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We employed ChatGPT as an ML Engineer. This is what we learned

Towards AI

We test it on a practical problem in a modality of AI in which it was not trained, computer vision, and report the results. A sensible proxy sub-question might then be: Can ChatGPT function as a competent machine learning engineer? ChatGPT’s job as our ML engineer […] improvement in precision and 34.4%

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Explosive growth in AI and ML fuels expertise demand

AI News

According to a recent report by Harnham , a leading data and analytics recruitment agency in the UK, the demand for ML engineering roles has been steadily rising over the past few years. AI and machine learning are reshaping the job landscape, with higher incentives being offered to attract and retain expertise amid talent shortages.

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10 Best AI Tools for Small Manufacturers (February 2025)

Unite.AI

The AI/ML engine built into MachineMetrics analyzes this machine data to detect anomalies and patterns that might indicate emerging problems. MachineMetrics cloud platform can be deployed in minutes by connecting simple IoT devices to machines, automatically tracking metrics like cycle time, downtime, and performance.

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Getting Started with Docker for Machine Learning

Flipboard

Envision yourself as an ML Engineer at one of the world’s largest companies. You make a Machine Learning (ML) pipeline that does everything, from gathering and preparing data to making predictions. Do you think learning computer vision and deep learning has to be time-consuming, overwhelming, and complicated?

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OpenAI Researchers Introduce MLE-bench: A New Benchmark for Measuring How Well AI Agents Perform at Machine Learning Engineering

Marktechpost

Machine Learning (ML) models have shown promising results in various coding tasks, but there remains a gap in effectively benchmarking AI agents’ capabilities in ML engineering. MLE-bench is a novel benchmark aimed at evaluating how well AI agents can perform end-to-end machine learning engineering.

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Falcon 3 models now available in Amazon SageMaker JumpStart

AWS Machine Learning Blog

Clean up To clean up the model and endpoint, use the following code: predictor.delete_model() predictor.delete_endpoint() Conclusion In this post, we explored how SageMaker JumpStart empowers data scientists and ML engineers to discover, access, and run a wide range of pre-trained FMs for inference, including the Falcon 3 family of models.

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Benchmarking Computer Vision Models using PyTorch & Comet

Heartbeat

[link] Transfer learning using pre-trained computer vision models has become essential in modern computer vision applications. In this article, we will explore the process of fine-tuning computer vision models using PyTorch and monitoring the results using Comet. Pre-trained models, such as VGG, ResNet.