Lifeboat Foundation

This timelapse of future technology begins with 2 Starships, launched to resupply the International Space Station. But how far into the future do you want to go?

Tesla Bots will be sent to work on the Moon, and A.I. chat bots will guide people into dreams that they can control (lucid dreams). And what happens when humanity forms a deeper understanding of dark energy, worm holes, and black holes. What type of new technologies could this advanced knowledge develop? Could SpaceX launch 100 Artificial Intelligence Starships, spread across our Solar System and beyond into Interstellar space, working together to form a cosmic internet, creating the Encyclopedia of the Galaxy. Could Einstein’s equations lead to technologies in teleportation, and laboratory grown black holes.

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After cracking an unsolvable mathematics problem last year, AI is back to tackle geometry.

Developed by Google DeepMind, a new algorithm, AlphaGeometry, can crush problems from past International Mathematical Olympiads—a top-level competition for high schoolers—and matches the performance of previous gold medalists.

When challenged with 30 difficult geometry problems, the AI successfully solved 25 within the standard allotted time, beating previous state-of-the-art algorithms by 15 answers.

Researchers based at the Drexel University College of Engineering have devised a new method for performing structural safety inspections using autonomous robots aided by machine learning technology.

The article they published recently in the Elsevier journal Automation in Construction presented the potential for a new multi-scale monitoring system informed by deep-learning algorithms that work to find cracks and other damage to buildings before using LiDAR to produce three-dimensional images for inspectors to aid in their documentation.

The development could potentially work to benefit the enormous task of maintaining the health of structures that are increasingly being reused or restored in cities large and small across the country. Despite the relative age of America’s built environment, roughly two-thirds of today’s existing buildings will be in use in the year 2050, according to Gensler’s predictions.

Researchers have proposed a new strategy for the shape assembly of robot swarms based on the idea of mean-shift exploration: When a robot is surrounded by neighboring robots and unoccupied locations, it actively gives up its current location by exploring the highest density of nearby unoccupied locations in the desired shape.

The study, titled, “Mean-shift exploration in shape assembly of robot swarms,” has been published in Nature Communications.

This idea is realized by adapting the mean-shift algorithm, an optimization technique widely used in machine learning for locating the maxima of a density function.

The automotive industry has experienced rapid advancements due to the integration of edge computing and artificial intelligence (AI) in recent years. As vehicles continue developing self-driving capabilities, these technologies have become increasingly critical for effective decision-making and real-time reactions.

Edge computing processes data and commands locally within a vehicle’s systems, improving road safety and transportation efficiency. Combined with 5G, it enables real-time communication between vehicles and infrastructure, reducing latency and allowing autonomous vehicles to respond faster. AI algorithms enable cars to interpret visual data and make human-like driving decisions.

Edge computing and AI are transforming vehicles into true self-driving machines, filling any gaps in low-latency 5G tech and enabling companies to pioneer advanced autonomy.

In the adrenaline-fueled arena of sports gambling, a revolution is unfolding — one powered by artificial intelligence (AI). This technological marvel is transforming the art of sports betting from a game of chance into a symphony of data-driven precision. Let us explore the burgeoning world where AI intersects with sports gambling, turning bettors from mere spectators into strategic players in a game where data, algorithms, and probabilities redefine the odds.

Sports gambling, a realm where intuition, experience, and sometimes sheer luck have traditionally dictated the rules, is undergoing a transformative shift. AI, with its unparalleled ability to analyze vast datasets and discern patterns beyond human capability, is emerging as the new MVP in this field. This transition from gut-driven bets to AI-powered predictions is not just about increasing the odds of winning; it’s about elevating sports gambling to an art of calculated strategies.

At the heart of AI’s influence in sports gambling lies predictive analytics. Companies like Stratagem and Stats Perform are harnessing the power of AI to analyze historical data, player statistics, and even weather conditions to predict game outcomes with astonishing accuracy. For instance, Stratagem uses advanced machine learning algorithms to turn data from thousands of past games into insightful betting strategies, offering gamblers an edge that was unimaginable a few years ago.

Classical computers can sometimes outperform quantum computers thanks to new algorithms, challenging the idea that quantum always prevails.

NYU researchers have developed a new method that allows classical computers to perform certain tasks faster and more efficiently than quantum computers.

Quantum computing has been hailed as a technology that can outperform classical computing in both speed and memory usage, potentially opening the way to making predictions of physical phenomena not previously possible.

Many see quantum computing’s advent as marking a paradigm shift from classical, or conventional, computing. Conventional computers process information in the form of digital bits (0s and 1s), while quantum computers deploy quantum bits (qubits) to store quantum information in values between 0 and 1.

Under certain conditions, this ability to process and store information in qubits can be used to design quantum algorithms that drastically outperform their classical counterparts. Notably, quantum’s ability to store information in values between 0 and 1 makes it difficult for classical computers to perfectly emulate quantum ones.

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.

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