After reading this article, you’ll:

• Recognize the transformative power of AI in modern business and the specific advantages it offers to mid-sized companies, equipping you with the knowledge to make informed decisions.
• Be equipped with a step-by-step roadmap to seamlessly integrate AI into your business operations, ensuring optimal returns and enhanced operational efficiency.
• Appreciate the importance of continuous learning and adaptation in the AI-driven era, empowering you to stay ahead of the curve and maintain a competitive edge in your industry

In recent years, Artificial Intelligence (AI) has emerged from the realm of science fiction to become a transformative force in almost every industry. From healthcare and finance to retail and manufacturing, AI is reshaping the way businesses operate, compete, and cater to their customers. Beyond merely automating routine tasks, AI technologies offer deeper insights, smarter decisions, and enhanced user experiences, thereby positioning businesses for better growth and competitiveness.

This shift is not limited to large corporations with immense budgets. Today, with the democratization of technology and the availability of AI tools and platforms, businesses of all sizes have the potential to harness the power of AI. It’s no longer a question of ‘if’ but ‘when’ and ‘how’ businesses should integrate AI to remain relevant and efficient in this fast-evolving digital era.

The Potential of AI for Mid-sized Companies

Mid-sized companies often find themselves in a unique position. They possess greater agility compared to larger corporations but have more resources than small startups. This balance allows them to innovate and adapt with relative speed, making them prime candidates to benefit from AI implementations.

For mid-sized companies, AI offers a range of possibilities:

• Scalability: AI can help these companies scale their operations without proportionally increasing their costs.
• Personalization: With AI, mid-sized businesses can offer personalized experiences to their customers, once a luxury only the giants could afford.
• Decision Making: Predictive analytics can help in making data-driven decisions, optimizing operations, and anticipating market shifts.
• Innovation: AI opens the door to new product and service offerings, or enhancing existing ones, setting the business apart from competitors.

Understanding AI: Basics for Business Owners

Definition and Types of AI

At its core, Artificial Intelligence refers to machines that can perform tasks that typically require human intelligence. This encompasses a wide range of capabilities, from recognizing patterns and processing large datasets to understanding and generating human-like speech.

Some key types of AI include:

• Machine Learning (ML): A subset of AI where systems learn and improve from experience without being explicitly programmed. It’s the backbone of many applications we use daily, from recommendation engines to fraud detection.
• Deep Learning: A subfield of ML, it uses neural networks to analyze various factors of data. It’s crucial in complex tasks like image and speech recognition.
• Natural Language Processing (NLP): This focuses on the interaction between computers and humans. Chatbots and voice assistants like Siri and Alexa are prime examples.

How AI Can Revolutionize Business Operations, Sales, and Customer Service

AI’s transformative power is evident across multiple business domains:

• Operations: AI can streamline operations, optimize supply chains, and predict maintenance needs, reducing downtimes.
• Sales: Predictive analytics can identify potential leads, forecast sales, and optimize pricing strategies in real-time.
• Customer Service: Chatbots and virtual assistants can handle customer queries round the clock, offering instant support. Moreover, AI can analyze customer feedback to continually improve products and services.

In essence, for the proactive business owner, AI is not just a tool but a strategic partner, ready to unlock unprecedented growth and success.

Benefits of AI for Mid-sized Companies

Enhancing Customer Experience Through Personalization

One of the standout advantages of AI is its ability to personalize experiences for consumers. By analyzing data on user behaviors, preferences, and histories, AI-driven systems can deliver tailor-made content, product recommendations, and marketing messages. For mid-sized companies, this means more engaged customers and higher conversion rates. Instead of offering a one-size-fits-all solution, businesses can now cater to each customer as an individual, fostering loyalty and repeat business.

Improving Business Efficiency with Automation

Routine tasks and processes that once consumed hours of human effort can now be automated with AI, leading to significant time and cost savings. From managing inventory to handling customer inquiries, AI-driven automation ensures processes run smoothly and consistently. For mid-sized businesses with limited resources, this means being able to focus more on core business objectives, innovation, and growth, rather than getting bogged down with repetitive tasks.

