This article is the third in a series that aims to demystify data science , machine learning, deep learning, and artificial intelligence (AI) – while exploring how they are interconnected.
In this final article, we focus on deep learning and AI and how today’s computers mimic the structure of the human brain to perform natural language processing, image recognition, and more. We’ll also discuss how deep learning and AI work together to power data and predictive analytics.
Deep learning is a subset of the methods used in machine learning. It’s an algorithmic approach – based on Artificial Neural Networks (ANN) – for implementing machine learning that helps us better understand AI concepts.
As its name suggests, ANN is based on human brain structure and our understanding of how the brain processes data through interconnected neurons. More simplified than the brain, ANN has discrete layers and data flows through a defined number of connections and directions before producing output. Like other deep learning models, ANN can be trained with or without a teacher (known as supervised, unsupervised, or semi-supervised learning).
When using deep learning to conduct image analysis, for example, the image is broken down into a matrix of consumable data that serves as the input data for the first layer. Each neuron in this layer passes the data to a second layer, and so on, until it reaches the final layer where the resulting output is produced – which may suggest that the image is that of a dog.
For each image that the ANN consumes, neurons on each layer assign or adjust the weighting it places on its input. This indicates how correct or incorrect the output is relative to the task. The total of the weights determines the result.
The science behind ANN has been around for more than seven decades but it requires powerful computational resources to produce results from large amounts of data. As such, interest in deep learning waned until the development of computing systems advanced enough to support it. Nvidia, for instance, played a key role in advancing deep learning algorithms since ANN models were trained with Nvidia graphic processing units (GPUs).
ANN alone does not enable deep learning, instead deep learning consists of different ANN architectures known as Deep Neural Networks (DNN). These include Recurrent Neural Networks, Deep Feed Forward, Deep Botlzman Machine, and others. Each has a unique set of strengths and use cases including speech recognition, natural language processing, image analysis, and social network filtering – with results surpassing human expertise in some instances.
As mentioned above, deep learning is a subset of machine learning. However, it brings new capabilities that advance machine learning to a new level.
Unlike traditional machine learning, deep learning doesn’t require you to research, develop, and use new features to improve the performance of machine learning algorithms – the neural network does the work for you by learning how to select the most critical features.
Furthermore, deep learning can deliver near-human performance, even surpass it. To achieve this, machine learning requires the guidance and reinforcement learning of a data scientist who would need to manually identify and create new features.
A downside of deep learning is that it requires longer training times since the quantity of training data can be massive. It can also be difficult to explain deep learning results since it’s hard to interpret the output of collective neurons. On the other hand, machine learning provides a clear set of rules to help explain the results.
Often confused as the same thing, deep learning and data science differ in that data science is an interdisciplinary field that uses multiple processes to collect, clean, analyze, and visualize data; then develop predictive or prescriptive models to solve a task or problem.
Deep learning and machine learning techniques are frequently used in data science to help assimilate big data, identify patterns and new features from that data, and create the predictive/prescriptive models used in data analytics.
AI is the capability of a device or software agent to display human-like intelligence such as observing, learning, taking action, and solving a problem or task autonomously.
AI has inhabited the realm of science fiction for years where intelligent machines walk, talk, think, and act like humans. Could fiction become reality? Yes, and it’s already here. Virtual assistants like Siri and Alexa use sophisticated voice recognition to translate, interpret, and act on our requests or questions.
Self-driving vehicles are also powered by AI. Data from cameras integrated into the body of vehicles can help recognize objects, road conditions, and other environmental factors that enable them to safely drive autonomously.
In the world of E-commerce, AI is powering smarter platforms that can predict our purchasing interests based on past purchases and website behavioral habits.
In the home, Nest, a smart thermostat, can learn for our heating and cooling preferences and automatically adjust the temperature. AI is also helping to keep our floors clean. Robotic vacuum cleaners use lasers to map a floor plan for smart navigation and obstacle avoidance.
Although each has unique attributes, AI, machine learning, and deep learning combine to provide powerful data and predictive analytics capabilities.
