Standard Chartered and Northern Trust cryptocustody JV wins FCA approval


Standard Chartered and Northern Trust cryptocustody JV wins FCA approval

Zodia Custody, a digital asset joint venture operation between Standard Chartered and Northern Trust, has received regulatory approval from the Financial Conduct Authority and is now providing commercial services to clients as a cryptoasset business.

An Overview of Standard Ranges – Tristan Brindle – CppCon 2019
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Presentation Slides, PDFs, Source Code and other presenter materials are available at:

An Overview of Standard Ranges

The ranges revolution is nearly upon us! C++20 will include concept-enabled, range-based versions of all the standard algorithms you know and love, as well as new “views” which can transform the way you write code. In this talk we’ll offer an overview of the ranges features currently in the C++20 draft, with examples of how you can use them to reduce verbosity, avoid bugs and improve the correctness of your code, and in some cases get better performance. We’ll also cover the currently-available ranges implementations that you can use today, without having to wait for the next version of the standard.

If you’ve heard the buzz around ranges and are wondering what they’ll bring and how they’ll benefit your code-base, then this is the talk for you.

Tristan Brindle

Tristan is a freelance developer, C++ trainer and BSI committee member based in London. He’s the author of NanoRange, a C++14-compatible Ranges implementation, and lead tutor for C++ London Uni, a not-for-profit organisation offering free weekly C++ classes for students in London and around the world.

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Evaluating the Increasing Threat of U.S. Recession

Central banks have been working to slow demand, which we think increases the chance of mild recession. Head of Portfolio Solutions for Global Fixed Income Tim Johnson evaluates what the market and economic indicators are saying.

Guarding Against Spurious Correlations in Natural Language Understanding / He He (NYU)

Guarding Against Spurious Correlations in Natural Language Understanding

While we have made great progress in natural language understanding, transferring the success from benchmark datasets to real applications has not always been smooth. Notably, models sometimes make mistakes that are confusing and unexpected to humans. In this talk, I will discuss shortcuts in NLP tasks and present our recent works on guarding against spurious correlations in natural language understanding tasks (e.g. textual entailment and paraphrase identification) from the perspectives of both robust learning algorithms and better data coverage. Motivated by the observation that our data often contains a small amount of “unbiased” examples that do not exhibit spurious correlations, we present new learning algorithms that better exploit these minority examples. On the other hand, we may want to directly augment such “unbiased” examples. While recent works along this line are promising, we show several pitfalls in the data augmentation approach.

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