Machine Learning vs. Traditional Analytics: When to Use Which?
This article focuses on demystifying the difference between traditional data analytics methods vs.
GENOT: Entropic (Gromov) Wasserstein Flow Matching with Applications to Single-Cell Genomics
Single-cell genomics has significantly advanced our understanding of cellular behavior, catalyzing innovations in treatments and precision medicine. However, single-cell sequencing technologies are inherently destructive and can only measure a limited array of data modalities simultaneously. This limitation underscores the need for new methods capable of realigning cells. Optimal transport (OT) has emerged as a potent …
Query structured data from Amazon Q Business using Amazon QuickSight integration
Amazon Q Business is a generative AI-powered assistant that can answer questions, provide summaries, generate content, and securely complete tasks based on data and information in your enterprise systems. Although generative AI is fueling transformative innovations, enterprises may still experience sharply divided data silos when it comes to enterprise knowledge, in particular between unstructured content …
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Faster food: How Gemini helps restaurants thrive through multimodal visual analysis
Businesses across all industries are turning to AI for a clear view of their operations in real-time. Whether it’s a busy factory floor, a crowded retail space, or a bustling restaurant kitchen, the ability to monitor your work environment helps businesses be more proactive and ultimately, more efficient. Gemini 1.5 Pro’s multimodal and long context …
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Innovative robot navigation inspired by brain function boosts efficiency and accuracy
A research team has taken inspiration from the brains of insects and animals for more energy-efficient robotic navigation.
Jensen Huang Wants to Make AI the New World Infrastructure
Nvidia CEO Jensen Huang has a plan to bring AI infrastructure to countries around the world, and he’s pitching it in person.
Platform allows AI to learn from constant, nuanced human feedback rather than large datasets
During your first driving class, the instructor probably sat next to you, offering immediate advice on every turn, stop and minor adjustment. If it was a parent, they might have even grabbed the wheel a few times and shouted “Brake!” Over time, those corrections and insights developed experience and intuition, turning you into an independent, …
Building a Graph RAG System: A Step-by-Step Approach
Graph RAG, Graph RAG, Graph RAG! This term has become the talk of the town, and you might have come across it as well.
Speed up your AI inference workloads with new NVIDIA-powered capabilities in Amazon SageMaker
This post is co-written with Abhishek Sawarkar, Eliuth Triana, Jiahong Liu and Kshitiz Gupta from NVIDIA. At re:Invent 2024, we are excited to announce new capabilities to speed up your AI inference workloads with NVIDIA accelerated computing and software offerings on Amazon SageMaker. These advancements build upon our collaboration with NVIDIA, which includes adding support …
Vertex AI grounding: More reliable models, fewer hallucinations
At the Gemini for Work event in September, we showcased how generative AI is transforming the way enterprises work. Across all the customer innovation we saw at the event, one thing was clear – if last year was about gen AI exploration and experimentation, this year is about achieving real-world impact. Gen AI has the …
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