AI automates any task that requires cognitive decision making and problem solving. Machine learning is a subset of AI, but not all AI is created using machine learning. Instead, machine learning is a set of algorithms and methodologies that enable AI to process, learn, and analyze big data. Machine learning also enables AI to perceive images, voice, video stream, and other environmental sources. With this input AI can solve a problem or conduct a task.
As such, AI is dependent on machine learning and deep learning techniques to process and learn from data in an autonomous way, identify patterns and features, and make decisions or classifications.
Driven by technological innovation, computational power, and improved understanding of how the human mind works, AI is experiencing exponential growth. It’s progress is unstoppable, and while some worry that it is a threat to life as we know it – particularly in the labor market – at EastBanc Technologies we will continue to contribute to a smarter, better, and safer AI for the future.
AI and cloud computing together have reshaped the digital landscape in recent years. Alone, each is transformative; together, they can revolutionize industries, driving the next tech evolution. Let's explore how to optimize this integration.Read more
Explore the intricacies of AI deployment: Why does the performance of the AI models sometimes worsen after it's been out in public?Read more
Choosing your digital transformation partner is crucial for the business's long-term success. In our many years of experience, EastBanc Technologies has built a list of factors to consider when choosing a digital transformation consulting company.Read more
AI's vast potential brings challenges and opportunities that will redefine the industry's future; let's dive into how predictive analytics can help and look at several standout examples from diverse sectors that can provide insights for IT and beyond.Read more
The rise of low-code development platforms has revolutionized the software development process.; Llet's look at how they did do it and what they provide.Read more
Artificial intelligence (AI) has the potential to revolutionize various industries and aspects of our lives. However, along with its promises, AI also presents several challenges that need to be addressed for responsible and fair development and use. This article discusses some of the top challenges for AI, including bias in data and algorithms, explainability and transparency, ethical concerns, integration with society, security and safety, and regulatory framework.Read more
Increasingly complex AI and ML models require more data to be trained effectively - what are the ways of tackling the increasing power needs?Read more
The demand for faster and more efficient software delivery has led to the emergence of DevSecOps, a combination of DevOps and security practices. In this article series, EastBanc Technologies explores some of the top trends in DevOps, starting with DevSecOps.Read more
It's no secret that the business landscape is changing. In order to stay ahead of the competition, it's necessary to undergo a digital transformation. In this blog, we'll outline the steps you need to take in order to make sure your business is prepared for the future.Read more
Get ready to witness the power of artificial intelligence as it transforms the military, retail and personalized medicine industries! From revolutionizing defense strategies to streamlining the shopping experience to providing customized healthcare solutions, AI is changing the game in ways we never thought possible.Read more
In the context of EastBanc Technologies' dev approach, MVP stands for Minimal Viable Product. An effective method of quickly establishing a framework for a digital solution, the MVP streamlines the process of a product’s initial deployment. We take a look at the fundamentals of the MVP and how to construct one.Read more
Solar energy is a promising – and green – alternative to fossil fuels. As long as the sun is shining. Check out how AI helps solar energy providers optimize output, manage supply & demand and reduce the price of electricity using predictive analytics and machine learning. This is AI at work, making gigantic strides for worldwide adoption of this renewable energy source.Read more
Wind energy has the potential to cover much of the world's insatiable thirst for electricity in a sustainable way. Unfortunately, the wind doesn't always blow -- and not always with the same intensity. Using AI and machine learning models, energy producers and scientists are finding new ways to maximize the output and efficiency of wind energy.Read more
The potential for Artificial Intelligence (AI) in the green energy industry is rapidly gaining momentum. Renewable energy sources such as solar power are complex and unreliable due to constantly changing weather conditions, but AI can help remove obstacles and unleash the true power of solar.Read more
Apple’s introduction of passkeys with the latest versions of its MacOS and IOS operating systems means is a major step forward for online identity management, but passkeys will not hand us complete control over our own online identities. For that to happen, we need to look at Self-Sovereign Identity (SSI).Read more
Cryptocurrencies are notoriously volatile. Indeed, the rapid rises and vertigo-inducing plunges can make even the most stout-hearted crypto investors tremble. But with time, Bitcoin, et al may settle into a more temperate pattern and become a stable - or even a centerpiece - of our financial systems.Read more
