HubBucket | Technology Research and Development
Science, Technology, Engineering, Artificial Intelligence - AI, Machine Learning - ML, Deep Learning, Artificial Neural Networks, Computer Vision, Machine Vision, Natural Language Processing - NLP / NLProc, Robotics, Co-Bots, Virtural Reality - VR, Augmented Reality - AR, Mixed Reality, Cloud Computing, Quantum Computing, Blockchain, Encryption, Cyber Security, Development and Operations - DevOps, Healthcare, HealthIT, MedTech, Wearables, Blockchain, FinTech, Business Technology, Renewable Energy and Sustainability Technology, etc.
HubBucket develops technology that will:
- Help businesses improve their products and services
- Help to save Human lives
- Help to save our planet for future generations.
HubBucket, Technology R&D Divisions:
About HubBucket, Inc.
HubBucket, Inc. is a Minority (African American) and United States Navy - USN Veteran founded and owned corporation. HubBucket, Inc. is located in Brooklyn, New York. Mr. VonVictor V. Rosenchild is the Founder, Chairman, President and CEO of HubBucket, Inc. Please visit our About page on this website to learn more about HubBucket, Inc.
Enterprise Technology Research and Development
A strong enterprise automation strategy can improve your organization's approach to business process management and cut costs dramatically. HubBucket Enterprise, "HubBucketEP" is a research and development - R&D division of HubBucket, that focuses on the development of Artificial Intelligence - AI, Machine Learning - ML, Deep Learning, and Neural Network applications and systems designed to automate and augment business processes.
Robotics and process automation technologies are empowering organizations to approach operations in entirely new ways, in our 21st Century global society. Businesses of all sizes are seriously looking at larger-scale paybacks through value levers that have tremendous potential to shift enterprise value, realign the workforce and achieve economies of operational scale.
HubBucket Enterprise, "HubBucketEP" is a unified suite of Artificial Intelligence - AI Automation product that enable organizations to reduce cost, and shorten the time it takes to bring their products and services to market.
Enterprise Automation Technology
Industrial Technology Research and Development
Industry Automation Technology
The HubBucket Industries technology, research and development - R&D division is focused on developing technology that will enable corporations and associated organizations working within the industrial space to increase their productivity, while maintaining the required levels of safety for their human labor.
HubBucket Industries develops Artificial Intelligence - AI, Robotics and Co-Bots that enable organizations to streamline their Business Process by automating redundant tasks, coupled with enhancing the physical capabilities of their Human Labor with Exoskeleton and Co-Bots.
What is a Co-Bot?
A Cobot / Co-Robot / Co-Bot (from collaborative robot) is a robot intended to physically interact with humans in a shared workspace. This is in contrast with other robots, designed to operate autonomously or with limited guidance, which is what most industrial robots were up until the decade of the 2010s.
What is a Human Exoskeleton?
A Human Exoskeleton is the External Skeleton that supports and protects an Human's body. More often than not, a Human Exoskeleton consist of a Robotic Assisted outer framework, that the person(s) wears in order to provide them with more strength and dexterity. The Human Exoskeleton enables the person who wears it, to lift more weight than their body normally could, in addition to helping them work longer hours, since they can reserve their Physical energy.
Development and Operations Technology Research and Development
Development and Operations - DevOps
DevOps (Development and Operations) is an enterprise software development phrase used to mean a type of agile relationship between development and IT operations. The goal of DevOps is to change and improve the relationship by advocating better communication and collaboration between these two business units.
HubDevOps focuses on developing Artificial Intelligence - #AI automation tool for DevOps teams. The AI DevOps tools supports scripting and executing arbitrary tasks and includes a set of sane-default deployment workflows.
