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Blog Posts (46)

  • Our secret to building winning teams

    What's our secret to winning IBM's Build-A-Bot Challenge? It's the same as our secret to providing the solutions and high-level of leadership that clients have come to expect from such a small (but growing) firm: a real, tangible, company-empowered growth mindset. While many companies like to list employee growth and development as a bullet point in a list of values, Cedrus delivers on the promise to a depth that I haven't seen from anyone else. I'm relatively new to Cedrus, but I can already see the results of this mindset manifesting in all aspects of the company and how we stand out to our customers. I was told in my first interview that Cedrus cares less about what specific tools and technologies I know how to work with, and more about my capability to learn new things and contribute as part of a team, since new techniques can easily be learned, but one's ability to grow and be a value-adding collaborator are much harder to cultivate. Then, they back this mindset up with an encouragement to go learn whatever we feel is necessary to succeed and grow. Essentially: Take whatever time you need for learning Just don't bill the client for this time Feel free to expense any learning-related costs But we ask that you run it past management first if the cost will be significant And this goes into effect on day 1: I expensed some courses within my first week. Meanwhile, other companies impose limits, like requiring someone to be employed with the company for a year before any training expenses would be approved or annual spending caps that wouldn't be high enough for a conference or a certification. Further, this mindset extends far beyond structured or conventional training: Want to read some research papers? Please do! Wanna form a team to enter a hackathon? How can we help? The company realizes that self-directed, independent learning is crucial to not only growing someone's skills, but also keeping them engaged in their work, looking for ways to reward and empower people who go out of their way to better themselves since it betters the company at the same time. So when a coworker suggested that we form a team to enter the Build-A-Bot Challenge (with only about 2 weeks remaining), we didn't have to stress out about keeping this side-project secret; we knew that the company would support us in our efforts. Besides the intangible peace of mind, we also were able to do things like: poll our department for feedback on our solution idea, call out work on the project as part of our workload in status update meetings, and even post our submission video on our company YouTube channel. That's all well and good, but how does a project like this help Cedrus' clients? This IBM hackathon facilitated a level of knowledge transfer, experience building, and design thinking that could not be replicated through other means, and all in a short amount of time and at no additional cost. Together our team went through the entire development lifecycle, from architecting a solution, to planning sprints, developing a prototype, iterating the user experience, and deployment. While many of my team members have been through their fair share of full lifecycles, each time through is a learning opportunity, and I was able to learn so much from each of their strengths this time through, leaving me much better equipped to serve our clients and deliver solutions. And this hackathon isn't a rare occurrence; Cedrus also invests in R&D to ensure our consultants are well versed, knowing when cutting-edge research is the right solution for our customers' needs. Cedrus delivers growth for our clients by growing people who like to grow.

