Practical Enterprise AI: Common Roadblocks and How to Avoid Them
Come learn what to keep in mind when implementing AI-powered applications and effective strategies for scalable, practical generative AI.
Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
May 2024
With AI Writing Code, Will AI Replace Software Engineers?
Software developers have plenty to keep them awake at night. Their top concern is no longer how to express the latest algorithm in their favorite language (C, C++, Erlang, Java, etc.). Instead, it’s being replaced by artificial intelligence (AI). Here we take a look at the process for AI writing code and answer the question: Will AI replace programmers? Read along or jump ahead to the section that interests you the most.
5 Ways Advertising, Media and Entertainment Companies are Using Gen AI
The emergence of generative AI (gen AI) heralds a new, groundbreaking era for advertising, media and entertainment. According to a recent Snowflake report, Advertising, Media and Entertainment Data + AI Predictions 2024, gen AI is going to transform the industry — from content creation to customer experience. The companies that will come out ahead during this time are those that most successfully and quickly supercharge their data strategy.
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Testing LLM Backends for Performance with Service Mocking
While incredibly powerful, one of the challenges when building an LLM application (large language model) is dealing with performance implications.
Introducing Cloudera's AI Assistants
In the last couple of years, AI has launched itself to the forefront of technology initiatives across industries. In fact, Gartner predicts the AI software market will grow from $124 billion in 2022 to $297 billion in 2027. As a data platform company, Cloudera has two very clear priorities. First, we need to help customers get AI models based on trusted data into production faster than ever.
GitTogether | GenAI & Open Source | Kunal Deo
The resurgence of Artificial Intelligence (AI) in recent years owes much to a pivotal moment: the publication of a groundbreaking paper by Google. This event underscores the significant role of Open Source in advancing AI technologies. In this presentation, we delve into how Open Source is not just influencing but also shaping the landscape of Generative AI (GenAI). However, our focus extends beyond the traditional dichotomy of Open Source versus proprietary technologies. Instead, we explore the complementary nature of both realms in fostering the development of the AI ecosystem.
What is Intelligent Process Automation? 5 Key Facts
As generative AI grows in popularity and enterprises scramble to embrace new technology in a scalable, compliant way, it can be difficult to know the right path forward. Your enterprise has already invested in automating processes to free up resources and improve organizational efficiency, but is it enough? This is where intelligent process automation comes into play.
Product analytics for generative AI model and media asset companies using BigQuery
Using BigQuery object tables, we analyze unstructured Cloud Storage data with generative AI models and join the results with BigQuery structured data.
Navigating the Enterprise Generative AI Journey: Cloudera's Three Pillars for Success
Generative AI (GenAI) has taken the world by storm, promising to revolutionize industries and transform the way businesses operate. From generating creative content to automating complex tasks, the potential applications of GenAI are vast and exciting. However, implementing GenAI in an enterprise setting comes with its own set of challenges. At Cloudera, we understand the complexities of enterprise GenAI adoption.
Interview with Miguel Jetté, Vice President of AI at Rev
In this latest entry of our fascinating interview series that focuses on major players in the global tech arena, we are delighted to present Miguel Jetté, Vice President of Artificial Intelligence at Rev. Join us as we dive into his career development, provide tips for aspiring AI leaders, and discuss the key lessons he has learned along the way.
The Sliding Doors for Your AI Strategy
I have been having quite a bit of fun in this blog series exploring the “sliding doors” (or divergent paths) that organizations can take with their AI and data initiatives. The right door can lead to great value, as I covered in my previous posts on ESG reporting, data products, and responsible AI.
QonfX 2024 Rewind: Testing, AI, and the Future
We did a sort of time travel on 20th April at QonfX. If you are not one of the 3000+ people who registered for this event, it is a unique software testing conference that keeps its focus on the Future of Testing. This year was the second edition of QonfX and received even more love than the last time. Feedback like the above filled our social feeds during and post QonfX. We cannot keep a count of the number of times attendees used the words ‘eye-opening’ for the talks given by the speakers.
How ClearML Helps Teams Get More out of Slurm
It is a fairly recent trend for companies to amass GPU firepower to build their own AI computing infrastructure and support the growing number of compute requests. Many recent AI tools now enable data scientists to work on data, run experiments, and train models seamlessly with the ability to submit their jobs and monitor their progress. However, for many organizations with mature supercomputing capabilities, Slurm has been the scheduling tool of choice for managing computing clusters.
ClearML Supports Seamless Orchestration and Infrastructure Management for Kubernetes, Slurm, PBS, and Bare Metal
Our early roadmap in 2024 has been largely focused on improving orchestration and compute infrastructure management capabilities. Last month we released a Resource Allocation Policy Management Control Center with a new, streamlined UI to help teams visualize their compute infrastructure and understand which users have access to what resources.
Snowflake Cortex LLM Functions Moves to General Availability with New LLMs, Improved Retrieval and Enhanced AI Safety
Snowflake Cortex is a fully-managed service that enables access to industry-leading large language models (LLMs) is now generally available. You can use these LLMs in select regions directly via LLM Functions on Cortex so you can bring generative AI securely to your governed data. Your team can focus on building AI applications, while we handle model optimization and GPU infrastructure to deliver cost-effective performance.