Artificial intelligence will continue to disrupt many industries, and the best way to maximize the impact of the technology is to start teaching it early. Weaving AI learning into high school curricula will create a strong link between technologies and curious students, fostering future employees well trained in the digital world. -- benefiting business and driving innovation.Read more
A dive into the implementation of the blockchain in finances, smart contracts and NFTs.Read more
Blockchain is a word that is now heard everywhere, but not everyone has a clear understanding and knows what is there under the hood. In our second part of the blockchain guide let's dive deeper into the technology and concepts behind it.Read more
Teaching computer science to teenagers is a no-brainer in today's digital world. Here's why weaving artificial intelligence and machine learning into the high school curriculum can increase the growth of innovative technologies like never before.Read more
While traditional computers continue to evolve and pump out more raw power, they are no match for the quantum computer, which can tackle calculations that the most powerful conventional machines would need decades to process – in a split second.Read more
HackTJ 2002 is in the books, bringing together more than 400 bright young minds eager to tackle real-world problems with creative technology solutions. As a Gold Sponsor for the event, EastBanc Technologies created three challenges for the young innovators, and we are delighted to announce this year's top contestants -- and their winning hacks.Read more
This is EastBanc Technologies 3rd year sponsoring HackTJ, and our participation includes designing three challenges for teams to hack. The challenges will explore how to alleviate some of the world’s most pressing issues impacting our personal and professional lives.Read more
One “new” technology that has stuck is Blockchain. To understand what Blockchain is, you only need to know three things. What is a block? What is a chain? What is a ledger?Read more
Modern technology brings the world closer together, but millions of people continue to be left behind. The "digital divide" is multifaceted and impacts society in a variety of ways. These are some of the technologies that are helping bridge the gap.Read more
Artificial intelligence (AI) can be found almost everywhere in modern life. Learn key lessons and best practices that help companies avoid common AI pitfalls and achieve ROI from their AI systems.Read more
Open Data fuels today's digital economy, enables communication and innovation, boosts business and generally makes our lives easier. But how do we protect privacy if everything is open? Zero-knowledge proof could be the answer.Read more
Blockchain capabilities, including fully-automated data storage and transparency, make it an essential technology for cybersecurity. In this article, we look at some of its use cases.Read more
DevOps built-in flexibility allows development teams to work at a level that suits their resources and skills without being held back by departmental barriers.Read more
Artificial Intelligence (AI) – the capability of a machine or piece of software to display human-like intelligence – permeates our daily lives, often in ways we do not notice.Read more
Data-driven software touches our lives every day. Sometimes, it is in ways you see, such as when you check your Twitter feed, pay for your bus ticket or order your latte using your phone.Read more
EastBanc Technologies is recognized on CIOReview’s list: “Most Promising Microsoft Azure Solution Providers.”Read more
In this article, we’re going to dig a bit deeper into AI-implementation. We will take our airline use case a step further, and we will describe a specific example of how EastBanc Technologies solved a particularly challenging problem through AI and machine learning.Read more
If your organization provides a product or service -- which applies to just about any business on the planet -- you, too, can benefit from Artificial Intelligence (AI). While implementing AI may sound daunting, it doesn't have to be complex or expensive. This article covers the basics of AI and looks at some easy-to-explore use cases.Read more
Digital transformation is about opportunity and survival. Businesses that transform digitally gain a significant competitive advantage.Read more
Part 2: Best practices for modernizing your company’s IT infrastructure to ensure innovation success.Read more
Best practices for modernizing your company’s IT infrastructure to ensure innovation success.Read more
Learn how machine learning engineers and data scientists collaborate and roll out models faster and with ease using Azure Machine Learning.Read more
What is DevOps, what are DevOps practices, and how do you implement DevOps? Your FAQs answered.Read more
Refactor, rewrite, or leave as is? Learn when and how to bring your legacy systems up to speed with modern application development practices.Read more
Learn how technology can better meet your business needs with this foundational understanding of how software and system architectures work.Read more
Ready to embrace AI? Explore why cloud computing is the best infrastructure for your AI model, not on-premises.Read more