  • Audio data with deep learning - the next frontier

    Introduction Artificial intelligence (AI) has become an inherent part of our lives and machine learning is driving to solve new problems every day. With the recent advancements in deep learning, most AI practitioners agree that AI's impact is exponentially expanding year after year. This, of course, has been with the help of big data and unstructured data. These two types of data are not synonymous. Big data can be structured or unstructured and has three characteristics - volume, velocity (speed with which it arrives) and variety (different types like pictures, videos etc.) in data. Unstructured data, on the other hand, refers to data that is not organized or repetitive and is oftentimes large in volume and velocity and thus can be synonymously referred to as big data. Two well-known examples of unstructured data are images and text. Image data is used to solve complex computer vision problems such as facial recognition and autonomous cars. Text data, on the other hand, is used to solve Natural Language Processing (NLP) problems such as understanding spoken language or translating from one language to another (refer to our NLP blog here). Because of its applications, image and text data have received a lot of attention. Along with images and text, there's a third type of unstructured data - audio data. Audio data is less well known, and we'll be diving into it in this writing. This type of data comes in the form of audio files (.wav, .mp3 etc.) or streaming audio. Most applications of audio data are in the music domain in the form of music cataloging or lyric generation. Complexity of audio data has limited it from finding mainstream applications. This has changed with the rapid development in the field of deep learning. Audio data applications Audio data is used to build AI models that perform automatic speech recognition (ASR). ASR solves problems such as understanding what is said to a voice assistant such as Alexa or Siri or converting speech to text for applications such as voice bots and automatic medical transcription. In addition to ASR, audio data is also used to solve problems such as speaker detection, speaker verification and speaker diarization. Applications of speaker detection include Alexa’s ability to change responses based on who is speaking or identifying speakers in a live-streaming audio or video. An application of speaker verification is biometric security. Speaker diarization refers to separating audio to identify who is speaking “what” and “when”. A common application of speaker diarization is transcribing meeting recordings or phone conversations by speaker. As this technology ripens, many more applications are possible that would be based on conversations between people e.g., automatic test result generation for school verbal tests, mental health diagnosis based on conversations. Features of audio data Unlike text and image data, audio data has hidden characteristics in its signal which tend to be more difficult to mine. Most audio data available today is digitized. The digitization process stores audio signals by sampling them. The sampling rate varies by the type of media. For example, CD quality audio uses a sampling rate of 44,100. This means that audio data is sampled 44,100 times in a second and stored in a digital format. Each sample value represents the intensity or amplitude of the sound signal. This sampled data can be processed further to extract features depending on what kind of analysis is required. Spectral features that are based on the frequency domain are probably the most useful. Examples of such features and their applications are as follows (there are many more): 1. Mel Frequency Cepstral Coefficients (MFCC) - represents the envelope of time power spectrum which represent sounds made by a human vocal tract 2. Zero crossing rate – used to detect percussive sounds and a good feature for classifying musical genres 3. Average Energy – can represent formants which uniquely identify a human voice 4. Spectral entropy – used to detect silence A speech model will extract the above features depending on the application and use them in a supervised or unsupervised machine learning model or in a deep learning model. Models for speaker detection, verification and speaker diarization Models for speaker detection and speaker verification are classification problems. For speaker detection, audio features must be extracted for each speaker. The audio feature data can be fed to a neural network which can then be trained. Models for speaker diarization have historically been unsupervised clustering problems but newer models are based on neural networks. Speech model performance Performance of speech models have yet to overcome the following challenges: (1) poor accuracy in recordings of people of the same gender or of people with different accents (2) poor accuracy of speech to text due to language complexities and (3) inability to deal with background noises. The first challenge can be overcome with more training data. New methodologies in bringing together acoustic data and text data is addressing the second challenge. Speech denoising (removal of background noise) is another area that requires a lot of noise and quiet speech samples. Overall, one can expect that speech models will perform better with more varied data. This is the case for deep learning models in other areas as well. As building complex deep learning models becomes easier with various frameworks, a majority of the work is in understanding and preparing the data. Conclusion Audio data is coming into prime time along with its cousins – image and text data. The main driver for it has been deep learning. Applications such as voice assistants and voice bots have entered the mainstream due to this technology development. With a broad spectrum of models in the area of ASR, speaker detection, speaker verification and speaker diarization, we can expect a larger array of conversation-based applications. Crossing this frontier will require integrating multiple types of data and preparing them well so that they are ingested by advanced models to produce good predictions. About Cedrus: Cedrus Digital is involved in studying audio and conversation data and provides strategies on how information can be harvested from them. Cedrus Digital provides analytics and data science services to gain visibility into high volume call center inquiries – creating opportunities for process efficiencies and high value Conversational AI call center solutions and supplementation. Chitra Sharathchandra is a Data Scientist who enjoys working on implementable AI solutions related to multiple types of data

