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[Alexander] created codex_py2cpp as a way of experimenting with Codex, an AI intended to translate natural language into code. [Alexander] had slightly different ideas, however, and created codex_py2cpp as a way to play with the idea of automagically converting Python into C++. Itâs not really intended to create robust code conversions, but as far as experiments go, itâs pretty neat.
Spike-based neuromorphic hardware holds the promise to provide more energy efficient implementations of Deep Neural Networks (DNNs) than standard hardware such as GPUs. But this requires to understand how DNNs can be emulated in an event-based sparse firing regime, since otherwise the energy-advantage gets lost. In particular, DNNs that solve sequence processing tasks typically employ Long Short-Term Memory (LSTM) units that are hard to emulate with few spikes. We show that a facet of many biological neurons, slow after-hyperpolarizing (AHP) currents after each spike, provides an efficient solution. AHP-currents can easily be implemented in neuromorphic hardware that supports multi-compartment neuron models, such as Intelâs Loihi chip. Filter approximation theory explains why AHP-neurons can emulate the function of LSTM units.
Classifying celestial objects is a long-standing problem. With sources at near unimaginable distances, sometimes itâs difficult for researchers to distinguish between objects such as stars, galaxies, quasars or supernovae.
Instituto de AstrofĂsica e CiĂȘncias do Espaçoâs (IA) researchers Pedro Cunha and Andrew Humphrey tried to solve this classical problem by creating SHEEP, a machine-learning algorithm that determines the nature of astronomical sources. Andrew Humphrey (IA & University of Porto, Portugal) comments: âThe problem of classifying celestial objects is very challenging, in terms of the numbers and the complexity of the universe, and artificial intelligence is a very promising tool for this type of task.â
The first author of the article, now published in the journal Astronomy & Astrophysics, Pedro Cunha, a Ph.D. student at IA and in the Dept. of Physics and the University of Porto, says, âThis work was born as a side project from my MSc thesis. It combined the lessons learned during that time into a unique project.â
This March, we, a group of educators, scientists, and psychologists started an educational non-profit (501 c3) Earthlings Hub, helping kids in refugee camps and evacuated orphanages. We are getting lots of requests for help, and are in urgent need to raise funds. If you happen to have any connections to educational and humanitarian charities, or if your universities or companies may be interested in providing some financial support to our program, we would really appreciate that! Please share with everyone who might be able to offer help or advice.
Our advisory board includes NASA astronaut Greg Chamitoff, Professor Uri Wilensky, early math educator Maria Droujkova, AI visionary Joscha Bach, and others.
Support Us The Earthlings Hub works with a fiscal sponsor Blue Marble Space. CREDIT CARD & PAYPAL Please contact us if you would like to via other means, such as checks, stocks, cryptocurrency, or using your Donor Advised Fund: [email protected]
âWeâve spent a lot of time in education to help people understand that just like an automobile extends your capabilities in the physical domain, artificial intelligence extends your abilities within the data domain and the information domain,â the general said Wednesday.
AI and its traces can be found across the Pentagon and its many enclaves and alcoves. The department has for years recognized its value as well, describing the tech in a 2018 strategy as rapidly changing businesses, industries and military threats. More can be done, Groen said.
A new training approach yields artificial intelligence that adapts to diverse play-styles in a cooperative game, in what could be a win for human-AI teaming.
As artificial intelligence gets better at performing tasks once solely in the hands of humans, like driving cars, many see teaming intelligence as a next frontier. In this future, humans and AI are true partners in high-stakes jobs, such as performing complex surgery or defending from missiles. But before teaming intelligence can take off, researchers must overcome a problem that corrodes cooperation: humans often do not like or trust their AI partners.
Now, new research points to diversity as being a key parameter for making AI a better team player.
Details released for a new critical remote code execution vulnerability affecting the Chrome dev channel and related Chromium-based web browsers.
The speed of operations leaves manual inspectors with just seconds to decide if the product is really defective, or not.
Thatâs where Microsoftâs Project Brainwave could come in. Project Brainwave is a hardware architecture designed to accelerate real-time AI calculations. The Project Brainwave architecture is deployed on a type of computer chip from Intel called a field programmable gate array, or FPGA, to make real-time AI calculations at competitive cost and with the industryâs lowest latency, or lag time. This is based on internal performance measurements and comparisons to other organizationsâ publicly posted information.
Continue reading “Real-time AI: Microsoft announces preview of Project Brainwave” »
Single-cell RNA-sequencing technology gives access to cell cycle dynamics without externally perturbing the cell. Here the authors present DeepCycle, a robust deep learning method to infer the cell cycle state in single cells from scRNA-seq data.
The worldâs smallest remote-controlled walking robot, measuring just half a millimetre wide, has been demonstrated by Northwestern University. Its potential applications include the clearing of blocked arteries.