Software is a strategic differentiator that can catalyze digital transformation. Organizations are investing in technology, such as modern cloud services, to drive efficiencies and increase the customer experience. To make this a reality, it’s essential that business leaders have a basic understanding of business software and applications work and the opportunities they bring.Read more
How an intelligence-driven customer technical support approach can transform your support from a reactive operation to a streamlined, efficient, and proactive operation.Read more
Kubernetes is a popular container orchestration system, but how did it come to be and why, and what role does it play in digital transformation?Read more
Continuous integration and continuous delivery (CI/CD) is integral to a DevOps approach to software development. But what is CI/CD and why is it key?Read more
2020 has seen profound change in the way we live and work with COVID-19 accelerating the pace of digital transformation. Yet, business leaders are often confused about how to implement one of the key enablers of...Read more
Artificial intelligence (AI), together with its brethren buzzwords data science, machine learning, and deep learning have been around for some time now and are no longer future concepts. Yet misconceptions persist about the true meaning of these terms.Read more
When SUSE, the world’s largest independent open source company, announced its acquisition of Rancher Labs in early July 2020, the industry took notice. Clearly, the Kubernetes management industry is very much alive.Read more
We live in a technology-driven world. Even non-technology companies are seeing their business models increasingly shaped by technology. Led by disrupters such as Amazon and Netflix, those enterprises who recognized opportunities early have found ways to extend the analog experience into a digital one. Even creating new revenue streams that they could never have predicted.Read more
Digital transformation is about delivering core competencies in a digital, automated, and user-centric manner. Driven by data and powered by tech (e.g. cloud, cloud native stack, AI, machine learning, and deep learning), it increases business agility, competitiveness, and enhances customer value.Read more
Let’s start by understanding where DataOps falls in the line-up of current IT methodologies. DataOps is the next level up from ETL (extract, transform, and load) and MDM (master data management systems) in terms of organizing data and processes. It can also be thought of as a methodology that combines DevOps and Agile within the field of data science.Read more
The hotel industry hasn’t changed much in the past decades. While they have introduced some level of digitization such as websites and apps, they haven’t fully embraced digital transformation. Indeed, if things are working fine, why change? Because the next unforeseen disruptor may be right around the corner.Read more
The term “DataOps” has picked up momentum and is quickly becoming the new buzz word. But we want it to be more than just a buzz word for your company, after reading this article you will have the knowledge to leverage the best of DataOps for your organization.Read more
Unstructured text is found in many, if not all business functions, and can become a source of valuable insight. Product reviews will guide your customers’ preferences, customer support chats can identifyRead more
Disclaimer: We have not spoken to a WeWork executive and have no further background information. This is merely a thought experiment to exemplify what digital transformation is about.Read more
In part one of this series, we defined data science and explored the role of a data scientist — including data preparation, modeling, visualization, and discovery. We also introduced the role of a machine learning engineer who closely collaborates with the data scientist.Read more
Big data continues to grow exponentially creating a critical need for solutions that can make sense and extract valuable information from it. For example, the Internet is full of a wide variety of constantly growing text sources— blog posts, forum posts, chats, message boards, item and services reviews, etc.Read more
Kubernetes, the de facto container orchestrator, is great and should be part of any DevOps toolkit. But, just as any other open source technology, it’s not a full-fletched ready-to-use platform.Read more
With the increasing popularity of machine learning (ML), it’s becoming more difficult for data scientists to find the appropriate tools for a specific task and decide on a robust approach. Should they stick to the basics and code everything from scratch or use one of the many pre-built tools that keep popping up on the market?Read more
Blue-green deployments and canary releases mitigate application deployment risk by enabling IT to revert back to the previous version should an issue occur during the release. Switching back and forth between versionsRead more
For those who were still debating whether they should hop on the digital transformation bandwagon, the COVID-19 crisis was a wakeup call, maybe even a slap in the face.Read more
The entire business world is talking about digital transformation. IT leaders, on the other hand, talk about DevOps, cloud native, Kuberentes and containers.Read more
If your organization leverages technology as a differentiator, a DevOps approach to application and service delivery is inevitable. The benefits are just too great.Read more
