Posted by Robin Kothari and Rolando Somma, Research Scientists, Google Research, Quantum AI Team Quantum computers promise to solve some problems exponentially faster than classical computers, but there are only a handful of examples with such a dramatic speedup, such as Shor’s factoring algorithm and quantum simulation. Of those few examples, the majority of them…
Posted by Hidayet Aksu, Software Engineer, and Adam Sealfon, Research Scientist, Google In recent years, the Privacy Sandbox initiative was launched to explore responsible ways for advertisers to measure the effectiveness of their campaigns, by aiming to deprecate third-party cookies (subject to resolving any competition concerns with the UK’s Competition and Markets Authority). Cookies are…
Posted by Eliya Nachmani, Research Scientist, and Michelle Tadmor Ramanovich, Software Engineer, Google Research Speech-to-speech translation (S2ST) is a type of machine translation that converts spoken language from one language to another. This technology has the potential to break down language barriers and facilitate communication between people from different cultures and backgrounds. Previously, we introduced…
Each time you use AI to generate an image, write an email, or ask a chatbot a question, it comes at a cost to the planet. In fact, generating an image using a powerful AI model takes as much energy as fully charging your smartphone, according to a new study by researchers at the AI…
Tim O’Reilly forwarded an excellent article about the OpenAI soap opera to me: Matt Levine’s “Money Stuff: Who Controls Open AI.” I’ll skip most of it, but something caught my eye. Towards the end, Levine writes about Elon Musk’s version of Nick Bostrom’s AI that decides to turn the world to paper-clips: [Elon] Musk gave…
Speaking at the “Generative AI: Shaping the Future” symposium on Nov. 28, the kickoff event of MIT’s Generative AI Week, keynote speaker and iRobot co-founder Rodney Brooks warned attendees against uncritically overestimating the capabilities of this emerging technology, which underpins increasingly powerful tools like OpenAI’s ChatGPT and Google’s Bard. “Hype leads to hubris, and hubris…
From EV batteries to solar cells to microchips, new materials can supercharge technological breakthroughs. But discovering them usually takes months or even years of trial-and-error research. Google DeepMind hopes to change that with a new tool that uses deep learning to dramatically speed up the process of discovering new materials. Called graphical networks for material…
Generative AI has been the biggest technology story of 2023. Almost everybody’s played with ChatGPT, Stable Diffusion, GitHub Copilot, or Midjourney. A few have even tried out Bard or Claude, or run LLaMA1 on their laptop. And everyone has opinions about how these language models and art generation programs are going to change the nature…
This story is from The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. Ever since last week’s dramatic events at OpenAI, the rumor mill has been in overdrive about why the company’s chief scientific officer Ilya Sutskever and its board decided to oust CEO Sam…
To teach an AI agent a new task, like how to open a kitchen cabinet, researchers often use reinforcement learning — a trial-and-error process where the agent is rewarded for taking actions that get it closer to the goal. In many instances, a human expert must carefully design a reward function, which is an incentive…