  • NLP Introduction - How AI Understands Our Communication Patterns

    Introduction I know like me, as a child, you probably daydreamed about how amazing life would be like to have a walking and talking robot. I used to imagine ordering my robot to make my bed, clean up my room and most definitely do all of my homework! I would have time to spend on the real things that were of much greater importance. Little did I know back then that it is a complicated task to communicate with a machine. Communication is often a two-way process. It is necessary to not only express our thoughts impeccably but to comprehend others’ words without our biases. It is a bonus if we can predict others’ words! It is clear that communication is critical, and to communicate well is a very desirable skill. According to a popular Holmes Report on “The Cost of Poor Communications”, the cost of inadequate communication is staggering for businesses. It is evident that companies that have leaders who are highly effective communicators have relevant business models, higher profits and at least 50% higher returns to shareholders. They constantly seek to learn how they can serve their customers and in turn grow their profits. Diving into The Complexity of Language So, what makes understanding human language so difficult to understand? It is something to ponder over - we humans are certainly not experts at communicating with each other. How can we communicate with a machine? The challenge is attributed to the dynamism of human language. For example, understanding the query intent is a complex process. If we remove all contextual information, then only the key words remain. This can be quite confusing! How would my robot comprehend my direction “Make my bed!”? Does this mean actually hammering wooden boards to construct a bed structure or does it mean to neatly arrange the bedsheets? This illustrates syntactical complexity in human language. We must keep in mind that all human languages have evolved over thousands of years of speech patterns. Language is essentially a fluid, living entity that develops with the needs and situations of communities. If we think about Shakespearean English and the English we speak today, we can easily notice the drastic contrast. According to Grammarly, in Shakespearean times (late 1500s – early 1600), the words bandit, lonely, critic, dauntless, dwindle, elbow, green-eyed (to describe jealousy) and lackluster were created. It is interesting to observe the turbulence during that time – resulting in the creation of new vocabulary. Additionally, the tone, sentiment and mentality of society was very different – all providing a distinctive filter on communication. The Challenge of Human-Machine Understanding As humans we can use our intuitions and communication experiences to understand even if it something not explicitly stated. In contrast, a machine lacks intuition. However, intuition can be developed with the “experience” of a larger corpus. For example, we have sufficient life experiences to understand what a lion is. A computer cannot comprehend what a lion is as an entity or define its attributes. A computer is exceptional at computing the probability of a lion moving as higher than the probability of a piano moving. Regardless of how many layers of natural language methodologies we implement and the quantity of text, it is impossible to recreate human intuition and experience in a machine. Our best approach in converging on the communication gap between human and machine is to represent words relative to other words within a corpus. Natural language processing (NLP) is an umbrella technology encompassing everything from text parsing to complex statistical methods used in deep learning. The aim is to enable communication between a machine and humans. NLP methodologies process human language. NLP allows computers to communicate and comprehend by reading, editing, summarizing text and even generating text. NLP’s Impact on Machine Learning There are many open-source techniques to aid a machine to understand text. Text embedding techniques, such as Word2vec (from Google) and GloVe (from Stanford), provide a general natural language methodology to cultivate an understanding of words, context, sentiment and intent. Words are represented as a dense vector in a highly dimensional sparse matrix. We build a dense vector so that it is similar to vectors of words that appear in similar contexts. Using these vector representations, it is possible to find how different words in a sentence relate to each other and how they relate collectively. The algorithm goes through each position of a word in the text. The word vectors are iteratively adjusted until this probability is maximized. If a word in a sentence is replaced with a word with a comparable vector representation, we can obtain a similar meaning for the sentence. Word2vec performs wonderfully when we have a large corpus. Word2vec training can be improved by eliminating stopwords from the dataset. Stopwords are high frequency words that add little value to language understanding, and their removal aids in improving model accuracy and training time. About Cedrus: If you’d like a guided approach for implementing NLP on your road towards Enterprise-AI, Cedrus Digital specializes in the AI transformation journey for companies of all sizes. Come work with our experts to set you on your path in not only NLP, but Conversational AI, Vision, Predictive Analytics, and Knowledge Graphs as well. We can help you brainstorm& prioritize use cases, as well as help with planning, management, and delivery of AI projects. Let’s partner together. In future blogposts I will dive deeper into the intricacies of text embedding and explore, with some technical rigor, other aspects of NLP required for successful implementation. Businesses have realized that unstructured and semi-structured data need to be mined using NLP rather than rely on outdated manual or template-based techniques. Natural Language Processing is powerful tool that has an immense impact on the business model and serving the customer. Stay tuned! Swati Sharma, Ph.D. is a Senior AI Solutions Engineer at Cedrus Digital. She teaches and mentors future data scientists and works with clients to create solutions for complex business problems.

