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Articles by Iris Zarecki
The Real Bottleneck in Enterprise GenAI Isn’t the Model - It’s the Data Architecture
GenAI adoption is accelerating — but production deployments remain difficult. A recent survey of 300 senior IT and data leaders shows why: the biggest obstacle isn’t the model. It’s enterprise data architecture. Let’s break down what the research revealed — and what it means for building GenAI systems on AWS. The Shift: From Experiments to Production Enterprise GenAI is moving out of experimentation.
Why your GenAI pilot succeeds, but your production deployment fails - and what to do about it
If you’ve built a GenAI pilot that works, you’re already ahead of most teams. The demo answers questions correctly. Latency feels acceptable. The model seems “smart enough.” Then you try to ship it to production - and everything starts to fall apart. Responses slow down. Answers become inconsistent or flat-out wrong. Costs spike. Security and governance suddenly matter. And the trust you had during the pilot evaporates. This isn’t because your LLM suddenly got worse.
Beyond RPA, Chatbots, and Assistants
Automation in contact centers has come a long way. It began with basic macros and rule-based scripts designed to streamline repetitive tasks like data entry or case routing. Then came robotic process automation (RPA), which mimicked human actions within digital systems: copying and pasting information, logging into applications, and executing structured workflows. RPA was a major step forward, delivering tangible gains in efficiency, cost reduction, and consistency.
Protecting sensitive financial information in the age of gen AI
Artificial intelligence (AI) has become a game-changer for banks and financial institutions. Generative artificial intelligence (gen AI) and large language models (LLMs) offer immense potential for analyzing vast datasets, automating complex tasks and enhancing customer experience through personalization and efficiency. However, these advancements introduce substantial AI data privacy risks that cannot be overlooked.
Enterprise data is at the crux of the biggest challenges for GenAI deployment
A recent survey from K2view, the generative data product company, examines the top challenges enterprises are facing as they work toward generative AI (GenAI) implementation. The report unveils the most significant roadblocks to realizing GenAI’s full potential lie in organizations’ existing data infrastructure, particularly in the areas of data accessibility and latency, data privacy, and security.
K2view Announces AI Data Fusion, Market-First Solution for Grounding GenAI Apps with Enterprise Data
K2view Announces AI Data Fusion, Market-First Solution for Grounding GenAI Apps with Enterprise Data K2view AI Data Fusion augments LLMs with real-time operational data to grow sales and customer intimacy, while minimizing GenAI hallucinations Augmenting LLMs with real-time enterprise data enables organizations to grow sales and customer loyalty, while minimizing GenAI hallucinations.” — Ronen Schwartz, K2view CEO PALO ALTO, CALIFORNIA, UNITED STATES, March 11, 2024 /EINPresswire.com/ --...
The “Glitch” - Is It Really the Culprit Behind IT Outages?
Credit: ID 135942749 © Anton Yeroma | Dreamstime.com When things go wrong, responsible people step up to the plate and take – responsibility. Unfortunately, there aren't that many responsible people in this world, which is why, when things go wrong, most people look for someone or something to blame. In other words - a scapegoat. Tech has not escaped this phenomenon. When banking apps and websites go down, when airlines cancel flights, the go-to excuse is often a technical glitch.
Why There Are IT Outages – And What to Do About Them? - Dataconomy
What do fat fingers, power failures, and Godzilla have in common? Answer: They have all been responsible for IT outages that, even if they aren’t caused by Godzilla, can cause monster-sized budget holes for companies. How monster-sized? A Rand Organization report says that according to 98% of organizations, IT outages cost them a whopping $100,000 an hour. And those outages are practically guaranteed, according to a University of Chicago study.
Artificial Intelligence Predictions for the year 2019
Artificial Intelligence is dominating innovation in companies across the globe- doesn’t matter if they are giant conglomerates or young startups. According to a report by Research and Markets titled Artificial Intelligence Market by Technology, and Industry Vertical – Global Opportunity Analysis and Industry Forecast, 2018-2025, the global Artificial Intelligence market size is expected to reach $169,411.8 million in 2025, from $4,065 million in 2016 growing at a CAGR of 55.6% from 2018 to 2025.
INFOGRAPHIC: How Netflix Uses Big Data to Drive Success
Anyone with a Netflix subscription understands the process of finding a movie or TV show to watch. You go to the website and see the shows that you recently watched, some shows that are recommended and maybe a few show ratings. Each Netflix user has his or her unique set of options with Netflix, putting a lot of effort into ensuring you find something to watch quickly. If you don’t find something immediately, you might leave the website and look on YouTube instead.
Algorithms will out-perform Doctors in just 10 years time
The power of Algorithms to calculate, contemplate and anticipate the needs of patients is improving rapidly and still has no sign of slowing down. Everything from patient diagnosis to therapy selection will soon be moving at exponential rates. Does that mean the end of doctors? Not quite. To better understand technology’s ever-growing role in healthcare, we first have to better examine the potential of tools and timelines that we are working with.
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