Data and machine learning professionals are wrapping up the year by enhancing skills and preparing for career progression. November’s popular reads in Towards Data Science (TDS) included guides on knowledge graphs, hardware benchmarks, job search tips, and Markov models. New insights and projects explored human’s role in ML, AI bias, and personal data tracking. A…

At the DealBook summit, Nvidia CEO Jensen Huang predicted that AI could rival human intelligence within five years, emphasizing Nvidia’s crucial role in AI’s growth due to the increased demand for their GPUs. Despite current AI limitations, Nvidia’s advancements are significant, amidst calls for robust governance in AI companies.

Researchers at TUS and collaborating institutes have created a deep learning binary classifier that identifies an unknown quasicrystalline phase in materials with over 92% accuracy, revolutionizing material analysis with wide-ranging technological implications.

Chase Dimond shares his journey to earning over 7 figures with a services agency, specifically an email marketing agency, advocating it as the best business model for beginners due to low startup costs, high demand, easy fulfillment, and high profit margins. He outlines four steps to success: choosing your service, building a notable track record,…

Lincoln Laboratory is working to reduce the energy requirements of AI models by promoting energy usage transparency and improving training efficiency.

This guide provides over 50 customizable AI-generated prompts for creating line art coloring book pages using Midjourney, Stable Diffusion, and DALL-E. The prompts span various themes suitable for both children and adults and are designed to output clean, thick-outlined images ideal for coloring. Tips for prompt adjustments and negative prompts are included for optimal results.

Artificial Intelligence, with advancements like GPT-4, has evolved into multimodal AI, integrating text, images, audio, and video for a holistic understanding akin to human perception. This allows for more accurate predictions and nuanced interactions across applications such as customer service, social media analysis, and training, significantly enriching AI’s interface with everyday life.

A study involving 32 papers reviewed the application of explainable AI in poverty estimation using satellite imagery and deep learning. It found that transparency, interpretability, and domain knowledge—key elements of explainable machine learning—vary and often fall below the necessary scientific standards for accurate insights into poverty and welfare.

The blog post introduces PyTorch, a key deep learning library used for creating and operating on tensors, the core components for neural network modeling. It provides a beginner-friendly guide on tensor properties and operations, like addition and multiplication, and connects tensor manipulation to deep learning application. It mentions resources for further learning, including a free…

Deep Learning advancements in AI, specifically in SLAM technology, have been made by University College London researchers with DSP-SLAM. This system accurately maps environments and tracks camera movement, utilizing object shape and pose estimation to improve scene representation significantly. It performs well across multiple input types and has excelled in reconstructing objects in tests.