Systems | Development | Analytics | API | Testing

March 2024

Generative AI in Call Centers: How to Transform and Scale Superior Customer Experience

Customer care organizations are facing the disruptions of an AI-enabled future, and gen AI is already impacting customer care organizations across use cases like agent co-pilots, summarizing calls and deriving insights, creating chatbots and more. In this blog post, we dive deep into these use cases and their business and operational impact. Then we show a demo of a call center app based on gen AI that you can follow along.

Special Episode: Fivetran and Databricks CEOs reveal the secret to AI

George Fraser, CEO and co-founder of Fivetran, and Ali Ghodsi, CEO and co-founder of Databricks, are building products that power the modern data stack. They offer an insider’s perspective on the hardest parts of building and deploying generative AI in the enterprise.

Episode 5: Data democratization and readiness for AI | Powell Industries

The key to breaking down data silos and fostering innovation goes well beyond having the right technology. It’s the people and processes that truly drive change. Ajay Bidani, Data and Insights Manager at Powell Industries, shares his perspective on how a strong, inclusive data culture is fueling the manufacturer’s global success.

AI in Software Testing: Transforming the Way We Deliver Quality Software

The software testing landscape, while crucial for ensuring application quality, has grappled with limitations in traditional methods for decades. This article explores how Artificial Intelligence (AI) is emerging as a game-changer, addressing these challenges and augmenting the capabilities of testers. By combining advanced machine learning, deep learning, natural language processing, and other techniques, AI offers a powerful toolkit to propel software testing into a new era.

Data Architecture and Strategy in the AI Era

At a time when AI is exploding in popularity and finding its way into nearly every facet of business operations, data has arguably never been more valuable. More recently, that value has been made clear by the emergence of AI-powered technologies like generative AI (GenAI) and the use of Large Language Models (LLMs).

Connecting Space and Data: NASA's Asteroid Dust Quest and AI Innovation

Perhaps it's the awe-inspiring films about space exploration (my personal favorite – Apollo 13) that evoke the image of NASA as a place buzzing with activity, filled with screens displaying data, charts, and ALWAYS a big countdown clock. However, one of NASA's most recent challenges may surprise you - the task of cracking open a billion-dollar canister filled with ancient asteroid dust.

LLM Validation & Evaluation MLOps Live #27 with Tasq.ai

In this session, Yaron Haviv, CTO Iguazio was joined by Ehud Barnea, PHD, Head of AI at Tasq.ai and Guy Lecker ML Engineering Team Lead, Iguazio to discuss how to validate, evaluate and fine tune an LLM effectively. They shared firsthand tips of how to solve the production hurdle of LLM evaluation, improving LLM performance, eliminating risks, along with a live demo of a fashion chatbot that leverages fine-tuning to significantly improve the model responses.

Don't Get Left Behind in the AI Race: Your Easy Starting Point is Here

The ongoing progress in Artificial Intelligence is constantly expanding the realms of possibility, revolutionizing industries and societies on a global scale. The release of LLMs surged by 136% in 2023 compared to 2022, and this upward trend is projected to continue in 2024. Today, 44% of organizations are experimenting with generative AI, with 10% having already implemented it in operational settings. Companies must act now in order to stay in the AI Race.

Leveraging AI and Analytics in Your Data Privacy Program

In an age of rapid technological transformation, governments are playing regulatory catch-up as they try to keep pace with technological developments and the increasing amount of personal identifiable information (“PII”) generated by our every-day lives. Privacy laws regulating the use of PII continue to strengthen (Gartner estimates that while 10% of the world’s population was covered by comprehensive privacy laws in 2020, by year-end 2024 it will be 75%).

4 Ways Codezero Optimizes AI Dev

Leveraging Codezero can significantly benefit AI developers in building better, larger, and more sophisticated models through its suite of features designed to simplify and secure microservices development. By addressing common challenges in AI model development, such as environment consistency, collaboration, scalability, and security, Codezero provides a conducive environment for innovation and efficiency. Here’s how AI developers can harness Codezero for these advantages.

How to Improve Customer Experience with AI: 3 Strategies for Success

In today's hyperconnected world, where negative reviews on social media can wreak havoc on a company’s reputation, delivering an exceptional customer experience isn't just a luxury—it's a business imperative. Companies are locked in a fierce battle for customers that is primarily based on their ability to deliver outstanding customer experiences (CX). According to research by The Conference Board, 65% of CEOs globally prioritize investing in strategies to improve CX.

Snowflake Brings Gen AI to Images, Video and More With Multimodal Language Models from Reka in Snowflake Cortex

Snowflake is committed to helping our customers unlock the power of artificial intelligence (AI) to drive better decisions, improve productivity and reach more customers using all types of data. Large Language Models (LLMs) are a critical component of generative AI applications, and multimodal models are an exciting category that allows users to go beyond text and incorporate images and video into their prompts to get a better understanding of the context and meaning of the data.