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  • Customized Digital Transformation | Cedrus Digital | New York

    Line separator DIGITAL TRANSFORMATION SOLUTIONS DONE RIGHT Your company is unique; your technology solutions should be too. Our expert consultants advise and aim to tailor our solutions to your specific business needs with unprecedented speed and agility. Why trust your innovation to anyone else? WHAT WE DO FEATURED PARTNERSHIPS OUR VISION To deliver our customers innovative solutions with unparalleled levels of functionality and sophistication, bridging the present into the future, while bringing unprecedented operational efficiencies into their business. WHO WE ARE 82 % Repeat Customers 164 % Customer base growth over the last 4 years 44 % CAGR for the past 3 years About Cedrus We are a young, imaginative, diverse company, deeply rooted in successfully solving large business problems for the past 25 years. Our employees, partners, and customers share our zeal for excellence. Learn more about what makes us special. MEET CEDRUS Our Expertise We tame cutting-edge technologies to fit your business. Our extensive certifications, internal investments in assets and IP, and our experience from hundreds of transformational projects inform our wisdom as we take on new challenges. OUR EXPERTISE HOW WE'RE DIFFERENT We expertly guide you through discovery and design, architecture and development, and production and support, with an approach perfectly tailored to your unique business needs. Realizing your business' potential has never been easier! Learn about our offerings at no commitment, risk, or cost. WHAT WE DO See us in action! Get to know our work through some real-life examples. Take a look at some use cases, demos, and solutions that others are already implementing . USE CASES Grow with us! WE ARE HIRING! Want to be part of a dynamic, creative team? Want to join a company that will invest in you? Learn more about joining our team. JOIN US OUR PARTNERSHIPS Our close partnerships with some of the industry's top performers will give you the best experience in using their groundbreaking, industry-defining tools and platforms. By keeping an open mind, a scientific curiosity, and an objective outlook, we accommodate and adapt our recommendations to the context of your business. LEARN MORE WHAT WE'RE UP TO NOW Our secret to building winning teams 76 Write a comment 1 Audio data with deep learning - the next frontier 99 Write a comment 2 An Introduction to the World of Knowledge Graphs 235 Write a comment 5 View More WHAT PEOPLE SAY Media and Entertainment Software Provider We were impressed with Cedrus' ability and assets to support us during our Cloud migration. Cedrus is not a typical systems integrator- they understand the underlying business challenge and help resolve it through cutting edge technology practices. Their unparalleled expertise in implementing and deploying APIs/microservices to the Cloud enabled us to quickly and smoothly transition our software offerings to AWS. READY TO GET STARTED ? Get in touch with us! We're thrilled to answer your questions and help you define a vision. Contact Us

  • CONTACT US | Cedrus Digital

    Line separator GET IN TOUCH Want to know more about our offerings, company, and team? Drop us a line! ENGAGE WITH US ! Need an innovative solution? We can help you solve for your specific business opportunities. Cedrus is an unconventional group of people with deep, diverse experience in solving complex business and technical problems where others can't. Let us help you discover and deliver your next big thing! We have the technical chops. Our team is deeply versed in the latest technology, we only execute with the best tools, and we only recommend solutions we've thoroughly vetted. We have tangible experience. We deliver true value. We have delivered in industries from healthcare, to insurance, to finance, to river barge shipping. Bring us your challenge, and we will rise to provide the business-savvy technical solution you need. You will not be able to find better value than our work. Get in contact below! HOW CAN WE HELP? Submit Thanks for submitting, we'll be in touch soon! JOIN THE TEAM ! We are always looking for bright, driven individuals to join our slightly unconventional team. Are you looking to grow and learn in your career? Not afraid to speak your mind when you create? Want to be part of a team of unlike-minded peers? You may just be a great fit! You'll get amazing experience We have numerous clients in diverse lines of business, with expansive projects that will let you flex and expand your expertise. Our office space rocks Cedrus is located in the heart of Manhattan with easy bike access, endless coffee, and community collaboration and gatherings. We will foster your growth Be part of an awesome team Our team has years of mentorship experience. We keep our team members up-to-date with the latest technology, providing resources for learning, a team learning culture, and supporting the acquisition of certifications. We're an unusual mix of people with diverse experience and a can-do attitude. Our team is motivated, hungry to learn, and eager to contribute and take ownership of their work. You will have remote options Team members have the autonomy to work remotely as needed once they are up to speed with their team's needs and rhythms. WE'RE HIRING Check out our job postings on our Linkedin page . ​ ​ Don't see what you're looking for? We're always looking for skilled talent. Reach out to us at

