The Five Step Playbook to Move GenAI into Production

In this contributed article, Josh Reini, Developer Relations Data Scientist, TruEra, discusses how gaining the required confidence to deploy GenAI apps at scale can be challenging, and structured evaluation has gained recognition as a key requirement on the path from science experiment to customer value. Evaluation frameworks can play a critical role in this journey by allowing developers to run experiments faster and gain systematic validation for production readiness. Connecting such an evaluation framework with a scaled observability platform brings confidence in production. This article explores five practical steps to move LLM applications from early prototypes to scaled, production applications.

Video Highlights: NumPy, SciPy and the Economics of Open-Source — with Dr. Travis Oliphant

In this video presentation, our good friend Jon Krohn, Co-Founder and Chief Data Scientist at the machine learning company Nebula, explores the origins of NumPy and SciPy with their creator, Dr. Travis Oliphant. Dr. Oliphant shares his journey from personal need to global impact, the challenges overcome, and the future of these essential Python libraries in scientific computing and data science.

Embracing the Agile Data Platform: A Key to Business Survival Today

In this contributed article, Philip Miller, a Customer Success Manager, Senior, for Progress, discusses how embracing an agile data platform, which enables an organization to navigate the complex volume of data effectively, is crucial for survival in today’s data-driven business landscape. In today’s global marketplace, moving from a rigid data management to a dynamic platform allows organizations to extract meaningful insights quickly, which in turn fosters innovation and resilience.

How Optical I/O is Enabling the Future of Generative AI: A Q&A with Ayar Labs CTO Vladimir Stojanovic

As we look at the future of AI and the challenges it faces, who better to provide insights than Vladimir Stojanovic, CTO and co-founder of Ayar Labs. In this Q&A interview, we’ve asked Vladimir a dozen questions about how Ayar Labs’ technology is enabling the growth of generative AI.

Fine-Tune Your LLMs or Face AI Failure

In this contributed artticle, Dr. Muddu Sudhakar, CEO and Co-founder of Aisera, focuses on the downsides of general-purpose Gen AI platforms and why enterprises can derive more value from a fine-tuned model approach.

Video Highlights: The 3 Steps of LLM Training with Lisa Cohen

In this video presentation, our good friend Jon Krohn, Co-Founder and Chief Data Scientist at the machine learning company Nebula, is joined by Lisa Cohen, Google’s Director of Data Science and Engineering, to discuss the capabilities of the cutting-edge Gemini Ultra LLM and how it stands toe-to-toe with GPT-4.

Navigating Cloud Migration: Choosing right Database for Cloud Migration of Your Data

In this contributed article, technical leader Kamala Manju Kesavan believes it is essential to periodically reassess your database strategy to ensure that it continues to meet your organization’s evolving requirements. If migrating to another database solution is deemed necessary, approach the process methodically, leveraging best practices and stakeholder collaboration to maximize success and drive business value.

AI Washing: Unmasking the Illusion

In this contributed article, Maxime Vermeir, Senior Director of AI Strategy at ABBYY, discusses the term “AI Washing” which has emerged as a modern-day mirage, beguiling businesses into pouring resources into AI solutions that, unfortunately, fall short of solving real-world problems. The market is rife with lofty declarations of “innovation” and “Generative AI” utilization, yet they seldom offer a lucid narrative on tangible business outcomes.

Overcoming the Technical and Design Hurdles for Proactive AI Systems

In this contributed article, George Davis, founder and CEO of Frame AI, howlights how we find ourselves at an early, crucial stage in the AI R&D lifecycle. Excitement over AI’s potential is dragging it into commercial development well before reliable engineering practices have been established. Architectural patterns like RAG are essential in moving from theoretical models to deployable solutions.

Using Clinician Big Data to Alleviate a Struggling Workforce

In this contributed article, Charlie Lougheed, CEO and co-founder of Axuall, explains why healthcare needs to adjust its thinking and in what ways clinician big data can make impactful changes throughout the healthcare industry, from credentialing to attrition.