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Escaping POC Purgatory: Evaluation-Driven Development for AI Systems

O'Reilly on Data

Most teams approach this like traditional software development but quickly discover it’s a fundamentally different beast. Check out the graph belowsee how excitement for traditional software builds steadily while GenAI starts with a flashy demo and then hits a wall of challenges? Whats worse: Inputs are rarely exactly the same.

Testing 174
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Is SaaS dead? Not quite, but it’s evolving rapidly

CIO Business Intelligence

The rapid advancement of AI has led some to predict the end of software as we know it. The key will be adapting quickly and leveraging AI to create more intelligent, efficient, and personalized software solutions. On the other hand, it may require managing a more diverse and complex software landscape.

ROI 116
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What you need to know about product management for AI

O'Reilly on Data

If you’re already a software product manager (PM), you have a head start on becoming a PM for artificial intelligence (AI) or machine learning (ML). Why AI software development is different. Machine learning adds uncertainty. This shift requires a fundamental change in your software engineering practice.

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Where Web 3.0 is taking the software industry

CIO Business Intelligence

Beyond that basic fact, there is much uncertainty. . What impact will it have on the software industry and world at large? As the trilemma is improved, making blockchain more suitable for typical business use cases, and public blockchains become more robust, we are going to see a significant impact to both software and society.

Software 145
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Easily Build an Optimization App and Empower Your Data

Speaker: Gertjan de Lange

If the last few years have illustrated one thing, it’s that modeling techniques, forecasting strategies, and data optimization are imperative for solving complex business problems and weathering uncertainty. See how an end-user runs the new model from their browser device, with no other software needed.

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Dell cuts jobs amid growing economic uncertainties

CIO Business Intelligence

Trendforce forecasts that starting in 2024, the demand for AI development and software services will significantly increase, alongside the growth of edge computing AI servers using mid-range GPUs and FPGAs. This sector is expected to see an annual growth rate exceeding 20 percent from 2023 to 2026.

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Regulatory uncertainty overshadows gen AI despite pace of adoption

CIO Business Intelligence

It’s no surprise, then, that according to a June KPMG survey, uncertainty about the regulatory environment was the top barrier to implementing gen AI. So here are some of the strategies organizations are using to deploy gen AI in the face of regulatory uncertainty. One option, however, is to use open source software.