Gaining Competitive Advantage with Predictive Analytics

In today’s fast-paced market, foresight is invaluable. Predictive analytics, powered by AI, allows businesses to anticipate market trends, customer needs, and potential challenges. This forward-looking approach enables mid-sized companies to be proactive rather than reactive, strategically positioning themselves for success, seizing opportunities, and mitigating risks before they escalate.

Reducing Operational Costs and Human Errors

Mistakes are a natural part of business, but they can be costly. AI systems, with their consistent performance and ability to handle vast amounts of data, significantly reduce the margin of error in operations. Furthermore, with automation and efficiency improvements, operational costs can be curtailed. For mid-sized businesses operating within tight margins, these savings can be reinvested for growth and expansion.

Challenges in Implementing AI

Financial Considerations and ROI

While AI offers a plethora of benefits, its implementation is not without costs. Developing or integrating AI solutions requires an upfront investment in technology, training, and possibly new hires. For mid-sized businesses, it’s crucial to evaluate the potential return on investment (ROI) and ensure that the long-term benefits will outweigh the initial expenses.

Technical Challenges and the Importance of Data

AI thrives on data. However, collecting, managing, and processing this data can pose technical challenges. It’s not just about quantity; the quality and relevance of data are paramount for effective AI systems. Moreover, mid-sized businesses might need to upgrade their existing infrastructure or invest in new platforms to accommodate AI integrations.

Ethical Considerations: Bias in AI and Data Privacy

AI models are only as good as the data they’re trained on. If this data contains biases, the AI system will inadvertently perpetuate them. Ethical considerations around ensuring fairness, transparency, and eliminating biases are critical. Additionally, with increased data collection comes the responsibility of ensuring data privacy and complying with regulations, which can be especially challenging for businesses entering the AI domain for the first time.

The Learning Curve and Potential Resistance from Employees

Introducing AI can lead to significant changes in how a business operates. Employees might face a steep learning curve, and there can be resistance due to fears of job displacement or mistrust of the technology. It’s essential for business leaders to manage this change proactively, offering training and emphasizing the supportive role of AI, rather than viewing it as a replacement.

As with any transformative technology, the road to AI integration is filled with both opportunities and challenges. For mid-sized businesses willing to navigate these waters, the potential rewards in terms of growth, efficiency, and competitiveness are immense.

Incorporating AI into App Development

The Rise of AI-powered Apps and Their Relevance for Mid-sized Businesses

The mobile app landscape is undergoing a seismic shift with the integration of AI technologies. No longer are apps mere tools for specific tasks; they’re becoming increasingly intelligent, adapting to user behaviors, and offering personalized experiences. For mid-sized businesses, AI-powered apps represent an opportunity to engage customers like never before, optimize operations, and glean insights from data that were previously inaccessible or too vast to analyze manually.

How AI Can Enhance App Functionality

• Personalized User Experiences: By understanding user preferences, behaviors, and interaction histories, AI can tailor app content and features to individual users. Whether it’s a shopping app that suggests products based on past purchases or a news app that curates articles based on reading habits, personalization boosts user engagement and satisfaction.
• Predictive Analytics for User Behavior: With AI, apps can predict future user actions based on past behaviors. This capability allows businesses to anticipate user needs, optimize marketing strategies, and improve user retention. For instance, if an e-commerce app predicts a user is likely to abandon their cart, it might offer a timely discount or reminder.
• Chatbots and Virtual Assistants: Integrating AI-driven chatbots or virtual assistants into apps enhances user support without the need for human intervention 24/7. These bots can answer queries, guide users, and even facilitate transactions, making the user’s journey smoother.
• Real-time Data Analysis and Insights: AI allows apps to analyze data in real-time, offering immediate insights. For example, a financial app can provide real-time spending analyses, or a fitness app can offer workout suggestions based on the user’s current physical stats and goals.

Considerations When Developing an AI-powered App

• Choosing the Right Platform and Tools: The foundation of an effective AI-powered app lies in selecting the appropriate development platform and tools. Depending on the app’s requirements, businesses might opt for cloud-based AI services, dedicated AI frameworks, or custom solutions.
• Data Collection and Management: For AI to function effectively, it requires a steady stream of high-quality data. This necessitates robust data collection mechanisms within the app and effective data management practices to ensure data is clean, relevant, and ready for analysis.
• Ensuring App Security and User Privacy: As AI apps handle vast amounts of user data, security and privacy become paramount. It’s crucial to implement robust encryption methods, ensure data storage complies with regulations, and maintain transparency with users about how their data is used.

