Relativity Space, a small startup with big ambitions. Founded by 29-year-old CEO Tim Ellis and 26-year-old CTO Jordan Noone, the company is on a mission to do for space rockets what Henry Ford did for the car: optimize their production via automation.

The fact that this rocket-building robotic factory is neighbors with these A-listers’ regular haunts emphasizes one of Relativity’s main selling points — that they can build rockets anywhere, even on Mars — as long as there’s ample space for 3D printers and robots. Behind the loading bay doors of the company’s Los Angeles development headquarters, you’ll find four enormous metal 3D printers producing rocket parts around the clock.

Stargate is the name of Relativity’s latest proprietary printer. 30-feet-tall and equipped with two colossal robotic arms, Stargate printers will be responsible for manufacturing roughly 95 percent (by mass) of the startup’s first rocket, Terran-1. Parts like electronic elements, cables, rubber gaskets, and moving parts account for the remaining 5 percent.

Making a rocket 3D-printable was no small feat; Relativity’s team had to rethink and re-engineer their typical design to make it work. Terran-1 will end up having 100 times fewer parts than a normal rocket. And while a conventional liquid-fueled rocket usually consists of thousands of components, Terran-1’s Aeon engine will be assembled from only 100 parts.

This simplicity in design will pay off in more ways than one. According to Ellis, Relativity will theoretically be able to transform raw materials into a rocket ready for the launch pad in just 60 days. But this won’t be proven true until at least 2021, the earliest expected year for the Terran-1 to lift off.

3D-Printing a New Way to the Stars

When fully assembled, Terran-1 will be about 100 feet tall and capable of carrying 2,800-pound satellites to low Earth orbit. That puts it right in the medium range of payloads; it’s more than small launchers like Rocket Lab’s Electron, but far less than SpaceX’s massive Falcon 9 rocket.

It’s worth mentioning that Relativity Space is far from the only company leveraging 3D printing. Rocket Lab, SpaceX, Blue Origin, and dozens of others are also using the revolutionary technology to produce parts. But Ellis and Noone are doubling down more on 3D printing for good reason; they see it as an essential piece of the puzzle to establishing transportation infrastructure to and from Mars.

Prior to Relativity Space, both Ellis and Noone worked on University of Southern California’s renowned rocketry team. After college, Ellis went to work for Blue Origin while Noone became employed at SpaceX. That’s when Ellis started to envision a different type of rocket factory — one run by robots as much as possible.

Fast forward to now, and the duo is many steps closer to making that vision a reality. They’ve certainly come a long way. the first iteration of Relativity’s Stargate printer is approximately 15 feet tall and has three robotic arms which it uses to monitor printing progress, weld metal, and correct defects. While the newest Stargate model only has two arms, it can print large components like fuel tanks or rocket bodies in a single go. Ellis says the next version of Stargate will be twice as big (around 60-feet-tall) to print even larger parts.

The Brains Behind the Robots

While the Stargate printers are used to take care of larger rocket elements, Relativity relies on commercially available metal 3D printers to produce components requiring more precision, like the engine. To get the fine-tuned nuances they need, Ellis and Noone turn to AI.

Before a print like this, Relativity’s team runs a simulation to see what the ideal print would look like. Then they run the real thing while sensors capture environmental data. By comparing these two outcomes, the team is able to train the machine learning algorithms behind the printer to recognize and correct mistakes until it can produce a flawless iteration of the component.

Ellis believes this process will be integral to perfecting automated manufacturing on other worlds. “To print stuff on Mars you need a system that can adapt to very uncertain conditions,” he explains. “So we’re building an algorithm framework that we think will actually be transferable to printing on other planets.”

Per Aspera Ad Astra

Like any ambitious startup, Relativity Space has its doubters. Max Haot is the CEO of Launcher Space, another rocket startup that utilizes 3D printing. He explains that, while everyone in the aerospace industry is eager to tap into the benefits of 3D printing, it may not be the best production method for every component:

“The question is whether 3D printing aluminum tanks is worth it when compared to the traditional tank manufacturing methods. We don’t think so, but let’s see where they take it.”

Still, that hasn’t stopped Relativity from securing hundreds of millions dollars’ worth of deals with numerous satellite operators. And many of the startup’s investors and advisors see much more potential in the company than just launch services.

Shagun Sachdeva, Senior Analyst at space consultancy Northern Sky Research, says “Even if we don’t get to the point of full rocket manufacturing on Mars, Relativity may be able to manufacture other components in orbit. That’s a pretty big development for the industry as a whole.”

When their first rocket is completely assembled, Relativity’s team will ship it to Kennedy Space Center’s Launch Complex-16 for liftoff. What do you think of Relativity’s out-of-this-world approach to rocket building? Do you think this is the future of space exploration? Let us know your thoughts in the comments!