Predicting the Generative AI Revolution Requires Learning From Our Past

Having frequently worked with governments around the world over the course of my career, I’ve had all kinds of discussions about the global impact of generative AI. Today, I’m publicly wading into those waters to deliver my perspective, and my opinion is that … it’s incredibly hard to predict the future. Done. Wrapped up this entire post in a single sentence.

6 Ways Qlik Can Improve Databricks Performance and AI Initiatives

Data engineers and architects are being asked to do more with their enterprise data than ever before. Yet, the knowledge gap between what businesses want to do with data and how they can accomplish it is growing daily—especially considering today's AI hype cycle. With all that noise in the market, it's easy to see how organizations struggle to keep pace with innovation.

Open Source Fractional GPUs for Everyone, Now Available from ClearML

If you’ve been following our news, you know we just announced free fractional GPU capabilities for open source users, enabling multi-tenancy for NVIDIA GPUs and allowing users to optimize their GPU utilization to support multiple AI workloads as part of our open source and free tier offering.

Why a Solid Data Foundation Is the Key to Successful Gen AI

Think back just a few years ago when most enterprises were either planning or just getting started on their cloud journeys. The pandemic hit and, virtually overnight, the need to radically change ways of working pushed those cloud journeys into overdrive. Cost-effective adaptability was essential. And the companies that could scale up or scale down quickly were the ones that navigated the pandemic successfully. Migrating to the cloud made that possible.

AI in Banking: 5 Impacts Artificial Intelligence Will Have on the Industry by 2025

The potential impact of AI in banking appears boundless. A 2023 McKinsey report found that effectively incorporating generative AI tools into business operations could lead to annual operational savings ranging from $200 billion to $340 billion for the global financial services industry. These cutting-edge technologies can also enhance customer satisfaction, attract more potential customers, and improve employee experience.

What Can AI Do for Business? 5 AI-Centric Benefits

In just a few months, enterprise AI has rapidly evolved into a strategic partner for organizations that want to stay ahead of the disruption curve. Whether enterprises are leveraging predictive analytics for strategic decision-making, using machine learning algorithms for supply chain optimization, or applying generative AI and large language models to enhance customer service, it’s clear AI will help business in many ways.

Why You Need GPU as a Service for GenAI

GPU as a Service (GPUaaS) serves as a cost-effective solution for organizations who need more GPUs for their ML and gen AI operations. By optimizing the use of existing resources, GPUaaS allows organizations to build and deploy their applications, without waiting for new hardware. In this blog post, we explain how GPUaaS as a service works, how it can close the GPU shortage gap, when to use GPUaaS and how it fits with gen AI.

Watch now: Generative AI automatically heals tests in Rainforest

We consistently hear from engineering leaders that automated test maintenance is a painful, mindless exercise that takes too much time away shipping code — the main goal of any startup software team. Our vision is to deliver end-to-end test automation that requires no maintenance from your team. With that in mind, we’ve designed Rainforest as an intuitive, no-code platform that anyone can quickly use with no training. This has been an important — but insufficient! — step.

5 Benefits of Applying AI to Public Sector Processes: Lessons from Parks and Recreation's Pawnee

The business of governance is not easy. Public sector organizations face a range of obstacles from corruption to lack of transparency to red tape—obstacles that have the potential to erode public trust in institutions and hinder economic development. That’s probably why, in virtually every country around the world, popular culture lampoons the intricacies of government bureaucracy.

The State of AI Infrastructure at Scale 2024

In our latest research, conducted this year with AIIA and FuriosaAI, we wanted to know more about global AI Infrastructure plans, including respondents’: 1) Compute infrastructure growth plans 2) Current scheduling and compute solutions experience, and 3) Model and AI framework use and plans for 2024. Read on to dive into key findings! Download the survey report now →

Will AI take over software testing jobs? Human impact and why you shouldn't panic

When ChatGPT first hit the market its human-like responses were astonishing, yet somewhat eerie. Many thought, “It communicates just like me.” It follows that the next logical thought was, “It’s going to take over my job.” However, the fear that AI-driven tools will replace human software testers is unfounded. AI will certainly impact testing jobs, including market expectations, skillsets, and required knowledge.

7 Capabilities to Look for in Low-Code AI Tools

Artificial intelligence (AI) can transform the way your enterprise does business—but if you can’t quickly implement AI in your business processes, you’ll just as quickly fall behind competitors. This is where low-code AI tools can help. Over the past decade, low-code platforms have enabled software engineers, professional developers, and employees with minimal coding experience to build new digital, automated solutions using drag-and-drop interfaces.