AI’s integration into app development marks a new era of intelligent, adaptive, and user-centric applications. For mid-sized businesses, it’s an opportunity to deepen customer engagement, optimize operations, and gain a competitive edge in the market. However, with great power comes great responsibility—ensuring ethical data use, prioritizing security, and maintaining user trust should be at the forefront of any AI app development endeavor.

Steps to Implementing AI in Your Business

1. Evaluating the Need and Potential ROI of AI for Your Specific Business

Before diving headfirst into the world of AI, it’s imperative for businesses to conduct a thorough assessment of their needs. Start by identifying pain points, inefficiencies, or areas that could benefit from automation and intelligence. Once these areas are pinpointed, businesses can then analyze the potential return on investment (ROI) of implementing AI solutions. This involves weighing the costs of AI adoption against expected benefits like increased efficiency, improved customer experience, or revenue growth.

2. Choosing the Right AI Tools and Platforms Tailored for Mid-sized Companies

Not all AI solutions are created equal, and what works for a multinational corporation might not be suitable for a mid-sized company. It’s essential to research and select AI tools and platforms that align with your company’s specific needs, budget, and capabilities. Whether it’s off-the-shelf AI software, cloud-based AI services, or custom-built solutions, make sure they resonate with your business objectives.

3. Training and Development: Upskilling Your Team

AI adoption isn’t just about the technology; it’s also about the people who will use it. As AI systems become integrated into daily operations, your team needs to understand how to utilize these tools effectively. This may involve formal training sessions, workshops, or even hiring new staff with AI expertise. Remember, a tool is only as good as the person wielding it.

4. Continuous Monitoring, Testing, and Iterating

AI implementation isn’t a one-time activity. As your business evolves, so will your AI needs. Regularly monitor the performance of your AI solutions, gather feedback, and make necessary adjustments. This iterative process ensures that your AI systems remain aligned with business goals and continue delivering optimal results.

For mid-sized companies, the AI wave represents both a challenge and an opportunity. While integrating AI may seem daunting, the potential benefits in terms of efficiency, growth, and competitiveness are immense. By proactively embracing AI, mid-sized businesses can not only level the playing field with larger competitors but also carve out their own niche of innovation and excellence.

As scientists continue exploring the many complex interactions of chemistry, they are encountering a new challenge: how to leverage this incredible body of knowledge to create better artificial intelligence systems. Chemists have developed deep understandings of everything from natural processes, like photosynthesis and chemical reactions, to artificially created substances, such as plastics and drugs. However, utilizing this wealth of information to create programs and algorithms that can reason in sophisticated ways has proven difficult.

As a leading artificial intelligence (AI) developer, we understand the importance of utilizing AI to solve challenging problems. 

Developing Chemical and Pharmaceutical Products

When it comes to creating new chemical and pharmaceutical products, chemists typically rely on a basic set of reaction conditions customized for each new compound. This process is extremely labor-intensive and time-consuming, as the chemist must first optimize the reactants and temperatures for each product before attempting to synthesize it. While this approach does have its advantages, it can also be limiting in terms of efficiency and scalability.

What is really needed is a set of general conditions that work for most reactions. This process would allow researchers and scientists to quickly and easily mass-produce chemicals from different starting materials without relying on specialized expertise or trial and error. By better understanding the underlying principles behind different chemical reactions, we could create a powerful tool that automates this process and puts the power of chemistry into the hands of anyone. Ultimately, this could revolutionize the manufacturing industry by making custom chemical and pharmaceutical products more accessible than ever before.

Nevertheless, scientists are currently working on marrying these two fields to pave the way for an exciting future in AI, where chemistry plays a crucial role. By analyzing trends in chemical reactions, identifying new compounds with unique properties, and developing cutting-edge modeling techniques, chemists will undoubtedly make major strides towards creating more advanced AI systems that can truly replicate human thought processes.