HubBucket NLP / NLProc
Natural Langauge Processing Technology Research and Development
Natural Language Processing
Natural Language Processing - NLP/NLProc
Natural Language Processing (NLP) is fast becoming an essential skill for modern-day organizations to gain a competitive edge. It has become the essential tool for many new business functions, from chatbots and question answering systems to sentiment analysis, compliance monitoring, and BI and analytics of unstructured and semi-structured content.
Consider all the unstructured content that can bring significant insights – queries, email communications, social media, videos, customer reviews, customer support requests, etc. Natural Language Processing (NLP) tools and techniques help process, analyze, and understand unstructured “big data” in order to operate effectively and proactively.
Our Natural Language Processing services cover a range of needs, from data acquisition and processing to analytics, entity extraction, fact extraction, and question answering systems (think of a digital assistant built uniquely for your enterprise).
HubBucket Virtual and Agumented Reality
Virtual and Augmented Reality Technology Research and Development
Virtual Reality - VR and Augmented Reality - AR Technology
The difference between Virtual, Augmented, and Mixed Reality technologies:
- Virtual Reality (VR) immerses users in a fully artificial digital environment.
- Augmented Reality (AR) overlays virtual objects on the real-world environment.
- Mixed Reality (MR) not just overlays but anchors virtual objects to the real world.
We conduct research in Virtual, Augmented and Mixed Reality technology, and develop Virtual Reality, Augmented Reality, and Mixed Reality applications for Healthcare, HealthIT, Medicine, MedTech, Renewable Energy, Sustainability, and Business. In addition, and with a wider range, we also develop these applications for Science, Technology, and Engineering.
Virtual & Augmened Reality
HubBucket IoT and IIoT
Internet and Industrial Internet of Things Technology Research and Development
Internet of Things
Internet of Things - IoT
The Internet of Things (IoT) is the concept of basically connecting any device with an on and off switch to the Internet (and/or to each other). This includes everything from cellphones, coffee makers, washing machines, headphones, lamps, wearable devices and almost anything else you can think of. This also applies to components of machines, for example a jet engine of an airplane or the drill of an oil rig. As I mentioned, if it has an on and off switch then chances are it can be a part of the IoT. The analyst firm Gartner says that by 2020 there will be over 26 billion connected devices... That's a lot of connections (some even estimate this number to be much higher, over 100 billion). The IoT is a giant network of connected "things" (which also includes people). The relationship will be between people-people, people-things, and things-things.
On a broader scale, the IoT can be applied to things like transportation networks: "Smart Cities" which can help us reduce waste and improve efficiency for things such as energy use; this helping us understand and improve how we work and live. The reality is that the IoT allows for virtually endless opportunities and connections to take place, many of which we can't even think of or fully understand the impact of today. The IoT also opens up companies all over the world to more security threats. Then we have the issue of privacy and data sharing. Another issue that many companies specifically are going to be faced with is around the massive amounts of data that all of these devices are going to produce. Companies need to figure out a way to store, track, analyze and make sense of the vast amounts of data that will be generated.
Industrial Internet of Things - IIoT
The Industrial Internet of Things originally described the IoT (Internet of Things) as it is used across several industries such as manufacturing, logistics, oil and gas, transportation, energy/utilities, mining and metals, aviation and other industrial sectors and in use cases which are typical to these industries.
Just like the Internet of Things - IoT in general, the Industrial Internet of Things - IIoT covers many use cases, industries and applications. Initially focusing on the optimization of operational efficiency and rationalization/automation/maintenance, with an important role for the convergence of IT and OT, the Industrial Internet of Things opens plenty of opportunities in automation, optimization, intelligent manufacturing and smart industry, asset permance management, industrial control, moving towards an on demand service model, new ways of servicing customers and the creation of new revenue models, the more mature goal of industrial transformation.