How Financial Services and Retail Companies Are Accelerating their Data, Apps and AI Strategy in the Data Cloud

Last year, we held our first Accelerate event, to explore industry trends, data and technology innovations, and data strategy case studies in financial services. This year, we are expanding to five industry events, featuring leaders in financial services; retail and consumer goods; manufacturing; media, advertising and entertainment; and healthcare and life sciences. Accelerate Financial Services and Accelerate Retail are one-day virtual events brought to you by Microsoft.

AI and RAG with Gemma, Ollama, and Logi Symphony

Local LLMs are becoming mainstream with sites like HuggingFace promoting open sharing of trained LLMs. These LLMs are often very small but still extremely accurate, especially for domain-specific tasks like medicine, finance, law, and others. Gemma is a multi-purpose LLM and, while small, is competitive and accurate. Local LLMs also have the advantage of being completely run inside your own environment.

Navigating AI-Driven Claims Processing

95% of insurers are currently accelerating their digital transformation with AI-driven claims processing. Traditionally, this process involved manual steps such as claim initiation, data entry, validation, decision-making, and payout, consuming significant time and resources. However, the introduction of AI has replaced tedious manual work, enabling companies to streamline their tasks efficiently.

Establishing A Robust Data Foundation To Maximize The Benefits Of Gen AI

Newly appointed Snowflake CEO Sridhar Ramaswamy joins Snowflake's Director of Engineering Mona Attariyan and "Data Cloud Now" anchor Ryan Green to discuss the need for organizations to prepare themselves to take full advantage of Gen AI by implementing a carefully developed data strategy that eliminates data silos and promotes data sharing while protecting data privacy.

How Financial Services Should Prepare for Generative AI

It’s no surprise that ever since ChatGPT’s broader predictive capabilities were made available to the public in November 2022, the sprawl of stakeholder capitalization on large language models (LLMs) has permeated nearly every sector of modern industry, accompanied or exacerbated by collective fascination. Financial services is no exception. But what might this transformation look like, from practical applications to potential risks?

What is RAG? Retrieval-Augmented Generation for AI

Retrieval-augmented generation (RAG) is an AI framework and powerful approach in NLP (Natural Language Processing) where generative AI models are enhanced with external knowledge sources and retrieval-based mechanisms. These appended pieces of outside knowledge provide the model with accurate, up-to-date information that supplements the LLM’s existing internal representation of information. As the name suggests, RAG models have a retrieval component and a generation component.

Gen AI for Customer Service Demo

Iguazio would like to introduce two practical demonstrations showcasing our call center analysis tool and our innovative GenAI assistant. These demos illustrate how our GenAI assistant supports call center agents with real-time advice and recommendations during customer calls. This technology aims to improve customer interactions and boost call center efficiency. We're eager to share how our solutions can transform call center operations.

Harness Generative AI in Your Processes with the Prompt Builder AI Skill

Over the past year, interest in artificial intelligence has surged due to the proliferation of generative AI and large language models. These tools captured imaginations, demonstrating a technology brimming with possibility. While many focused on the potential of these tools, some companies made AI practical. For example, last year, Appian released packaged AI tools for processing content at scale and quickly building interface forms.

How Apps Bring Gen AI & LLMs To Life

In this conversation with Snowflake's Christian Kleinerman, Amanda Kelly, and Adrien Treuille, "Data Cloud Now" anchor Ryan Green discusses the origins of Streamlit, its exponential growth as an application development tool since being acquired by Snowflake, and the important role it is playing in the development of machine learning models across all industries. This wide-ranging conversation also explores the ways Gen AI and LLMs will transform the application development process and touches on the role the Open Source community will play in that transformation.

Gen AI And LLMs Will Transform The Enterprise

Snowflake's Mona Attariyan, Director of Engineering, leads this conversation with Snowflake's Sunny Bedi, CIO and CDO, and Jennifer Belissent, Principal Data Strategist, about the impact Gen AI and LLMs will have on enterprises. Topics covered range from the impact on employee productivity, the personalization of the customer experience, the opportunities for data monetization. and more.

Snowflake Ventures Invests in Landing AI, Boosting Visual AI in the Data Cloud

As Large Language Models are revolutionizing natural language prompts, Large Vision Models (LVMs) represent another new, exciting frontier for AI. An estimated 90% of the world’s data is unstructured, much of it in the form of visual content such as images and videos. Insights from analyzing this visual data can open up powerful new use cases that significantly boost productivity and efficiency, but enterprises need sophisticated computer vision technologies to achieve this.

Gen AI And LLMs Will Change Our Lives Profoundly

How will Gen AI and LLMs impact the nature of people's jobs and worker productivity? "Data Cloud Now" anchor Ryan Green kicked off the Data and AI Predictions 2024 event in January by discussing that topic with Snowflake's CEO Sridhar Ramaswamy and Mona Attariyan, Director of Engineering. The conversation also covers the potential for AI to generate misinformation and the need to establish ethical guardrails for the technology.