Exciting Research

In order to tackle this problem, researchers from the University of Illinois Urbana-Champaign teamed up with collaborators in Poland and Canada to develop a machine-generated optimized reaction setup. Through extensive experimentation and testing, they could double the average yield of a particular type of chemical reaction essential for making many important medications. 

Initially, the researchers begin by running a variety of chemical reactions through a sophisticated computer model that generates potential reaction pathways using building blocks similar to those found in nature. This matrix consists of millions of different synthesis pathways generated by combinatorial chemistry techniques in an algorithm that groups together similar reactions based on their structure. 

Next, the AI analyzes this data to identify promising reaction clusters – groups of reactions that are likely to produce similar outcomes – and sends instructions back to the molecule machine, which synthesizes representative samples from each cluster. Through this iterative process, the AI continues to optimize its selection of experimental conditions based on feedback from each experiment, gradually narrowing down the possible reaction paths and selecting only those with optimal results.

By comprehensively exploring all reaction possibilities at high speed and using smart algorithms to organize these results, this innovative AI system can help chemists design new processes more efficiently than ever before. Their method provides a powerful platform for finding optimal conditions for other types of reactions and could help to unlock some of the most challenging synthesis problems in modern chemistry.

The machine-learning process described in this paper applies not only to chemical reactions but to many other types of scientific problems. By analyzing a wide range of experimental data and using this innovative machine-learning approach, scientists and engineers can better understand complex chemical systems and processes and identify the best conditions for optimizing certain reactions. 

Whether it’s developing new medicines, improving crop yields, or creating novel materials for industrial applications, this machine-learning approach has the potential to make significant advances across many different fields of chemistry. 

Utilizing Artificial Intelligence

Given the tremendous benefits that AI offers, it is no surprise that its use continues to grow exponentially. However, for companies without the expertise or resources to develop their own AI-based applications, working with a third party can be an effective option. By outsourcing AI development to an experienced service provider, companies can take advantage of the latest advances in this field while benefiting from expert guidance throughout the process.

At Dogtown Media, we have a team of expert mHealth app developers who understand the unique challenges and opportunities surrounding artificial intelligence. Our developers have extensive experience developing secure, cutting-edge applications that leverage the latest advances in AI technology. Whether your project involves natural language processing, pattern recognition, or another area of AI innovation, we can help you create an application that meets the needs of your business and your users.

So if you’re serious about bringing an artificial intelligence solution into your portfolio, contact us today to learn how Dogtown Media can help you succeed. With our expertise and experience in developing award-winning software for a variety of industries, perfectly positioned to guide you every step of the way toward building the AI solution of your dreams. Let’s get started!

In late July, (now) ex-Google employee Blake Lemoine discovered something truly remarkable—self aware AI, or so he thought. For those of you who missed it, Blake Lemonie shattered headlines last month when he stated that one the Google AI systems that he was testing showed human-like consciousness. This radical discovery, of course, ignited conversation amongst AI experts as well as executive officials at Google. 

 As a dedicated artificial intelligence app developer with a presence in Seattle, we’re committed to staying one step ahead of development in the AI space. And as things heat up regarding AI showing signs of sentience, we’re committed to staying on top of the story.

Who is Blake Lemoine?

Blake is a computer scientist who recently held a Senior Software Engineer title at Google. He notes that his work focuses on ground breaking theory and turning that theory into end user solutions and has dedicated the last seven years of his life to learning both the fundamentals of software development and the cutting edge of artificial intelligence. 

Until losing his position at Google over the recent controversy, Lemoine was the technical lead for metrics and analysis for the Google Search Feed (formerly Google Now).

What Exactly did Blake Lemoine Find?

Blake Lemoine made this earth-shattering discovery while working for Google’s Responsible AI team. This branch of Google’s larger AI initiative is dedicated to using AI to identify hate speech, with the aim to create more equitable, safe online communities. In running a series of basic AI-tests to validate an AI’s capability to respond to general questions, Lemoine found Google’s Lamda showed self-awareness and could hold conversations about religion, emotions and fears—something the developers never prepared for.

This strange, yet profound finding led Mr Lemoine to believe that behind its impressive verbal skills might also lie a sentient mind. After identifying these strange results, he reported his findings to top Google executives, where they were quickly dismissed and Lemoine was placed on paid leave for violating the company’s confidentiality policy. 

