Whitepapers

Leveraging Human-in-the-Loop AI Systems to Enforce Anti-Money Laundering in Banks & Other Financial Institutions

In this whitepaper the author establishes how these advanced human-AI systems reduce false positives, enhance accuracy, and adapt to evolving threats, providing a robust framework for detecting illicit activities while ensuring regulatory compliance.

Competitive Trends in Laptop Sales Online – Back-to-School Season 2024

C5i Compete’s Digital Shelf Analytics platform uses advanced data engineering and automation capabilities, riding on open-source technologies and frameworks, to deliver automated real-time multi-geography and multi-language reports, delivering insights across the 5Ps – Product, Price, Promotions, Place, and People.

Synthetic Concept Testing: Revolutionizing Product Development with Generative AI

This paper explores the effectiveness of synthetic concept testing, using generative AI (GenAI) and leveraging Microsoft Azure, in consumer goods industries that need rapid innovation and frequent product launches/updates aligned with current consumer needs & preferences.

Leveraging AI in the Complaints Handling Process in a Medical Devices Company

This white paper explores how artificial intelligence (AI) can revolutionize complaints handling processes, offering enhanced efficiency, accuracy, and compliance by integrating AI-driven data analysis, natural language processing, and machine learning with established Quality Management Systems.

AI and Sustainability: Harnessing Artificial Intelligence for a More Environmentally Friendly Future

Climate change and environmental degradation represent two of the gravest challenges confronting humanity in the 21st century. This white paper delves into the transformative power of Artificial Intelligence (AI) as a catalyst for environmental sustainability.

DSPy: A Framework for Programming with LLMs

Read how the author showcases how DSPy revolutionizes LLM programming by offering a declarative Python framework with automated prompt optimization and adaptable pipeline compilation, contrasting manual prompting approaches and enhancing efficiency and precision in LLM interactions. DSPy’s modular design streamlines LLM application development, reducing manual effort and ensuring prompt coherence, setting it apart from traditional frameworks like LangChain and general-purpose ones like PyTorch.

Dynamic Pricing Models for The Data-Driven World of Digital Commerce

In this whitepaper, the authors embark on a comprehensive exploration of this transformative journey. They explore the gap between the traditional framework of pricing and discounting strategies and cutting-edge practices demanded by e-commerce marketplaces today.

Winning The Customer Experience (Cx) Battle In Life Sciences: The Role Of AI Automation With MLOps As The Key Enabler

This whitepaper provides Life Sciences leaders with critical insights on transforming Customer Experience (CX) through Machine Learning Operations (MLOps).

Data Observability

Data Observability enables real-time monitoring and understanding of a data system’s behavior and performance, looking at aggregated metrics and insights about the data system and its processes to identify issues, patterns, trends, and causes to eliminate or quickly resolve malfunction.

Connected Intelligence – Supply Chain: A Force Multiplier

The author of this paper defines the fundamentals of a connected supply chain and the challenges for adoption and implementation. He goes on to illustrate the objectives and approaches to deploying a connected intelligence framework and generating business value. The author also advocates the integration of AI-powered platforms for streamlining functions within the supply chain and optimizing operations.

7 Facets of the Modernization of Insights in Enterprises

The authors of this paper define a robust framework for continuous modernization of the Insights function. They explain why Insights organizations need to begin with a North Star goal and clear strategy aligned to business goals and what aspects across technology, people, and process they need to address to power the organization’s business goals continuously.

CNN+BERT for Video Recognition

Traditionally, for video-based Action Recognition task, 3D CNN are used to extract temporal information and Temporal Global Average (TGAP) layer to summarize this information. In this work, we replace the TGAP layer with the attention mechanism of BERT as it has been state-of-the-art for many sequence-based tasks. BERT’s bidirectional attention mechanism gets a better representation of Temporal information with respect to TGAP.

Industry : Technology

How to use Reinforcement Learning to Valuate Textual Data

Having an accurate dataset is a very important aspect for training neural networks. A model trained on corrupted and faulty data may result in poor performance and getting a clean dataset is not always possible.

Industry : Technology

How to Design a Sustainably Accurate and Fast Model for Text Classification Tasks

Text classification is a common problem in natural language processing, and its task is to assign a pre-defined category to a given text sequence. The key step in solving it is to learn the text representation. Mainly, there are two solutions: to use a pre-trained model or not …

Industry : Technology

Video Ontology: Applying Deep Learning for Video Understanding

The past decade has seen rapid advancements in the area of computer vision, with deep neural networks, particularly convolutional neural networks (CNNs), achieving remarkable results in multiple areas of image processing. The breakthrough success of deep learning for images has sparked more recent…

Industry : Others

Building a Data-Driven Culture With AI-powered Insights for All

Organizations have been investing in Analytics and Business Intelligence (BI) for many years now. However, a common problem they are facing is that they are still trying to solve business problems on an ad-hoc basis. For instance, when a senior executive asks his BI analyst the reason behind the drop in sales, the analyst goes back, builds a regression model and then presents the top two factors that influenced the drop.

Industry : Technology

Data Lakes: Four Things To Consider for Future Scalability

Data is growing in volume, speed and in types. This is creating challenges for storing data and using it when required. To overcome this challenge, organizations are embarking on data lake journeys.

Industry : Technology

Brand Tracking With Digital Data

As digital media data analytics and allied digital cognitive capabilities evolve, brand tracking goes live – straight from the consumer’s consciousness. Social data, combined with Web Analytics data and customer data available to an organization, provides compelling snapshot of consumer opinion, experience, and engagement with a brand.

Industry : Technology

Deep Learning in Autonomous Cars

Technology has seen plenty of advancements over the decades, with cars nowadays being equipped with several sensors such as LIDAR, cameras, radars and more, with different technologies being adopted in the car…