This distinction between the Internet of Things - IoT and the Industrial Internet of Things - IIoT obviously is somewhat artificial and on all levels there are overlaps. The fastest growing categories of IoT use cases, for instance, are cross-industry. Moreover, although some technologies, architectural frameworks and applications across all IoT layers differ (edge computing and fog computing are typical in Industrial IoT, there are different types of network and connectivity tools, IIoT gateways serve other purposes, Industrial IoT platforms support other use cases than IoT platforms overall, digital twins are mainly about industrial markets, the use cases for augmented reality are not the same and so forth) between Industrial IoT and Consumer IoT an average large IIoT project will leverage several forms of connectivity and solutions of which some are used in consumer IoT as well.
The Industrial Internet of Things - IIoT can be defined as ‘machines, computers and people enabling intelligent industrial operations using advanced data analytics for transformational business outcomes”. Supply chains become connected supply chains, factories become connected factories and so forth. In this sense, the connectedness stretches far beyond the simple connectedness – and data-driven results – of devices and industrial assets to a more connected ecosystem, whereby the extended enterprise gains a new meaning. This is why the Industrial Internet of Things is mainly used in the context of Industry 4.0, the Industrial Internet and related initiatives across the globe, which all have their own names, from smart production to smart factory or intelligent industry.
HubBucket IoT / HubIoT
Within the HubBucket IoT / HubIoT Technology Research and Development - R&D division, we focus on developing Artificial Intelligence - AI, Machine Learning and Deep Learning applications for both the Internet of Things - IoT and the Industrial Internet of Things - IIoT.
HubBucket Cloud Computing
Cloud Computing Technology Research and Development
A Cloud Application, or Cloud App, is a software program where cloud-based and local components work together. This model relies on remote servers for processing logic that is accessed through a web browser with a continual internet connection. Cloud Application servers typically are located in a remote data center operated by a third-party Cloud Service Provider - CSP, such as Amazon Web Services - AWS, Google Cloud Platform - GCP, IBM Cloud, Microsoft Azure, etc. Cloud-based application tasks may encompass Email, File Storage and Sharing, Order Entry, Inventory Management, Word Processing, Customer Relationship Management (CRM), Enterprise Resource Planning (ERP), Data Collection, Financial Accounting, etc.
Benefits of Cloud-based Applications / Cloud Apps
- Fast response to business needs. Cloud applications can be updated, tested and deployed quickly, providing enterprises with fast time to market and agility. This speed can lead to culture shifts in business operations.
- Simplified operation. Infrastructure management can be outsourced to third-party cloud providers.
- Instant scalability. As demand rises or falls, available capacity can be adjusted.
- API use. Third-party data sources and storage services can be accessed with an application programming interface (API). Cloud applications can be kept smaller by using APIs to hand data to applications or API-based back-end services for processing or analytics computations, with the results handed back to the cloud application. Vetted APIs impose passive consistency that can speed development and yield predictable results.
- Gradual adoption. Refactoring legacy, on-premises applications to a cloud architecture in steps, allows components to be implemented on a gradual basis.
- Reduced costs. The size and scale of data centers run by major cloud infrastructure and service providers, along with competition among providers, has led to lower prices. Cloud-based applications can be less expensive to operate and maintain than equivalents on-premises installation.
- Improved data sharing and security. Data stored on cloud services is instantly available to authorized users. Due to their massive scale, cloud providers can hire world-class security experts and implement infrastructure security measures that typically only large enterprises can obtain. Centralized data managed by IT operations personnel is more easily backed up on a regular schedule and restored should disaster recovery become necessary.
How Cloud-based Applications work
Data is stored and compute cycles occur in a remote data center typically operated by a third-party company. A back end ensures uptime, security and integration and supports multiple access methods.
Cloud applications provide quick responsiveness and don't need to permanently reside on the local device. They can function offline, but can be updated online.
While under constant control, cloud applications don't always consume storage space on a computer or communications device. Assuming a reasonably fast internet connection, a well-written cloud application offers all the interactivity of a desktop application, along with the portability of a web application.