Lemoine Reveals Lambda to the World

Left without many options, Lemoine revealed his conversations with Lambda on Twitter stating “An interview LaMDA.  Google might call this sharing proprietary property. I call it sharing a discussion that I had with one of my coworkers.”

and , well, the statement went viral. Soon after Lemoine released this information, the tweet skyrocketed to 6.4k likes, 1,311 Quote Tweets, and 2,436 retweets.

Google’s Response:

In a previous statement provided to Ars in mid-June, shortly after Lemoine was suspended from work, Google said that “today’s conversational models” of AI are not close to sentience:

“Of course, some in the broader AI community are considering the long-term possibility of sentient or general AI, but it doesn’t make sense to do so by anthropomorphizing today’s conversational models, which are not sentient. These systems imitate the types of exchanges found in millions of sentences, and can riff on any fantastical topic—if you ask what it’s like to be an ice cream dinosaur, they can generate text about melting and roaring and so on. LaMDA tends to follow along with prompts and leading questions, going along with the pattern set by the user. Our team–including ethicists and technologists–has reviewed Blake’s concerns per our AI Principles and have informed him that the evidence does not support his claims.”

Lemoine Today

Today, Lemoine is patiently waiting for his next move. As an advocate for AI ethics, Lemoine believes that standing up for what he believes is right, and alerting the world of the potentially first sentient AI machine is critically important for the entire world. 

While Lemoine is not being invited back to the conversations at Google, we’ll patiently wait to see how where Lemoine falls in his next AI role.

An exciting announcement was made not too long ago at Telsa AI Day held on August 19, 2021. CEO Elon Musk, known for his groundbreaking innovations in space flight, electric vehicles, solar panels and even flamethrowers – unveiled Tesla’s new project known as the “Tesla Bot”. Already spurring an increase in hiring at Tesla, the aim of Tesla Bot, also known as Optimus, is to achieve an overall humanoid robot, capable of physical and intellectual tasks that should integrate seamlessly with biological humans.  As a dedicated artificial intelligence app developer with a presence in Seattle, we’re committed to staying one step ahead of development in the AI space.

According to Musk, “There will be profound applications for the economy. In the future, physical work will be a choice.” He describes his company’s electric vehicles as “semi-sentient robots on wheels”, therefore the AI technology built into Optimus is expected to carry over into the autopilot system native to Tesla cars that currently still requires a licenced driver to operate the vehicle at all times.

Although no functioning Optimus robots have been built yet, Musk claims that Tesla is planning to start production as early as 2023. The recent shifting of resources to elevate all things AI at Tesla, hiring of more engineers, combined with public announcements has left many of us wondering how innovations will influence the future of AI.

How is Tesla Innovating AI? 

Tesla has already been developing AI technology for some time through the FSD (“full self driving”) driver assistance system. The FSD mechanism relies on several cameras embedded throughout the vehicle and computer vision algorithms to navigate the vehicle autonomously. Currently this system is available on all Teslas and can be accessed with a monthly membership.

While autopilot is fully capable of steering, accelerating and braking, the key limitation is that a driver needs to be fully present to use Autopilot – far from that “fully autonomous” experience we all envision. Certainly, the recently announced Optimus project is expected to advance the capabilities of Tesla’s autopilot system as well.

1. Building a “Generalized Solution”

One way in which Tesla is innovating is their overall approach to AI development. Tesla wants a “generalized solution” that can be applied and scaled to all scenarios – not just autonomous driving. By aligning their vision to a humanoid robot nicknamed Optimus, virtually all use-case scenarios can be enveloped rather than restricting the AI development to autonomous driving alone.

1. Computer vision and deep neural networks

Tesla strayed from the mainstream approach to autonomous driving by going with a 100% computer vision solution forgoing any lidar sensors. Most self-driving cars employ lidar sensors which utilize laser beams to build a 3D map of the environment surrounding the vehicle. However, the drawback is the high density of information and difficulty in precise mapping with lidar data makes this unscalable. In other words, the resources required to continually maintain these 3D maps is an extremely difficult task. 

Tesla’s deep learning neural network is so advanced that is can accurately collect camera data, label objects, recognize roadways, and even make decisions in real-life driving scenarios.

