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Krishna Yadappanavar
5 Strategies to Slash Your Observability Bill
High observability costs have emerged as a significant concern for businesses across industries, such as the…
Les Yeamans
Data Streaming’s Importance in AI Applications
Confluent’s annual Current conference held last week in Austin, Texas, like past conferences, included two days…
Elizabeth Wallace
To Build or Not to Build Your Own LLM
Last year, a Forbes article predicted that every business would have its own LLM. Despite what…
Muhammad Muzammil Rawjani
10 Essential Python Libraries for Machine Learning and Data Science
As someone deeply involved in the world of machine learning and data science, I know firsthand…
5 Strategies to Slash Your Observability Bill
Modern tech stacks require a new approach to observability that enables continuous monitoring and optimization of performance metrics. This approach streamlines operations, reduces costs, and improves customer experience by speeding up issue resolution.
Real-time Analytics News for the Week Ending October 5
In this week's real-time analytics news: Accenture and NVIDIA expand an existing partnership to help businesses scale AI adoption.
Unlocking a Competitive Edge in Hedge-fund Trading, Right Down to the Data Specifics
While speed and performance are of utmost importance in Capital Markets, the key to a competitive edge lies in smooth, seamless data movement. As such, a critical requirement for hedge funds is to have a message broker that is robust, reliable, and resilient.
The Rise of Robotics: How AI is Reshaping Robotics in Manufacturing
As robots and their AI-enabled use cases become more frequent on factory floors, manufacturers should deploy these capabilities in a way that strengthens – not hinders – the overall workforce.
Celebrating the Mainframe’s 60th Anniversary: A Pillar of Modern Technology
Solutions that bridge the gap between mainframe and cloud environments allow organizations to take advantage of the strengths of both platforms. By leveraging such solutions, businesses can lower costs, improve agility, and make the most of their cloud investments.
What the Next Generation of AI Solutions for Banking Will Look Like
Smart finance companies will begin their AI transformation efforts by assessing their capabilities and then deciding which AI innovations they are capable of supporting.
Navigating the AI Landscape: Why Multiple LLMs Are Your Best Bet
In a rapidly evolving market, an AI strategy that includes access to a broad range of capabilities and insights from multiple LLMs can be a game-changer.
Vision Transformers Breakthrough Enhances Efficiency
The Visual State Space Duality (VSSD) model, introduced by researchers at City University of Hong Kong and Tianjin University, offers a groundbreaking approach to vision transformers, significantly improving efficiency and performance in computer vision tasks.
Countering Real-Time Frauds and Scams with Modern Streaming Engine Technology
In an era where fraudsters are increasingly adept at exploiting vulnerabilities in real time, traditional fraud detection methods are no longer sufficient. Organizations must adopt modern streaming engine technologies that can process and analyze customer event data in real time, allowing them to detect and prevent fraud as it happens.
Real-time Analytics News for the Week Ending September 28
In this week's real-time analytics news: AI agents and multiple collaborations to tackle the demands of AI.
Supply Chain Excellence: Modernizing Technology for Improved Trading Partner Collaboration
Modernizing the technology used in supply chain processes leads to significant improvements in visibility, efficiency, and compliance, ultimately fostering more vigorous and more collaborative partnerships.
The Top Value Application for AI? Real-time Capabilities
Financial services and healthcare organizations are leading the way with the adoption of AI. And many companies across all industries are building real-time machine-learning applications.
Federated Averaging: The Backbone of Federated Learning
Federated Averaging represents a significant advancement in the use of artificial intelligence in privacy-sensitive applications. By allowing for collaborative model training without direct data sharing, it paves the way for a new era of secure, decentralized machine learning.
How ADAS and Automotive Sensing Are Becoming Essential to Accident Prevention
By leveraging the insights gained from data analysis and the capabilities of emerging technologies, the auto industry can usher in an era where accidents are not just reduced but ultimately prevented, ensuring safer journeys for all.
How Real-time Decisions at the Edge Avoid Critical Latency Problems
Many modern applications must push processing and analysis closer to where data is generated, bypassing traditional centralized models that are often hampered by latency issues.
Data Streaming’s Importance in AI Applications
Confluent's Current conference highlighted the critical role of data streaming in addressing the real-time data needs of AI.
To Build or Not to Build Your Own LLM
Building an LLM can be a strategic play for many organizations. Yet, even with all the benefits of doing so, third-party models still make a lot of sense for some companies.
Harnessing Emerging Technologies: Driving Growth with AI, Intelligent Interoperability, and Quantum Computing
The next frontier in intelligent systems includes systems that are designed to go beyond traditional AI by continuously learning, adapting, and evolving in real-time. These systems have the potential to anticipate disruptions, optimize operations autonomously, and drive innovation in unprecedented ways.
What Does Real-time Mean in Today’s World?
Today, decisions need to be made in milliseconds and need to be made as soon as an event has occurred. Increasingly, there is a need for real-time analytics of data at its source, as it is being generated.
Real-time Analytics News for the Week Ending September 21
In this week's real-time analytics news: The New Jersey Institute of Technology (NJIT) will establish the Grace Hopper AI Research Institute to advance the university’s expertise in AI.
Smart Talk Episode 7: Cardinality, Control and Costs in Observability
Cardinality, control, and costs are the three Cs of understanding and managing observability data as Krishna Yadappanavar, CEO of Kloudfuse explains with Smart Talk’s host, Dinesh Chandrasekhar, founder and principal analyst of Stratola.
Beyond the Euphoria: Responsible Use of GenAI
The responsible use of GenAI is not merely a choice; it is an imperative. In the absence of clear regulatory guidelines, businesses should develop a discerning understanding of when to harness their power and, equally crucially, when to exercise restraint.
We’re Not Ready for AI-Driven Factories, Just Yet
Before plant managers implement an AI-driven approach, they must take a number of steps starting with meeting the infrastructure needs of AI.
With AI, It’s a Complex Future for Cybersecurity
The future of cybersecurity will be defined by new threats emerging from AI and machine learning and evolving cloud vulnerabilities. As such, organizations will need to focus on Zero Trust and supply chain security to remain agile, proactive, and resilient.
Cloud Computing is Ready for AI, Is Your Data?
The ability for companies to benefit from the convergence of cloud computing and generative AI will hinge upon putting both technologies to work on their data.