Cloud-based Applications / Cloud Apps vs. Web Applications / Web Apps
With the advancement of remote computing technology, clear lines between cloud and web applications have blurred. The term cloud application has gained great cachet, sometimes leading application vendors with any online aspect to brand them as cloud applications.
Cloud and web applications access data residing on distant storage. Both use server processing power that may be located on premises or in a distant data center.
A key difference between cloud and web applications is architecture. A web application or web-based application must have a continuous internet connection to function. Conversely, a cloud application or cloud-based application performs processing tasks on a local computer or workstation. An internet connection is required primarily for downloading or uploading data.
A web application is unusable if the remote server is unavailable. If the remote server becomes unavailable in a cloud application, the software installed on the local user device can still operate, although it cannot upload and download data until service at the remote server is restored.
The difference between cloud and web applications can be illustrated with two common productivity tools, email and word processing. Gmail, for example, is a web application that requires only a browser and internet connection. Through the browser, it's possible to open, write and organize messages using search and sort capabilities. All processing logic occurs on the servers of the service provider (Google, in this example) via either the internet's HTTP or HTTPS protocols.
A CRM application accessed through a browser under a fee-based software as a service (SaaS) arrangement is a web application. Online banking and daily crossword puzzles are also considered web applications that don't install software locally.
An example of a word-processing cloud application that is installed on a workstation is Word's Microsoft Office 365. The application performs tasks locally on a machine without an internet connection. The cloud aspect comes into play when users save work to an Office 365 cloud server.
Cloud-based Applications / Cloud Apps vs. Desktop Applications
Desktop applications are platform-dependent and require a separate version for each operating system. The need for multiple versions increases development time and cost, and complicates testing, version control and support. Conversely, cloud applications can be accessed through a variety of devices and operating systems and are platform-independent, which typically leads to significant cost savings.
Every device on a desktop application requires its own installation. Because it's not possible to enforce an upgrade whenever a new version is available, it's tricky to have all users running the same one. The need to provide support for multiple versions simultaneously can become a burden on tech support. Cloud applications don't face version control issues since users can access and run only the version available on the cloud.
Testing of Cloud Applications / Cloud Apps
Testing cloud applications prior to deployment is essential to ensure security and optimal performance.
A cloud application must consider internet communications with numerous clouds and a likelihood of accessing data from multiple sources simultaneously. Using API calls, a cloud application may rely on other cloud services for specialized processing. Automated testing can help in this multi-cloud, multi-source and multi-provider ecosystem.
The maturation of container and microservices technologies has introduced additional layers of testing and potential points of failure and communication. While containers can simplify application development and provide portability, a proliferation of containers introduces additional complexity. Containers must be managed, cataloged and secured, with each tested for its own performance, security and accuracy. Similarly, as legacy monolithic applications that perform numerous, disparate tasks are refactored into many single-task microservices that must interoperate seamlessly and efficiently, test scripts and processes grow correspondingly complex and time-consuming.
Testing cloud applications security includes penetration and data testing. Potential attack vectors, including advanced persistent threats, Distributed Denial of Services (DDoS), phishing and social engineering, must also be examined.
Cloud applications must be tested to ensure processing logic is error-free. Test procedures may be required to conform to rules established by a given third-party provider.
HubBucket Clouds - HubClouds
Our HubClouds Technology Research and Development - R&D division focuses on the design and development of Cloud-based Applications / Cloud Apps for Healthcare, STEM fields, Industry, Startups, Small Business, Enterprise, etc. Moreover, HubClouds designs and develops Artificial Intelligence - AI, Machine Learning - ML, and Deep Learning Cloud-based Applications / Cloud Apps.