How Healthcare and Life Sciences Organizations Are Accelerating Data, Apps and AI Strategy in the Data Cloud
Accelerate Healthcare and Life Sciences is a one-day virtual event, featuring technology and business leaders from Elevance Health, Ginkgo Bioworks, Datavant and more, to discover executive priorities, best practices and potential data and AI challenges that are top of mind for 2024.
Observability Meets AI: Unlocking New Frontiers in Data Collection, Analysis, and Predictions
As software systems become increasingly complex, observability — the ability to understand a system's internal state based on its external outputs — has become a critical practice for developers and operations teams. Traditional observability approaches struggle to keep up with the scale and complexity of modern applications. As the amount of telemetry data grows, it becomes expensive and complex to navigate. Enter AI and its promise to revolutionize observability.
Learn to Automate Your Claims Processing I Astera Data Wrap
Discover how Astera's AI-powered document processing solution simplifies claims handling. Learn how to automate data extraction, validation, and scheduling for faster, more efficient claims processing.
Data Accessibility: A Hurdle Before SAP's AI Integration
Unlocking the power of AI within SAP for your team requires overcoming a significant hurdle: data accessibility. SAP data’s complexity, spread across various modules, creates silos of information that your team might struggle to understand and utilize effectively. Inaccessible or misaligned SAP data will hinder your AI system’s ability to learn and deliver valuable results specific to your organization.
Data Prep for AI: Get Your Oracle House in Order
Despite the transformative potential of AI, a large number of finance teams are hesitating, waiting for this emerging technology to mature before investing. According to a recent Gartner report, a staggering 61% of finance organizations haven’t yet adopted AI. Finance has always been considered risk averse, so it is perhaps unsurprising to see that AI adoption in finance significantly lags other departments.
Impact of AI on #SoftwareTesting: Are Testers Ready? | #QonfX 2024
Join industry experts Rahul Verma, Navin Nair, Nagabhushan Ramappa, and our amazing host Balaji Ponnada in an insightful panel discussion on "AI's Impact on Testing, Tester Roles, and Tester Readiness." In this session, the panelists discuss how artificial intelligence (AI) has revolutionized software testing, sharing the complexities and opportunities of AI-driven testing environments. Through real-world examples and interactive discussion, they explore the changing role of testers in the AI era and provide valuable insights into the future of software testing.
Simplifying data modeling and schema generation in BigQuery using multi-modal LLMs
Watch how to use a multimodal LLM such as Gemini to analyze data in a BigQuery data lake and automatically generate schema layouts.
Introducing Choreo Copilot
We're excited to introduce Choreo Copilot (preview), which allows you to interact with Choreo. You can pose questions in natural language and Copilot will provide answers. Choreo Copilot enables you to grasp Choreo concepts, teaches you how to perform tasks in Choreo, and provides guidance when you encounter obstacles. Copilot is familiar with APIs in Choreo’s internal marketplace. Choreo already features an AI capability that enables API testing through natural language.
Artificial Intelligence vs. Intelligent Automation: What's the Difference?
AI injects “intelligence” into automation, enabling systems to execute tasks, comprehend complex data, make informed decisions, and learn from outcomes. Unlike technologies such as robotic process automation (RPA), which follow predetermined rules, AI leverages data to evaluate situations and determine the best course of action. Now that we've explored how AI augments traditional automation tools, let's delve deeper into the realm of intelligent automation.
Get Your AI to Production Faster: Accelerators For ML Projects
One of the worst-kept secrets among data scientists and AI engineers is that no one starts a new project from scratch. In the age of information there are thousands of examples available when starting a new project. As a result, data scientists will often begin a project by developing an understanding of the data and the problem space and will then go out and find an example that is closest to what they are trying to accomplish.
Snowflake's Arctic-TILT: A State-of-the-Art Document Intelligence LLM in a Single A10 GPU
The volume of unstructured data — such as PDFs, images, video and audio files — is surging across enterprises today. Yet documents, which represent a substantial portion of this data and hold significant value, continue to be processed through inefficient and manual methods.
Behind The Scenes Of Snowflake Open Source LLM Arctic
Snowflake CEO Sridhar Ramaswamy and Snowflake Head of AI Baris Gultekin join Adrien Treuille, Director of Product Management, to discuss the launch of Snowflake Arctic, the latest enterprise-grade, truly open large language model (LLM). Snowflake Arctic stands out in the competitive landscape with its exceptional efficiency and cost-effectiveness, emphasizing Snowflake's commitment to open-source development and the future of enterprise AI. Join us to explore how Arctic is set to revolutionize industries by making advanced AI more accessible and trustworthy.
Webinar Replay: The 4 Biggest Challenges of Scaling Cloud-Native AI Workloads
Learn the biggest obstacles with load test automation, and how existing user traffic holds the key to scaling eCommerce software safely, and fast.
Using Moesif, Kong, and Stripe to Monetize Your AI APIs - Part 1: Integrating The Platforms
As the wave of AI sweeps through the technology landscape, many have hopped on board. Interestingly enough, and often overlooked, is that many AI capabilities are served through APIs. Fancy user interfaces integrate with the actual mechanisms where the magic happens: the APIs. So, when generating revenue through AI platforms, the APIs drive the revenue.