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AI

Predictions for the Dawning AI Age: What to Expect in 2024 and Beyond

2024 is going to be an important transition year for artificial intelligence. 2023 was the public debut of generative AI and large language models (LLMs), a year of amazement, excitement, occasional panic and, yes, more than a little bit of hype. The year ahead is when businesses begin to make the promise of advanced artificial intelligence real, and we’ll begin seeing the effects on how we work and live.

It's Midnight. Do You Know Which AI/ML Uses Cases Are Producing ROI?

In one of our recent blog posts, about six key predictions for Enterprise AI in 2024, we noted that while businesses will know which use cases they want to test, they likely won’t know which ones will deliver ROI against their AI and ML investments. That’s problematic, because in our first survey this year, we found that 57% of respondents’ boards expect a double-digit increase in revenue from AI/ML investments in the coming fiscal year, while 37% expect a single-digit increase.

Unlocking the Power of LLMs | From Introduction to Enterprise Deployment #ai #llm

In today's rapidly evolving digital landscape, Large Language Models (LLMs) and Generative AI are emerging as transformative tools for enterprises. These innovations are not only changing how we interact with data but are also reshaping the very fabric of business operations. Unlike other public LLMs, what happens in your organization stays in your organization. But with great power comes great responsibility—and the need for in-depth understanding.

Testing Strategies for Generative AI Applications | Sumit Mundhada | #TestFlix 2023 #GenerativeAI

In this enlightening session, Sumit Mundhada explores the dynamic landscape of Generative AI applications, a powerful technology with immense potential across various business domains. With the rise of Largest Language Models (LLM), numerous innovative applications are emerging, presenting both opportunities and challenges. As businesses embrace this cutting-edge technology, it becomes imperative to understand the development process and implement effective testing strategies to ensure accuracy and an optimal customer experience.

API Generation vs. ELT/ETL | Key Differences

Organizations often grapple with the choice between two distinct but equally vital technologies: API generation and ELT (Extract, Load, Transform) solutions. While both serve as essential tools, they stand at opposite ends of the data management spectrum. API generation focuses on facilitating real-time data access and dynamic communication between software applications, whereas ELT specializes in the consolidation, transformation, and preparation of data for analytics.

Implications of the AI Executive Order for Government Procurement Systems

Artificial intelligence holds the potential to enhance efficiency, streamline processes, and improve decision-making across various government sectors. But without robust safeguards, there is a heightened risk of biased decision-making, privacy breaches, and misuse of sensitive data. The Biden administration’s AI executive order establishes new standards for AI safety and security as well as for responsible use of AI at federal agencies and in state and local governments.

The rise of AI in software testing: trends

AI growing relevance in software testing has garnered substantial attention in today's software industry. While incorporating AI and ML approaches into software testing is not required, it is worthwhile to explore and study how these methods may deliver valuable benefits in specific elements of the testing process. With the incorporation of artificial intelligence (AI) techniques software testing will undergo a transformational transition.