  • CLOUD NATIVE | Cedrus Digital

    CLOUD NATIVE Moving to the Cloud is the cornerstone of Digital Transformation. Building Cloud Native products gives you more flexibility, lowers costs, and is critical for organizations to move at a competitive speed as they grow and scale. We use our knowledge of building Cloud Native products, architectural best practices, and our assets to assist you in your journey to the Cloud. OUR CLOUD PARTNERS OUR PROCESS Our Cloud Native experts have extensive experience in your ongoing, iterative journey to the Cloud. Our process will guide you through the process to Cloud maturity and agile implementation. See Our Offerings OUR WORK With 20+ years of successfully delivering enterprise-grade solutions to some of the world’s largest companies, Cedrus is the perfect partner to tackle the most complex enterprise challenges and guide you through your Cloud journey. Our extensive partnerships and expertise with leading Cloud providers allows us to deliver scalable solutions that span Public, Private, Hybrid, and Multi-Cloud. ​ Your Cloud transition introduces a multitude of new opportunities to improve not only the technology you use, but the way your business operates and solves problems. ​ American Commercial Barge League (ACBL) needed to upgrade from an in-house solution that no longer met their growing logistics and technology needs. Cedrus advised in business and technical capacities to diagnose their most pressing issues. We used our years of experience in similar fields to suggest a custom solution that would help them manage logistics through IoT, and expand and enhance their existing software in future-safe AWS technologies. Now, ACBL has a strong, modern infrastructure with the benefits of improved accuracy, efficiency, and user experience. ​ Take a look at their incredible story below! USE CASES See the incredible benefits of moving to the cloud that we've provided to clients in Healthcare, Shipping, Insurance, Banking, and other industries. Explore More Here CLOUD OFFERINGS Assess Cloud Readiness Assessment CI/CD Readiness Assessment Cloud & Architecture Discovery Workshops Organization Security Assessment Measure and Optimize Infrastructure as Code Quickstart and Implementation Workload and Users Onboarding Automation Implementation Policy as Code Quickstart and Implementation AIOps Assessment and Implementation Cost Optimization Assessment and Implementation Cloud Security Assessment and Remediation Application Security Assessment Performance Assessment Cloud Security Monitoring Assessment and Implementation Multi-Cloud Monitoring Assessment and Implementation Proof and Foundation Design Thinking Workshop Project One MVP Implementation Well-Architected Framework Assessment Landing Zone Implementation CI/CD Pipeline Implementation Backup Migration Data Migration Managed Services Application Maintenance and Management Platform Maintenance and Management Cloud Managed Services Workload and User Onboarding Assessment and Automation Implement Cloud Center of Excellence Platform Automation (IaC) DevSecOps Strategy, Framework, and Toolings Data Migration, Data Lake, and Event-Driven Implementation API Strategy & Lifecycle Implementation Application Migration and Modernization IoT Quickstart and Full Implementation BlockChain Quickstart and Implementation Container Strategy and Implementation Serverless Quickstart and Full Implementation PCF Migration More Resources WANT TO LEARN MORE ? Get in touch with us! We're thrilled to answer your questions and help you define a vision. Contact Us

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