An AI Hedge Fund Goes Live On Ethereum

https://medium.com/numerai/an-ai-hedge-fund-goes-live-on-ethereum-a80470c6b681

In February, Numerai announced Numeraire, a cryptographic token to incentivize data scientists around the world to contribute artificial intelligence to our hedge fund (see Forbes, Wired, Smith+Crown). Earlier today, the Numeraire smart contract was deployed to Ethereum, and over 1.2 million tokens were sent to 19,000 data scientists around the world.

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The Difference Between LEGO MINDSTORMS EV3 Home Edition (#31313) and LEGO MINDSTORMS Education EV3 (#45544)

http://robotsquare.com/2013/11/25/difference-between-ev3-home-edition-and-education-ev3/ This article covers the difference between the LEGO MINDSTORMS EV3 Home Edition and LEGO MINDSTORMS Education EV3 products. Other articles in the ‘difference between’ series: * The difference and compatibility between EV3 and NXT ( link ) * The difference between NXT Home Edition and NXT Education products ( link ) One robotics platform, two targets The LEGO MINDSTORMS EV3 robotics platform has been developed for two different target audiences. We have home users (children and hobbyists) and educational users (students and teachers). LEGO has designed a base set for each group, as well as several add on sets. There isn’t a clear line between home users and educational users, though. It’s fine to use the Education set at home, and it’s fine to use the Home Edition set at school. This article aims to clarify the differences between the two product lines so you can decide which

Let’s ban PowerPoint in lectures – it makes students more stupid and professors more boring

https://theconversation.com/lets-ban-powerpoint-in-lectures-it-makes-students-more-stupid-and-professors-more-boring-36183 Reading bullet points off a screen doesn't teach anyone anything. Author Bent Meier Sørensen Professor in Philosophy and Business at Copenhagen Business School Disclosure Statement Bent Meier Sørensen does not work for, consult to, own shares in or receive funding from any company or organisation that would benefit from this article, and has no relevant affiliations. The Conversation is funded by CSIRO, Melbourne, Monash, RMIT, UTS, UWA, ACU, ANU, ASB, Baker IDI, Canberra, CDU, Curtin, Deakin, ECU, Flinders, Griffith, the Harry Perkins Institute, JCU, La Trobe, Massey, Murdoch, Newcastle, UQ, QUT, SAHMRI, Swinburne, Sydney, UNDA, UNE, UniSA, UNSW, USC, USQ, UTAS, UWS, VU and Wollongong.

Logic Analyzer with STM32 Boards

https://sysprogs.com/w/how-we-turned-8-popular-stm32-boards-into-powerful-logic-analyzers/ How We Turned 8 Popular STM32 Boards into Powerful Logic Analyzers March 23, 2017 Ivan Shcherbakov The idea of making a “soft logic analyzer” that will run on top of popular prototyping boards has been crossing my mind since we first got acquainted with the STM32 Discovery and Nucleo boards. The STM32 GPIO is blazingly fast and the built-in DMA controller looks powerful enough to handle high bandwidths. So having that in mind, we spent several months perfecting both software and firmware side and here is what we got in the end. Capturing the signals The main challenge when using a microcontroller like STM32 as a core of a logic analyzer is dealing with sampling irregularities. Unlike FPGA-based analyzers, the microcontroller has to share the same resources to load instructions from memory, read/write the program state and capture the external inputs from the G

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