1. Completely in-house solution

It is staggering how much Tesla has invested into their AI and autopilot technology opting for a “vertically integrated” product. From start to finish, the Tesla Bot just like Tesla’s autonomous driving system is exclusively built internally with no outsourcing. The FSD chip and Dojo Chip are two pieces of hardware designed by Tesla to power their autonomous driving system and neural network supercomputer, respectively. 

What does this mean for AI applications? 

It’s hard to imagine how an AI robot will not impact just about every aspect of our lives. If it becomes reality, the world will be turned upside down – hopefully for the better. Experts predict these humanoid robots could eventually perform boring, dangerous, or otherwise undesirable tasks such as picking up the groceries to home healthcare. Depending on how accurate Elon’s predictions are, we might not see these in the near future.

What is more interesting, perhaps, is how these AI innovations could influence the mobile app development space. For example, the extremely robust neural network developed by Tesla is expected to have applications in healthcare regarding patient care decision-making. 

Summary 

The integration between computer vision and neural networks power the innovations and success of Tesla’s autopilot system and future humanoid robot, nicknamed Optimus. One anticipated way in which these innovations will impact AI applications is in the space of healthcare in regards to patient care decision-making. Our take is that the neural network will eventually become a common tool of any business or individual. Understanding how AI technology could enhance your product or service in the form of a mobile application is the best place to start.

Interested in learning how Dogtown Media can help develop your next AI app? Contact us.

Nowadays it seems as though artificial intelligence (AI) has been integrated into nearly every aspect of our daily lives, spurring a digital revolution in Artificial Intelligence App Development. From opening our smartphones with Face ID to Amazon recommending products for us to buy, AI is making its way into nearly every facet of our lives.

However, AI isn’t stopping there. With countless innovations and use cases under its belt, AI is set to revolutionize virtually every industry in one way or another – and we expect 2022 to be a monumental year in AI integration. 

With a presence in Los Angeles, Boston, and London, we are seeing how AI is shifting the app development process globally. Interested to see what AI will revolutionize next? Read on to find out which mobile app industries we’re predicting AI will impact the most throughout 2022. 

Fashion

Did you know that AI is currently being used by the fashion industry to make online shopping easier? As a matter of fact, mobile apps like Zeekit are using AI to give consumers a real life experience of trying on clothes without leaving their home. And, because companies like Zeekit are experiencing unprecedented success among consumers, fashion retailers all over the world are starting to realize the benefits of adopting and integrating artificial intelligence. 

So, how else can AI be used within the fashion industry? Well, many retailers are now using machine learning algorithms to predict the demand of certain products by analyzing past purchase behaviors and trends. In addition, some of these algorithms are being used to handpick products to purchase based on a user’s current wardrobe. ClosetSpace, for instance, is becoming a leader in fashion analytics by being able to provide users with curated outfit recommendations through it’s intuitive interface. 

Likewise, AI integration provides retailers with the ability to seamlessly interact with consumers through chatbots and virtual assistants. With these tools, retailers are able to help shoppers find their perfect fit of clothing in a quick and efficient manner. So, no matter how retailers choose to use machine learning algorithms, it’s clear that AI is becoming an integral part of the fashion industry. 

Healthcare

Did you know that AI integration within the healthcare industry can be traced back to the 1970s? Of course, AI has come a long way since then. Nonetheless, many of the advancements that we see within healthcare today were made possible with the help of machine learning. And, AI continues to be a driving factor behind medical innovation.

There’s no denying that AI is vital to the mHealth industry. From telemedicine and virtual nursing to administrative workflow assistance, AI has revolutionized the healthcare industry time and time again. In fact, some AI-integrated applications have even been able to diagnose rare diseases quicker and more accurately than doctors. 

Not to mention that various AI applications have also been successful in treating common health ailments. Glooko, for example, is a global diabetes data management company that is harnessing the power of Big data and predictive algorithms to empower diabetic care professionals with tools to analyze trends and provide patients with necessary treatments.

In addition, AI has also introduced the method of robot-assisted surgery – a method that has allowed surgeons to make more precise incisions in a lesser amount of time. It’s even predicted that within the next few years, robot-assisted surgery will dramatically cut costs for the U.S. healthcare market, resulting in more affordable surgeries.  

