Lifeboat Foundation

With their ability to generate human-like language and complete a variety of tasks, generative AI has the potential to revolutionise the way we communicate, learn and work. But what other doors will this technology open for us, and how can we harness it to make great leaps in technology innovation? Have we finally done it? Have we cracked AI?

Join Professor Michael Wooldridge for a fascinating discussion on the possibilities and challenges of generative AI models, and their potential impact on societies of the future.

Continue reading “The Turing Lectures: The future of generative AI” »

Vending machines are an old charming piece of technology that supposedly makes the lives of people easier by making water, snacks and food in general readily available.

American Rounds says that it aims to redefine convenience in ammunition purchasing, as its ammo dispensers can be accessed round the clock.

Continue reading “Ammo ATM? AI-powered bullet vending machines introduced in US” »

Pushback on self service check out due to higher theft and increased discontent from customers.

Scientists run into a lot of tradeoffs trying to build and scale up brain-like systems that can perform machine learning. For instance, artificial neural networks are capable of learning complex language and vision tasks, but the process of training computers to perform these tasks is slow and requires a lot of power.

Training machines to learn digitally but perform tasks in analog—meaning the input varies with a physical quantity, such as voltage—can reduce time and power, but small errors can rapidly compound.

An electrical network that physics and engineering researchers from the University of Pennsylvania previously designed is more scalable because errors don’t compound in the same way as the size of the system grows, but it is severely limited as it can only learn linear tasks, ones with a simple relationship between the input and output.

1/ Chinese AI company SenseTime introduced its new multimodal AI model SenseNova 5o at the World Artificial Intelligence Conference, which SenseTime claims is China’s first GPT-4o-level multimodal real-time model.

2/ It processes audio, text, image and video data to interact with users as if they…

Chinese AI company SenseTime introduced its new multimodal AI model SenseNova 5o and the improved language model SenseNova 5.5 at the World Artificial Intelligence Conference.

Continue reading “SenseTime unveils SenseNova 5o, China’s first real-time multimodal AI model to rival GPT-4o” »

According to Fox 45 Baltimore, the Maryland Piedmont Reliability Project (MPRP) is a new plan to build a 70-mile 500,000-volt transmission line across three counties: Frederick, Baltimore, and Carroll. The line will connect a substation in southern Frederick County and supply the area with additional load capacity to handle surging power demand from AI data centers.

MPRP’s website explains that the new transmission lines will require the acquisition of private property through the use of an eminent domain, or government-mandated seizure to complete the construction.

“If PSEG and a property owner cannot agree on mutually acceptable value, PSEG may seek to use the power of eminent domain using the process set forth by the state of Maryland to acquire the necessary property rights,” the developer’s website states.

WASHINGTON — The Defense Advanced Research Projects Agency (DARPA) has selected the startup Scout Space to participate in the BRIDGES (Bringing Classified Innovation to Defense and Government Systems) consortium.

BRIDGES, launched by DARPA in 2023, aims to connect innovative small companies and nontraditional defense contractors with classified Department of Defense research and development efforts. The initiative seeks to bridge the gap between cutting-edge commercial technologies and classified defense needs, particularly in areas considered critical to maintaining U.S. military superiority.

Scout Space, based in Reston, Virginia, develops satellite flight software and space domain awareness sensors. The company announced July 8 it was selected by DARPA for its proposal outlining an approach to “advancing autonomous in-space threat response.”

Scientists merged human brain-like tissue with a computer chip and taught tiny robots how to navigate obstacles and grasp items.⁠

Scientists take another step towards organoid ‘hybrid intelligence.’

As artificial intelligence (AI) becomes increasingly ubiquitous in business and governance, its substantial environmental impact — from significant increases in energy and water usage to heightened carbon emissions — cannot be ignored. By 2030, AI’s power demand is expected to rise by 160%. However, adopting more sustainable practices, such as utilizing foundation models, optimizing data processing locations, investing in energy-efficient processors, and leveraging open-source collaborations, can help mitigate these effects. These strategies not only reduce AI’s environmental footprint but also enhance operational efficiency and cost-effectiveness, balancing innovation with sustainability.

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Practical steps for reducing AI’s surging demand for water and energy.