Digital transformation is one of today’s biggest buzzwords. Everyone is talking about it; everyone wants it. We all know the role technology is playing in enabling businesses to innovate at an unprecedented pace.Read more
The data on big data indicates that up to 60% of analytics projects fail or are abandoned, costing companies an average of $12.5 million. That’s not the result we seek from data lakes. Instead, companies are increasingly finding themselves mired in data swamps that are overfilled and too muddy to offer any useful visibility. Or are they?Read more
We collect data at a mind-boggling pace. In fact, as companies, we’re hoarding it. But what good is data if it can’t speak to us? Fortunately, data complexity can be broken down through design and visualization – the charts, graphs and plots that show trends, outliers and opportunities.Read more
As a company and as a team, our lives at EastBanc Technologies have always been about tackling the biggest problems for the biggest organizations.Read more
Artificial intelligence (AI) surrounds us. It unlocks our phones, creates our shopping list, navigates our commute, and cleans spam from our email. It’s making customers’ lives easier and more convenient.Read more
Nearly every week there’s something new in our industry. The pace of technology is unprecedented, the role of IT is booming, and innovation is part of our DNA.Read more
Technology is accelerating at such a rate that it permeates all industries. In fact, software is the only industry that cuts horizontally across all verticals.Read more
Innovation is a critical part of business. While prioritizing production in general makes sense, the best approaches make innovation a component of the whole production process.Read more
We recently sat down with a large pharmaceutical company to discuss their data analytics projects. What we heard wasn’t a surprise. Three of the four large analytics efforts they undertook last year had failed.Read more
AMS Group is a cohesive group of established companies that provide technology and security equipment to aerospace, defense, and security markets.Read more
A European market leader in online survey and feedback software acquired complementary companies in different Wester European countries, each of which had its own survey platform.Read more
Everyone loves their own data. Collecting it. Analyzing it. Drawing conclusions from it. But often, when you allow departments or business units within your organization to gather their own data, that data isn’t shared.Read more
Gartner predicts that through 2017 60% of big data projects will fail to go beyond piloting and experimentation and ultimately will be abandoned.Read more
Organizations generally understand the power behind analytics, but how do you make it work culturally and technically? We take a look at the barriers to data analytics success and suggest new approaches that buck the system, with dramatic results.Read more
And how to make your next data analytics project succeed?Read more
Container use is exploding right now. Developers love them and enterprises are embracing them at an unprecedented rate.Read more
If you’re making the move to containers, you’ll need a container management platform. And, if you’re reading this article, chances are you’re considering the benefits of Kubernetes.Read more
Wouldn’t it be nice to reach artificial intelligence (AI) nirvana? To have a system that provides real-time, context-aware decisions.Read more
Today’s IT environment is moving and evolving at an unprecedented pace. So, all of a sudden, your 5-year old software infrastructure can look more like it’s 50. To get your software current – and stay there – requires flexibility. Moving to containers does just that. There’s been lots of talk about containers over the past few years – so why aren’t you on the bandwagon yet?Read more
Under pressure to deliver applications faster and ensure 24/7 runtime, organizations are increasingly turning to DevOps methodologies to deliver applications quicker and in an automated fashion. But what tools should you have in your DevOps toolkit?Read more
Amazon Web Services (AWS), Azure, and Google Cloud Platform (GCP) are the public cloud market leaders, but how do you determine which of them best supports your enterprise's specific needs? For most enterprises, and for the foreseeable future, it’s going to be a multiple answer question.Read more
As the dominant movie rental service in the 90s and early 2000s, Blockbuster was the market leader, seemingly indefatigable. Until the great disruptor, Netflix, hit the scene.Read more
Big Data. Everyone’s paying for it, collecting it, and talking about it, but what are companies actually doing with it?Read more
The API management market is a hot one. As more organizations make investments in mobile, IoT, and big data, APIs are a core of their digital strategy.Read more
Big data is everywhere. Organizations are being advised to hoard it and do everything they can to derive actionable insights. This article will argue that this approach puts the cart before the horse.Read more
Let’s face it. Organizations struggle with their legacy applications. Even when they still solve some of the business’ problems, they reach a point where they can no longer keep up with market and industry demands.Read more
Let’s flash back to 2000. You’ve survived Y2K and you’re building systems for CRM, inventory, logistics, or data. They’re all state-of-the-art, and get the job done, even if they don’t talk to each other.Read more