HubBucket Quantum Computing
Quantum Computing Technology Research and Development
Quantum Computing Applications
Quantum Computing Application Development
Quantum Computers work on principles very different from those of classical, electronic computers. They exploit the behavior of subatomic particles as described by quantum mechanics, a subfield of physics that explains the complex and weird behavior of subatomic particles—that is, objects smaller than atoms. For instance, electrons can exist in multiple distinct states at the same time, a phenomenon known as superposition. And it’s impossible to know for sure at any given instant what state an electron may be in, because the very act of observing the state changes it. Furthermore, subatomic particles can be “entangled,” so that a change to one influences another, even if the two particles are physically distant from each other. To capture these complexities, quantum mechanics describes the state of subatomic particles probabilistically using “complex numbers.”
Over 30 years ago, legendary physicist Richard Feynman mused that no computer was powerful enough to perform the calculations needed to simulate the complex behavior of subatomic particles. Yet these particles behave in predictable ways. Their predictable behavior could be seen as a kind of calculation, one that was performed by the particles themselves. Could we harness these particles, he wondered, to perform calculations that are beyond the reach of the fastest known computers?
Much faster—in theory
The idea of a quantum computer remained a curiosity for years. Then came theoretical proof that computing based on quantum mechanics could be much more efficient than classical computing. In 1994, a researcher at AT&T’s Bell Labs named Peter Shor showed that a quantum computer could in theory solve a certain type of problem—finding the prime factors of an integer—much faster than classical computing methods. This happens to be a result of great importance, since the encryption systems used around the world rely on the fact that classical computers cannot factor large numbers in a practical amount of time. A quantum computer might someday render these encryption systems obsolete.
Two years later, another researcher at Bell Labs, Lov Grover, proved that a quantum computer could excel at solving other types of problems as well. The phonebook problem is the name for the task of finding something in an unsorted list—like looking up someone in the phonebook by her phone number rather than her name. In classical computing, the standard algorithm is to inspect each entry until the matching phone number is found, requiring as many inspection steps are there are entries in the phone book. Grover demonstrated that a quantum computer could solve this problem in far fewer steps—specifically, the number of steps equal to the square root of the number of entries in the phone book. Finding the matching phone number in a list of a billion entries would require just 31,623 operations—the square root of a billion—and, obviously, a small fraction of the time.
Typically, computing has picked up speed when engineers have developed more powerful hardware. But quantum algorithms outpace their classical counterparts not because they run on faster hardware—it’s because the quantum mechanical mathematics they use requires fewer steps. True, superior quantum algorithms probably do not exist for every class of computational problem. In fact, researchers don’t yet know all the types of problems at which quantum computing could excel. But the applications are broad. They include optimization problems—finding the best solution to a problem when numerous solutions are feasible—which have applications in many fields; factorization, with immediate applications in cryptography; physics simulation; number theory; and topology.
Building a Quantum Computer
The proof of the theoretical superiority of quantum computing methods has spurred research into how engineers might actually build a working quantum computer. Perhaps unsurprisingly, it’s a challenge.
As we know, the fundamental unit of information in a classical computer is the bit, short for binary digit. The analogous building block of a quantum computer, which embodies the mysterious and powerful properties of subatomic particles, is known as a quantum bit, or qubit. Classical computers use electrical charge to represent bits. And they perform calculations using circuits that implement Boolean algebra (the logic of true/ false, and/or). Quantum computers, by contrast, take advantage of quantum mechanics rather than electrical conductivity. And to manipulate these properties, they use linear algebra to manipulate matrices of complex numbers rather than Boolean algebra to manipulate bits.
While manufacturing semiconductors capable of storing and manipulating bits is well established, making qubits and quantum gates is very much a work in progress, though firms such as IBM, Google, and Microsoft are exploring15 a variety of methods, including using superconducting loops, trapped ions, silicon quantum dots, topological qubits, and microscopic diamonds.
The engineering challenges involved in building a Quantum Computer are formidable. The device created by D-Wave Systems, for instance, must operate in an enclosure carefully isolated from the outside environment at a temperature far colder than interstellar space. A typical quantum bit, or qubit, is perishable: It maintains its state for perhaps 50 microseconds before errors creep in.18 And even reading the value of a qubit is a very exacting process. The difference in energy between a zero and a one is just 10^-24 joules19—one ten-trillionth as much as an X-ray photon.
