The photos include a 360 degree panorama of the terrain, a selfie of the rover, and a picture of the rover’s landing platform sporting a Chinese flag.
Google wants to train you to become a UX designer in 6 months — without a college degree. Here’s how to make the most of the certificate program and potentially make $84000 a year.
The US unemployment rate sits at 6.7%. Thanks to COVID-19, millions of Americans are still out there looking for not just a new job but also an entire new career path.
Tech fields like UX design, data analysis, and project management are looking for promising candidates, and Google announced a new career-certificate program to help make them more accessible last summer.
Circa 2011
It sounds like a late-night infomercial: Kill germs and clean surfaces with nothing more than water and a few volts of electricity! Pay pennies a gallon! Strong enough to kill germs but gentle on your skin!
The use of electricity and water to clean and disinfect has been embraced by some food and hospitality businesses looking to save money and go green by swapping out conventional products.
Continue reading “Electrified water lets cleaners ditch the bleach” »
Introducing ways of defining and working with Infinite values in Python.
∀ x ∈ ℝ, -∞ < x < ∞
Every number is smaller than positive infinity and bigger than negative infinity.
Since the DeepSpeed optimization library was introduced last year, it has rolled out numerous novel optimizations for training large AI models—improving scale, speed, cost, and usability. As large models have quickly evolved over the last year, so too has DeepSpeed. Whether enabling researchers to create the 17-billion-parameter Microsoft Turing Natural Language Generation (Turing-NLG) with state-of-the-art accuracy, achieving the fastest BERT training record, or supporting 10x larger model training using a single GPU, DeepSpeed continues to tackle challenges in AI at Scale with the latest advancements for large-scale model training. Now, the novel memory optimization technology ZeRO (Zero Redundancy Optimizer), included in DeepSpeed, is undergoing a further transformation of its own. The improved ZeRO-Infinity offers the system capability to go beyond the GPU memory wall and train models with tens of trillions of parameters, an order of magnitude bigger than state-of-the-art systems can support. It also offers a promising path toward training 100-trillion-parameter models.
ZeRO-Infinity at a glance: ZeRO-Infinity is a novel deep learning (DL) training technology for scaling model training, from a single GPU to massive supercomputers with thousands of GPUs. It powers unprecedented model sizes by leveraging the full memory capacity of a system, concurrently exploiting all heterogeneous memory (GPU, CPU, and Non-Volatile Memory express or NVMe for short). Learn more in our paper, “ZeRO-Infinity: Breaking the GPU Memory Wall for Extreme Scale Deep Learning.” The highlights of ZeRO-Infinity include:
D-Wave’s newest offering, available in mid-2020, offers two and a half times more connectivity between qubits than the 2000Q quantum computer.
Just as microelectronics transformed the modern world through the creation of the integrated circuit, which is now at the heart of most electronic devices, quantum photonics needs an equivalent platform to fulfil its application potential. In this special focus issue of Nature Photonics, we report on the progress in making this a reality with the developments in integrated quantum photonics (IQP).
In a Review Article, Jianwei Wang and colleagues provide a general overview and introduction to IQP circuits and summarize the present development of quantum hardware based on IQP chips. They remark that the challenge for measurement-based quantum computation may shift from the need for deterministic gates to constructing a generic entangled cluster-state, on which any quantum computation could be mapped by a sequence of measurements.
IQP circuits are also a desirable platform for chip-based quantum communications. However, fully integrated chip-based quantum communication has not yet been realized, largely because of the integration difficulties between silicon wafers that feature optical waveguides and other passive components and light sources and photodetectors that are made from different semiconductors. Key components such as transmitters and receivers for quantum key distribution and quantum random number generators are instead individually fabricated.
A free-floating planet (FFP) is a planetary-mass object that orbits around a non-stellar massive object (e.g. a brown dwarf) or around the Galactic Centre. The presence of exomoons orbiting FFPs has been theoretically predicted by several models. Under specific conditions, these moons are able to retain an atmosphere capable of ensuring the long-term thermal stability of liquid water on their surface. We model this environment with a one-dimensional radiative-convective code coupled to a gas-phase chemical network including cosmic rays and ion-neutral reactions. We find that, under specific conditions and assuming stable orbital parameters over time, liquid water can be formed on the surface of the exomoon. The final amount of water for an Earth-mass exomoon is smaller than the amount of water in Earth oceans, but enough to host the potential development of primordial life.
Dark matter may self-interact through a continuum of low-mass states. This happens if dark matter couples to a strongly-coupled nearly-conformal hidden sector. This type of theory is holographically described by brane-localized dark matter interacting with bulk fields in a slice of 5D anti-de Sitter space. The long-range potential in this scenario depends on a non-integer power of the spatial separation, in contrast to the Yukawa potential generated by the exchange of a single 4D mediator. The resulting self-interaction cross section scales like a non-integer power of velocity. We identify the Born, classical and resonant regimes and investigate them using state-of-the-art numerical methods. We demonstrate the viability of our continuum-mediated framework to address the astrophysical small-scale structure anomalies. Investigating the continuum-mediated Sommerfeld enhancement, we demonstrate that a pattern of resonances can occur depending on the non-integer power. We conclude that continuum mediators introduce novel power-law scalings which open new possibilities for dark matter self-interaction phenomenology.
A preprint version of the article is available at ArXiv.
