The notion that artificial intelligence will help us prepare for the world of tomorrow is woven into our collective fantasies. Based on what we’ve seen so far, however, AI seems much more capable of replaying the past than predicting the future. That’s because AI algorithms are trained on data. By its very nature, data is…
A new kind of machine-learning model built by a team of researchers at the music-streaming firm Spotify captures for the first time the complex math behind counterfactual analysis, a precise technique that can be used to identify the causes of past events and predict the effects of future ones. The model, described earlier this year…
This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. Last week, AI insiders were hotly debating an open letter signed by Elon Musk and various industry heavyweights arguing that AI poses an “existential risk” to humanity. They called for labs to introduce a…
In this post, we introduce Koala, a chatbot trained by fine-tuning Meta’s LLaMA on dialogue data gathered from the web. We describe the dataset curation and training process of our model, and also present the results of a user study that compares our model to ChatGPT and Stanford’s Alpaca. Our results show that Koala can…
AI language models are the shiniest, most exciting thing in tech right now. But they’re poised to create a major new problem: they are ridiculously easy to misuse and to deploy as powerful phishing or scamming tools. No programming skills are needed. What’s worse is that there is no known fix. Tech companies are racing…
If you’ve ever played soccer with a robot, it’s a familiar feeling. Sun glistens down on your face as the smell of grass permeates the air. You look around. A four-legged robot is hustling toward you, dribbling with determination. While the bot doesn’t display a Lionel Messi-like level of ability, it’s an impressive in-the-wild dribbling…
Posted by Piotr Padlewski and Josip Djolonga, Software Engineers, Google Research Large Language Models (LLMs) like PaLM or GPT-3 showed that scaling transformers to hundreds of billions of parameters improves performance and unlocks emergent abilities. The biggest dense models for image understanding, however, have reached only 4 billion parameters, despite research indicating that promising multimodal…
With the release of platforms like DALL-E 2 and Midjourney, diffusion generative models have achieved mainstream popularity, owing to their ability to generate a series of absurd, breathtaking, and often meme-worthy images from text prompts like “teddy bears working on new AI research on the moon in the 1980s.” But a team of researchers at…
Neural networks, a type of machine-learning model, are being used to help humans complete a wide variety of tasks, from predicting if someone’s credit score is high enough to qualify for a loan to diagnosing whether a patient has a certain disease. But researchers still have only a limited understanding of how these models work….
Posted by Peter Mattson, Senior Staff Engineer, ML Performance, and Praveen Paritosh, Senior Research Scientist, Google Research, Brain Team Machine learning (ML) offers tremendous potential, from diagnosing cancer to engineering safe self-driving cars to amplifying human productivity. To realize this potential, however, organizations need ML solutions to be reliable with ML solution development that is…