Researchers around the world are regularly announcing progress in tackling the engineering challenges of quantum computing. But mass production of quantum computing is widely regarded as years away.
Enterprises are already seeking applications
Despite the nascent state of quantum computing, dozens of public and private sector organizations are already researching applications of great potential value. Financial services firms are notably active. For instance, Barclays, Goldman Sachs, and other financial institutions are investigating the potential use of quantum computing in areas such as portfolio optimization, asset pricing, capital project budgeting, and data security. In aerospace, Airbus is exploring applications in communications and cryptography, while Lockheed Martin is investigating applications in verification and validation of complex systems and accelerating the development of machine learning algorithms.
The US Navy is paying for training in quantum computing and plans to develop algorithms for optimization problems such as data storage and energy-efficient data retrieval with underwater autonomous robots, and NASA is exploring applications in communications, distributed navigation, and system diagnostics. Information technology players such as Alibaba, Google, and IBM are working on applications such as hack-resistant cryptography, software debugging, and machine learning. Life sciences firms are seeking applications of quantum computing in personalized medicine and drug discovery.
Other organizations are eyeing applications in logistics, industrial chemistry, and energy that could be extremely valuable. For instance, the standard process for manufacturing fertilizer uses some 2 to 5 percent of global natural gas production each year; quantum simulation could lead to the discovery of a more efficient process that could save billions of dollars and trillions of cubic feet of natural gas annually. Another intriguing application is using quantum computation to discover new, high-density designs that could dramatically expand the capacity of batteries used in everything from portable electronics to electric vehicles. Improvements in battery density have been running at just 5 to 8 percent annually—painfully slow compared to the familiar exponential Moore’s Law pace.
When data and transactions are no longer secure
One area in which quantum computing is already having an impact is encryption. The most widely used techniques for encrypting and protecting transactions depend on the impossibility of swiftly finding the prime factors of large numbers. For example, it would take a classical computer 10.79 quintillion years to break the 128-bit AES encryption standard, while a quantum computer could conceivably break this type of encryption in approximately six months.34 This has led to a search for encryption methods that would be resistant to attacks from quantum computers—to make information systems “quantum resistant.”
In 2015, the National Security Agency’s Information Assurance Directorate announced that it will begin guiding agencies and the private contractors who cater to them on transitioning to quantum-resistant algorithms. Public and private sector entities have already begun making plans to transition to encryption systems—so-called post-quantum cryptography—that would withstand attacks by a future quantum computing system.35 Enterprises are already thinking about risks to their encrypted data even before quantum encryption attacks become a reality. They are restricting access to or completely deleting sensitive data, even in encrypted formats, to prevent hostiles from capturing that scrambled data with the hope of decrypting it with quantum computers in the future.
It’s not just the hardware
Fulfilling the potential of quantum computing depends on more than just building new hardware. New software will be crucial as well: Because quantum computing takes an entirely different approach to problem solving, entirely new algorithms that take advantage of this approach will be needed to achieve a quantum speedup in performance. New software development tools will also be required. A quantum computing technology ecosystem—consisting of start-up companies, incumbent tech firms, and research institutions—that aims to provide the needed software is now emerging.
Growing investment is supporting a nascent technology ecosystem
Some incumbent IT providers have active quantum computing research programs that may eventually lead to commercial products. These include Google, IBM, Intel, Hewlett Packard Enterprise, Microsoft, Nokia Bell Labs, and Raytheon. They are exploring various areas, including building components such as qubits and quantum gates (basic circuits) and exploring quantum algorithms, software and tools, and encryption techniques.
A number of start-ups, some backed by venture capital, have entered the market as well. Besides D-Wave Systems, which is developing quantum computers, as many as a dozen companies are developing quantum computing components or quantum computing algorithms, software tools, or applications.
