Lifeboat Foundation

Autonomous driving has been one of the fundamental pillars of Tesla’s push to electrify transport, and by all accounts, the California company is leading the pack in production deployments of autonomous driving technology.

The team of engineers at Tesla working on AI are some of the brightest minds in the space and continue to roll out new, innovative ways of not only processing and interpreting computer vision, but in developing new methods to train its AI. It’s the digital equivalent of building the machine that builds the machine, the virtual equivalent to taking a step up the chain from designing automobiles to designing the manufacturing machines, processes, and systems that build them.

Continue reading “Tesla Fast Tracking Full Self-Driving Development With Advanced Neural Net Training Techniques” »

You can now order yourself a Finnish electric motorcycle with lots of torque, lots of range and a very unique look. Oh, and it’s also got a jaw-dropping, gaping hole where the middle of the back wheel would normally be.

We first saw this fancy Finnish design back in 2018. At that stage, it was known as the RMK E2, although since it made its public debut, the company has changed its name to Verge and the bike is now known as the TS.

Now, it’s ready for production and we can put some final numbers to it. The centerless hub motor that constitutes the rear wheel will deliver 80 kW (107 horsepower) and 1,000 Nm (738 lb-ft) of torque. According to Verge, that’ll get you to 100 km/h (62 mph) in less than 4 seconds, which is plenty quick but will see the back of a well-ridden superbike.

High-fidelity modelling of nanosecond repetitively pulsed discharges (NRPDs) is burdened by the multiple time and length scales and large chemistry mechanisms involved, which prohibit detailed analyses and parametric studies. In the present work, we propose a ‘frozen electric-field’ modelling approach to expedite the NRPD simulations without adverse effects on the solution accuracy. First, a burst of nanosecond voltage pulses is simulated self-consistently until the discharge reaches a stationary state. The calculated spatial distributions and temporal evolution of the electric field, electron density and electron energy during the last pulse are then stored in a library and the electrical characteristics of subsequent pulses are frozen at these values. This strategy allows the timestep for numerical integration to be increased by four orders of magnitude (from 10⁻¹³ to 10⁻⁹ s), thereby significantly improving the computational efficiency of the process. Reduced calculations of a burst of 50 discharge pulses show good agreement with the predictions from a complete plasma model (electrical characteristics calculated during each pulse). The error in species densities is less than 20% at the centre of the discharge volume and about 30% near the boundaries. The deviations in temperature, however, are much lower, at 5% in the entire domain. The model predictions are in excellent agreement with measured ignition delay times and temperatures in H₂–air mixtures subject to dielectric barrier NRPD over a pressure range of 54–144 Torr with equivalence ratios of 0.7–1.2. The OH density increases with pressure and triggers low-temperature fuel oxidation, which leads to rapid temperature rise and ignition. The ignition delay decreases by a factor of 2, with an increase in pressure from 54 to 144 Torr. In contrast, an increase in the H₂–air equivalence ratio from 0.7 to 1.2 marginally decreases the ignition delay by about 20%. This behaviour is attributed to the insensitivity of OH production rates to the variation in the equivalence ratio.

Avi Schiffmann has been procrastinating on his school work, but he has a good excuse. The 17-year-old high schooler is the creator of one of the most visited coronavirus trackers in the world, which he says now takes up “100 percent” of his free time.

The coronavirus pandemic doesn’t look like it will be over any time soon, and Schiffmann plans to continue actively tracking it until the end. As long as the site is up, he says he will keep working at it and adding new features. Once the pandemic is safely over, he’ll take the servers down, and maybe make a page that compares COVID-19 to SARS or the Spanish flu. He thinks it might be a historical piece on the coronavirus people can look back on.

Avi Schiffmann’s coronavirus tracker is a one-stop shop for all the information about COVID-19 the average person might want to know. It constantly updates with statistics for countries around the world on infections, deaths, recovered, and rates of change using data scraped from the WHO, CDC, and other government websites.

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Shoes will invariably wear out with enough use, but scientists might have found a way to delay the shopping trip for their replacements. A USC team has created a self-healing 3D-printed rubber that could be ideal for footwear, tires and even soft robotics. The effort involves 3D printing the material with photopolymerization (solidifying a resin with light) while introducing an oxidizer at just the right ratio to add self-healing properties without slowing down the solidifying process.

Continue reading “Self-repairing shoes may be a reality thanks to 3D-printed rubber” »

Not only will the Gemini Solar Project be the largest in US history, it is set to be the eighth largest in the world at 690-MW.

Quantum entanglement – that strange but potentially hugely useful quantum phenomenon where two particles are inextricably linked across space and time – could play a major role in future radar technology.

In 2008, an engineer from MIT devised a way to use the features of entanglement to illuminate objects while using barely any photons. In certain scenarios, such technology promises to outperform conventional radar, according to its makers, particularly in noisy thermal environments.

Now, researchers have taken the idea much further, demonstrating its potential with a working prototype.

That strategy was unveiled in a directive on Wednesday by the Ministry of Industry and Information Technology (MIIT), which called on local authorities in 23 provinces, five autonomous regions and four municipalities to support the establishment of these new big data centres, which will help bolster efforts to upgrade the country’s manufacturing sector.

The Ministry of Industry and Information Technology has called on local authorities in 23 provinces, five autonomous regions and four municipalities to support the establishment of new ‘industrial big data’ centres, which would bolster the digital transformation of various industries.

Over the past several years, the increased application of unmanned air vehicles (UAVs) in a wide variety of industries has inspired both public and private research laboratories to not only continually improve this technology, but to also support the miniaturization of these devices. The development of both micro- and nano-UAVs is directly related to the ability of researchers to miniaturize the major components of these devices, some of which include micro-processors, sensors, batteries and all necessary wireless communication units that allow UAVs to function properly in any given settings.