Lifeboat Foundation

A coating that can hide objects in plain sight, or an implant that behaves exactly like bone tissue. These extraordinary objects are already made from metamaterials. Researchers from TU Delft have now developed an AI tool that not only can discover such extraordinary materials but also makes them fabrication-ready and durable. This makes it possible to create devices with unprecedented functionalities.

They published their findings in Advanced Materials (“Deep Learning for Size-Agnostic Inverse Design of Random-Network 3D Printed Mechanical Metamaterials”).

Continue reading “New AI tool discovers realistic metamaterials with unusual properties (w/video)” »

Microsoft is back with another Super Bowl ad, this time for its AI chatbot called Copilot. And it kind of sucks.

SingularityNET’s community leaders reflect back on last year’s progress, ecosystem updates, as well as the massive push towards building beneficial AGI in 2024 and beyond.

Register for our BGI Summit today by visiting: https://bgi24.ai.

Continue reading “SingularityNET’s Big AGI Plans for 2024” »

Reliable quantum gates are the fundamental component of quantum information processing. However, achieving high-dimensional unitary transformations in a scalable and compact manner with ultrahigh fidelities remains a great challenge.

To address this issue, scientists in China showcase the use of deep diffractive neural networks (D²NNs) to construct a series of high-dimensional quantum gates, which are encoded by the spatial modes of photons. This work, published in Light: Science & Applications, offers a new paradigm for quantum gate design using deep learning.

Quantum computing holds the promise of transforming our information processing methodologies, and at its core, reliable quantum logic gates play an essential role in quantum information processing.

Wavelength-selective thermal emitters (WS-TEs) have been frequently designed to achieve desired target emissivity spectra, as in typical emissivity engineering, for broad applications such as thermal camouflage, radiative cooling, and gas sensing, etc.

However, previous designs required prior knowledge of materials or structures for different applications, and the designed WS-TEs usually vary from application to application in terms of materials and structures, thus there is no general design framework for emissivity engineering across different applications. Moreover, previous designs fail to tackle the simultaneous design of both materials and structures, as they either fix materials to design structures or fix structures to select suitable materials.

In a new paper published in Light: Science & Applications, a team of scientists, led by Professor Run Hu from School of Energy and Power Engineering, Huazhong University of Science and Technology, China, and coworkers have proposed a general deep learning framework based on the deep Q-learning network algorithm (DQN) for efficient optimal design of WS-TEs across different applications.

A fledgling startup founded by one of OpenAI’s first engineering hires is looking to “redefine manufacturing,” with AI-powered factories for creating bespoke precision parts.

Daedalus, as the company is called, is based in the southwestern German city of Karlsruhe, where its solo factory is currently housed. Here, Daedalus takes orders from industries such as medical devices, aerospace, defense, and semiconductors, each requiring unique components for their products. For example, a pharmaceutical company might require a customized metal casing for a valve used in the production of a particular medicine.

As it looks to ramp up operations with a view toward opening additional factories in its domestic market, Daedalus today announced it has raised $21 million in a Series A round of funding led by Nokia-funded NGP Capital, with participation from existing investors Khosla Ventures and Addition.

A new batch of startups are using tech and data to help supermarkets reduce waste of fresh produce, to the benefit of business and planet.

There’s a real life bionic woman, and a mindblowing technological advancement has made her life a lot better.

Artificial intelligence (AI) is evolving at break-neck speed and was one of the key themes at one of the world’s biggest tech events this year, CES.

From flying cars to brain implants that enable tetraplegics to walk, the show revealed some of the most recent AI-powered inventions destined to revolutionize our lives. It also featured discussions and presentations around how AI can help address many of the world’s challenges, as well as concerns around ethics, privacy, trust and risk.

Given how widespread AI is and the rate at which it is evolving, global harmonization of terminologies, best practice and understanding is important to enable the technology to be deployed safely and responsibly. IEC and ISO International Standards fulfil that role and are thus important tools to enable AI technologies to truly benefit society. They can not only provide a common language for the industry, they also enable interoperability and provide international best practice, while addressing any risks and societal issues.