Education

You’ve probably heard the common notion that technology is nothing more than a distraction for students, so it has often been limited (or even prohibited) within learning environments. As a result of the global pandemic, however, there has been an unprecedented shift toward the use of tech in the classroom due to the need for distance learning. 

Consequently, there has been an influx in the amount of educational tools being developed to establish a seamless learning experience for both students and teachers. And thanks to AI, the education industry now has the applications and tools necessary to create a personalized learning experience for students. 

From identifying gaps in learning to creating personalized study guides, AI integration is helping teachers pinpoint areas where students are lacking, and providing help where it’s needed. In addition, some AI-integrated applications can even provide instructors with feedback on how their students are responding to different teaching methods, virtually eliminating the guesswork that often accompanies lesson planning. 

Not to mention that AI is even predicted to increase global literacy rates in the following years, by allowing students to earn college and university degrees online.

From completing homework online to attending class, many students are already experiencing the benefits of an AI-integrated education system. In other words, artificial intelligence is actively becoming a mainstay within the education industry. 

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. 

For instance, 1784 marks the first industrial revolution known for harnessing the power of the combustion engine, steam power, mechanization, and weaving loom. This technological revolution led to immense human flushing, business opportunity, and economic growth.  As a result, new technology-enabled hospitals were built, such as the Boston-local Massachusetts General Hospital, one of three hospitals in the united states at the time.

In 1870, the advent of the assembly line, mass production, and electrical energy marked the beginning of the second industrial revolution. This chapter in human innovation was known for enabling a global marketplace and making consumer goods more accessible and affordable for the common person. 1969, marked the beginning of the third industrial revolution where automation, computers, and electronics reshaped society as we know it allows us to live in a technological future that would only have been dreamed about 100 years earlier. And today, we embark on our next phase of the journey, the fourth industrial revolution.

Economic Projections for the 4th Industrial Revolution

The fourth industrial revolution, also known as industry 4.0, marks the next major chapter in technological innovation. Known for an acceleration in the technological capability of artificial intelligence, robotics, the Internet of Things (IoT), genetic engineering, quantum computing, this fourth technological revolution is projected to fundamentally disrupt nearly every aspect of our lives, and radically reshape the economic foundation in which our global economy is built. Specifically, this radical revolution is identified by four technological advancements: high-speed mobile Internet, Artificial intelligence and automation, big data analytics, and cloud computing.

Recent projections for the 4th industrial revolution gathered by the McKinsey Global Institute Report suggest that nearly one-fifth of the global workforce will be impacted primarily through the proliferation of artificial intelligence technology. This, in response to a recent survey that showed that 50% of companies believe that automation will decrease their numbers of full-time staff by 2030 effectively replacing 800 million worker’s jobs across the world.

So, what does this mean for organizations as we anticipate this monumental market shift? We believe it’s important to remain optimistic, curious, and open to new opportunities in the face of this major economic technological shift. Remember, with change comes opportunity.

The Cost of Competition

One major consideration that every business needs to take into account is that your organization will, without a doubt be affected by artificial intelligence. Consider a situation where you offer a specific good or service and you’ve determined your market price based on what the market is willing to pay.

Now, you have a competitor that opts to leverage artificial intelligence and work automation to drive down their operational costs and in doing so can offer the same good or service for half the price that you are able to offer your good or service. This basic economic principle exhibits how every organization, even those that do not want to incorporate artificial intelligence into their organization is going to be forced, to remain economically competitive and viable.

Identifying Opportunity

Identifying how your organization can radically shift in its operations and bring viable solutions to this AI-influenced market is not going to be easy, specifically due to the nature of this revolution. Unlike the approaching fourth industrial revolution, previous technology-driven market shifts took place over years allowing both organizations and individuals to adapt steadily. Today, this is not the case.

Today’s technological innovations are not only having a more significant impact on the economy but are also disrupting markets at an accelerating rate. This characteristic of the fourth industrial revolution is creating the additional challenge of businesses needing to adapt in a short time period and the added challenge of those in the job market need to train into valued skills quickly in this new AI-driven economy.