It’s a mobile app world, and we just live in it. But for those working on the “next big thing,” there’s a conundrum – everyone knows we should be building apps in HTML, but not every device out there runs it as smoothly as it should.Read more
In technology, everyone likes to talk about “future-proofing.” But even for the most cutting-edge tech, time always catches up.Read more
The future is here. No, we don’t have flying cars or robot butlers – yet – but it’s definitely a digital world.Read more
We’re excited to announce Microsoft Azure support for the Kubernetes auto scaling module, an open source system for automating deployment, scaling, and management of containerized applications.Read more
You can’t mention enterprise technologies today without getting into a discussion about the cloud. “Are you in the cloud yet?” Why jumping headlong into cloud computing may not be the necessary move for your business.Read more
In the mad rush to move to the cloud, some organizations put the proverbial cart in front of the horse. They’re just looking for the best hosting, the preferred provider, or whatever the rest of the industry is using.Read more
2016 saw momentum in many areas – DevOps, cloud technologies, and big data- at the thrust of innovation. So, what tech predictions will define 2017?Read more
Every month, week, or day, it seems there’s buzz about yet another solution or service that will revolutionize your industry – or more simply, make your life easier.Read more
Apps. Sensors. They’re everywhere. Your phone, your car, your TV, even your refrigeratorRead more
In an increasingly commoditized market, learn how to cut through the noise and forge a cloud strategy that meets your needsRead more
Fleet management is a challenging business. This is particularly true of snow removal services where the dynamics on the ground can change fast and the pressures to perform put fleet supervisors to the test – in the toughest of conditions.Read more
Long before the first flakes fall from the sky many municipalities begin to prepare for the cold, icy, and snowy conditions that inevitably lie ahead.Read more
Fun fact: in 2014, cloud services were already a $45 billion business worldwide, and are expected to grow to $95 billion by 2017. Will you be part of that equation?Read more
Simple is good. Simple is clean. And whether I’m cooking or planning a trip, simple is always better, right? So why do so many companies make user experience (UX) so complex?Read more
Future-ready predictive analysis infrastructures hold the key to gaining insights from data today, and into tomorrow.Read more
Immersive and exciting, Virtual Reality is already part of our lives, whether it’s a plot device in a new sci-fi thriller or the best way to enjoy the latest video games or thrill rides.Read more
Now that smartphones are the most widely used tool for navigating important life activities (nearly two thirds of Americans own one), there’s pretty much an app for everything these days.Read more
If you’re tasked with choosing an API management system, Charles Dickens summed it up best: “It was the best of times, it was the worst of times.”Read more
DevOps: the panacea for all that’s wrong with enterprise IT. Where siloed teams who keep information close to their chest are replaced by agile, transparent relationships between developers and operations and fast and stable workflows that improve IT efficiency significantly and very visibly.Read more
As a technology company focused on complex project integrations that unify legacy systems as well as modular solutions that ensure lasting scalability, we work on a multitude of projects that involve custom software development; packaged, open source, and SaaS software integration; infrastructure setup; and production operations and maintenance.Read more
In an earlier blog we talked about why you need to integrate API management into your business strategyRead more
In a previous release of “What the Tech?” we discussed why you should integrate API management into your business strategy.Read more
Smart cars, smart homes, smart devices. The Internet of Things (IoT) is already transforming how we live. But very soon, the IoT will swiftly extend into the enterprise.Read more
Why you Need to Integrate API Management into your Business StrategyRead more
The promise of big data is, well, big! With terabytes of intelligence at their disposal, organizations can make faster, more accurate decisions, monitor trends, and even predict the future.Read more
Businesses accumulate data, create content, or possess unique business logic—each of which represents an untapped business opportunity. But how can organizations realize that opportunity?Read more
The Internet of Things (IoT) is much more than a consumer trend, it’s rapidly changing the way enterprises are using data to improve business decision-making.Read more
Content consumption is changing rapidly. With multiple channels and media formats, reaching target audiences is getting harder than ever.Read more
The way in which we consume content is changing rapidly and a few trends have emerged recently that we think will have a meaningful impact on media organizations this year and in years to come.Read more
Building a mobile app isn’t as simple as it used to be. With multiple devices to cater to, development teams must ask themselves a few questions:Read more