NVIDIA introduces professional certifications for AI infrastructure and operations practitioners, offering structured paths to enhance skills. The certifications equip professionals with advanced AI infrastructure and operations skills to boost career prospects.
Google's London office exudes a startup vibe, as managing director Debbie Weinstein explores AI's commercial potential amid US antitrust issues.
Amazon SageMaker announces updates to the inference optimization toolkit, including speculative decoding and FP8 quantization for faster generative AI model optimization. Integration with NVIDIA's TensorRT-LLM for enhanced performance and reduced deployment time, making it easier to achieve best-in-class results in hours.
AI agents are dynamic entities revolutionizing network deployment, configuration, and monitoring in 2024. They adapt, reason, and act autonomously, enhancing decision-making and real-time responsiveness.
Chronos-Bolt in AutoGluon-TimeSeries offers faster zero-shot forecasting than traditional models, outperforming statistical and deep learning baselines. Based on T5 architecture, it's 250x faster and 20x more memory-efficient than original Chronos models, delivering accurate predictions.
MIT scientists develop photonic chip for deep neural network computations, achieving high speed and accuracy. The chip could revolutionize deep learning for applications like lidar and high-speed telecommunications.
Learn how to use network science and Python to map out the connections between characters in the popular show Arcane from League of Legends universe on Netflix. By scraping character data and visualizing the network, you can apply these skills to any complex system beyond just the Arcane series.
Amazon SageMaker Fast Model Loader reduces LLM deployment time by 15x by streaming model weights from Amazon S3. This innovation transforms LLM deployment, offering faster loading times for more efficient AI applications.
Generate synthetic data for machine learning regression using a neural network with specified parameters. Simplify complex data generation with a customizable function in C#.
MIT Associate Professor Catherine D’Ignazio applies data to social issues, empowering citizens with data-driven arguments. Her work on feminicide led to innovative AI tools and a book, "Counting Feminicide," raising awareness globally.
Concerns grow over environmental impacts of Large Language Models (LLMs). Example: Llama 3.1 405B by Meta requires massive resources, emits tons of CO2. OpenAI faces financial strain with inference costs nearly matching total revenue.
Marietje Schaake discusses the unprecedented power of big tech in her new book. She highlights how tech companies' influence spans across various sectors, unlike previous monopolies.
Developers at re:Invent 2024 face unique challenges of physical AWS DeepRacer racing. Transition from virtual to physical racing poses a significant challenge due to differences in environments and car capabilities.
DER SPIEGEL enhances news recommendations using Large Language Models (LLMs) for accurate predictions. Results show LLMs achieve 56% Precision@5, outperforming random recommendations.
ChatGPT surpasses scientists, raising concerns about AI's future. Drew Breunig categorizes AI into gods, interns, and cogs, highlighting potential existential threats.