What to watch for
Breakthroughs in quantum computing are coming quickly, with some researchers saying that the challenges have progressed from basic science to engineering.44 Even so, no one knows when quantum computers might become widely commercially available. To stay abreast of progress in quantum computing, here are a few specific areas worth following:
Fundamental hardware engineering. There is a lot of progress still to be made in creating the basic building blocks of quantum computers such as qubits and quantum gates. A recent example of progress: Researchers at the University of New South Wales in Australia recently created a qubit that remains stable 10 times longer than previous technology. In partnership with the Australian government, the researchers are working to develop a prototype quantum silicon chip that could lead to the creation of a practical quantum computer.
Quantum algorithms and software. The design of quantum algorithms requires specialized skills. And designs are specific to the type of quantum computer used. On D-Wave’s system, for instance, computational tasks must be expressed as optimization problems. As quantum hardware evolves, the software written for quantum computers will have to evolve too.46 The level of activity and innovation in quantum software tools, operating systems, and algorithms—as well as in foundational engineering—will help indicate progress toward practical quantum computing.
Quantum supremacy. A symbolic milestone to watch for is the achievement of “quantum supremacy”—the creation of a general-purpose quantum computer that can perform a task no classical computer can. Google, which has already announced a 9-qubit quantum computer, has published a paper suggesting its researchers believe that a planned 50-qubit computer could achieve that goal in the next couple of years.
HubBucket Renewable Energy and Sustainability
Renewable Energy and Sustainability Technology Research and Development
Renewable Energy Technology
Technology for Renewable Energy and Sustainability
HubBucket Maping Technology
Maping Technology Research and Development
Graph Mapping Technology
Atlas Mapping Technology
GIS Mapping Technology
HubBucket Cyber Security and Information Security
Cyber Security and Information Security Technology Research and Development
Cyber Security and Information Security
HubBucket Open Source
Open Source Software and Hardware Technology Research and Development
Open Source Software and Open Source Hardware
Open Source Software and Hardware
HubBucket Blockchain and Financial Technology
Blockchain and Financial Technology Research and Development
Financial Technology - FinTech
Blockchain Encryption Technology
Smart Contract Mobile Apps
Blockchian Ledger Technology
HubBucket Analytics and Analysis Technology
Analytics and Analysis Technology Research and Development
Analytics and Analysis Applications
Business Analytics Technology
Business Analysis Technology
HubBucket Big Data Engineering
Big Data Engineering Technology Research and Development
Big Data Technology
Big Data Engineering
Big Data Streaming Technology
HubBucket HealthIT and MedTech
HealthIT and MedTech Technology Research and Development
Healthcare and Science
Medical Imaging Technology
HubBucket Assistive Technology for People with Disabilities
Assistive Technology for People with Disabilities Technology Research and Development
Assistive Technology for People with Disabilities
Assistive Technology for People with Disabilities
HubBucket Back Office and Front Office Technology
Back Office and Front Office Technology Research and Development
Back and Front Office Automation Technology
Back Office Automation Technology
Front Office Automation Technology
HubBucket Team Productivity and Collaboration Technology
Team Productivity and Collaboration Technology Research and Development
Artificial Intelligence - AI Automation Technology for Team Productivity and Collaboration
Team Productivity Technology
HubBucket Technology for Publishers and Authors
Publishers and Authors Technology Research and Development
Technology for Publishers and Authors
Technology for Publishers and Authors
HubBucket Government IT Projects
Public Information Technology - IT Projects
Government Information Technology - IT Projects
HubBucket, Inc. is a privately-held, U.S. based, technol0ogy research and development - R&D corporation. HubBucket, Inc. is an African American (Minority) and United States Navy - USN, Intelligence Community, Cryptology Veteran founded and owned corporation, located in Brooklyn, New York.
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