Making ‘transport’ robots smarter

Imagine a team of humans and robots working together to process online orders — real-life workers strategically positioned among their automated coworkers who are moving intelligently back and forth in a warehouse space, picking items for shipping to the customer. This could become a reality sooner than later, thanks to researchers who are working to …

Sampling and pipelining method speeds up deep learning on large graphs

Graphs, a potentially extensive web of nodes connected by edges, can be used to express and interrogate relationships between data, like social connections, financial transactions, traffic, energy grids, and molecular interactions. As researchers collect more data and build out these graphical pictures, researchers will need faster and more efficient methods, as well as more computational …

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Better Language Models Without Massive Compute

Posted by Jason Wei and Yi Tay, Research Scientists, Google Research, Brain Team In recent years, language models (LMs) have become more prominent in natural language processing (NLP) research and are also becoming increasingly impactful in practice. Scaling up LMs has been shown to improve performance across a range of NLP tasks. For instance, scaling …

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Boost medical discoveries with AlphaFold on Vertex AI

There’s a lot we can learn from combining technology with science to help support the development of amazing discoveries. By using an AI system to predict protein shapes, we have the potential to accelerate research in every field of biology. Inside every cell in your body, billions of tiny molecular machines are hard at work. …

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How InstaDeep used Cloud TPU v4 to help sustainable agriculture

You are what you eat. We’ve all been told this, but the truth is what we eat is often more complex than we are – genetically at least. Take a grain of rice. The plant that produces rice has 40,000 to 50,000 genes, double that of humans, yet we know far more about the composition …