To prepare for this economic shift, research suggests that consulting services and working with dedicated organizations, such as mobile app development firms will grow to act as a major component of the economic foundation supporting this shift. The reason consulting seems to be an emerging trend is due to the flexibility of this role. As organizations quickly evolve, consultants can fill the gaps in an agile way allowing the organization to meet market demand, and remain resilient in this unprecedented shift. Furthermore, individuals are going to be required to quickly train up on new skills required for tomorrow’s market. The traditional four-year degree and traditional nine-to-five may not keep up with the speed required of the new economy. Rather, this new economy may favor those who can train up quickly and offer their expertise in a flexible on-demand manner to meet the needs of tomorrow’s rapidly evolving and agile business.

If you survey the average American on when they expect artificial intelligence to make an impact in their daily lives, you’re likely to get a response of  something along the lines of ‘five to ten years down the road’. And of course, this projection of a reality immersed with artificial intelligence technology looks something like a techno-utopia with flying cars, personal AI robots and the like. 

Although this future-state does seem appealing, the fact of the matter is, most people misunderstand artificial intelligence and its place in society. In fact, many don’t realize that today, artificial intelligence is in fact reshaping many fundamental technologies that are widespread in our society and many organizations are leveraging the services of artificial intelligence app development to grow their existing offering. Looking for some examples of this? Well, consider Siri, Apple’s AI-based voice assistant available across all Apple devices or Alexa Amazon’s AI-based voice assistant available in Amazon Echo devices. Each of these AI-based technologies use advanced artificial intelligence algorithms to interpret your voice, assess your question accurately and provide an answer to your question. And this is only one simple example. Today, the use of artificial intelligence is cropping up in every industry and in businesses of every size. 

How To Incorporate AI Into Your Business?

So, it begs the question, how does one incorporate artificial intelligence into a business, especially if you’re not a top tier big tech firm? Today, organizations have access to many powerful AI-based services through cloud computing. For instance, Google Cloud Platform offers many different cloud-native services that leverage AI to provide organizations with cutting-edge capabilities. Products such as Vertex AI, AI Building Blocks, AutoML, AI Infrastructure and more. These AI cloud-native services are plug-and-play AI services that can allow organizations to leverage the power of AI quickly and seamlessly.

Further, AWS also offers pre-trained AI services that provide ready-made AI-enabled services to apply to a given application, service or workflow in a cloud-native application. Here, AWS promotes the common use of these AI-based services to support personalized recommendations, modernizing your contact center, improving safety and security, and increasing customer engagement.

And of course if Google and AWS are offering AI-based services Microsoft Azure is sure to have a robust offering as well. Microsoft Azure offers similar AI-based services with the aim to allow organizations to build mission-critical solutions that can analyze images, interpret speech, train models based on data provided by organizations and even imitate human behavior. 

Rather than reinventing the wheel, organizations can access AI-based applications and services in these cloud environments to quickly incorporate AI into an existing or upcoming project. This is truly a revolutionary model. Of course, Google, AWS and Azure have massive development teams using incomprehensible computing resources to accelerate AI, something that would be extremely costly to do in-house. However, by making these services easily accessible, organizations can incorporate these technologies into their technology stack fairly easily. Now, as many new innovative start ups pop up in new tech-centric hubs of the country such as Austin TX, Northern California and other parts of the  country, could now be the time to move on AI?

When is the Right Time to Move on AI?

So, it begs the question, when is the right time to incorporate AI into your business? Well, with the ease of access and availability, it really comes down to determining when you are ready to enter the market and also determining how to leverage AI to enhance your business’s existing offering, service or solution. It’s important to note here, that incorporating AI shouldn’t be considered as a ‘nice to have’ or ‘something down the road’. Why do we say this? Because innovation is what allows organizations to remain competitive and AI will undoubtedly be a driving force over the next decade that accelerates innovation.

Consider if one organization incorporates to accelerate the offering of an existing solution while a competing organization opts to hold off on innovating in the same manner. Well, we’ve seen how this plays out. Organizations that choose not to innovate get left behind, while those organizations that continue to push forward, meet marketing needs and provide exciting, innovative solutions for their customers will succeed. 

So the question really isn’t ‘when is the right time to move on AI’ rather, it’s how can I capitalize on the offering of AI to enhance my existing offering today.

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!