Lifeboat Foundation

Building a useful quantum computer in practice is incredibly challenging. Significant improvements are needed in the scale, fidelity, speed, reliability, and programmability of quantum computers to fully realize their benefits. Powerful tools are needed to help with the many complex physics and engineering challenges that stand in the way of useful quantum computing.

AI is fundamentally transforming the landscape of technology, reshaping industries, and altering how we interact with the digital world. The ability to take data and generate intelligence paves the way for groundbreaking solutions to some of the most challenging problems facing society today. From personalized medicine to autonomous vehicles, AI is at the forefront of a technological revolution that promises to redefine the future, including many challenging problems standing in the way of useful quantum computing.

Quantum computers will integrate with conventional supercomputers and accelerate key parts of challenging problems relevant to government, academia, and industry. This relationship is described in An Introduction to Quantum Accelerated Supercomputing. The advantages of integrating quantum computers with supercomputers are reciprocal, and this tight integration will also enable AI to help solve the most important challenges standing in the way of useful quantum computing.

An Oakland, California, school district is the first in the US to transition to a 100% electric school bus system with vehicle-to-grid (V2G) technology.

Modern student transportation platform Zum has provided Oakland Unified School District with a fleet of 74 electric school buses and bidirectional chargers. Utility Pacific Gas and Electric (PG&E) supplied 2.7 megawatts (MW) of load to Zum’s Oakland EV-ready facility. The fleet will be managed through Zum’s AI-enabled technology platform.

“Oakland becoming the first in the nation to have a 100% electric school bus fleet is a huge win for the Oakland community and the nation as a whole,” said Kim Raney, executive director of transportation at Oakland Unified School District. “The families of Oakland are disproportionately disadvantaged and affected by high rates of asthma and exposure to air pollution from diesel fuels.”

A cheaper, smaller scanner uses AI to match other MRIs’ image quality.

As AI systems have grown in sophistication, so has their capacity for deception, according to a new analysis from researchers at Massachusetts Institute of Technology (MIT). Dr Peter Park, an AI existential safety researcher at MIT and author of the research, tells Ian Sample about the different examples of deception he uncovered, and why they will be so difficult to tackle as long as AI remains a black box.

How to listen to podcasts: everything you need to know

Listen to the Guardian’s Black Box series all about humans and artificial intelligence.

Brighter with Herbert.

AI chip that mimics the human brain year 2023.

Designing efficient in-memory-computing architectures remains a challenge. Here the authors develop a multi-level FeFET crossbar for multi-bit MAC operations encoded in activation time and accumulated current with experimental validation at 28nm achieving 96.6% accuracy and high performance of 885 TOPS/W.

Artificial general intelligence through an AI photonic chip face_with_colon_three

The pursuit of artificial general intelligence (AGI) continuously demands higher computing performance. Despite the superior processing speed and efficiency of integrated photonic circuits, their capacity and scalability are restricted by unavoidable errors, such that only simple tasks and shallow models are realized. To support modern AGIs, we designed Taichi—large-scale photonic chiplets based on an integrated diffractive-interference hybrid design and a general distributed computing architecture that has millions-of-neurons capability with 160–tera-operations per second per watt (TOPS/W) energy efficiency. Taichi experimentally achieved on-chip 1000-category–level classification (testing at 91.89% accuracy in the 1623-category Omniglot dataset) and high-fidelity artificial intelligence–generated content with up to two orders of magnitude of improvement in efficiency.

Jan Leike, co-leading Superalignment of GPT4o, posted on X, “I resigned,” just the day before the GPT4o launch.

OpenAI co-founder Ilya Sutskever and another executive leave the company as GPT-4o launches.

OpenAI Spring Update – streamed live on Monday, May 13, 2024. Introducing GPT-4o, updates to ChatGPT, and more.