Software


Three interesting but little known programming languages

@machinelearnbot

The descriptions below are from Wikipedia. Julia is a high-level dynamic programming language designed to address the requirements of high-performance numerical and scientific computing while also being effective for general purpose programming.[1][2][3][4] Unusual aspects of Julia's design include having a type system with parametric types in a fully dynamic programming language and adopting multiple dispatch as its core programming paradigm. It allows for parallel and distributed computing; and direct calling of C and Fortran libraries without a compiler without glue code and includes best-of-breed libraries for floating-point, linear algebra, random number generation, fast Fourier transforms, and regular expression matching. Julia's core is implemented in C and C, its parser in Scheme, and the LLVM compiler framework is used for just-in-time generation of machine code.


Bug bounty hunter reveals DJI SSL, firmware keys have been public for years

ZDNet

An exasperated bug bounty hunter has revealed that drone maker DJI left everything from AWS credentials to private SSL keys on public forums. As reported by the Register, security researcher Kevin Finisterre discovered the Chinese firm had left the private keys of the DJI HTTPS domain on GitHub, exposed for all to see for roughly four years. To make matters worse, DJI had also made AWS credentials and firmware AES keys available for anyone to search for through the GitHub repository. Given these tools, as summarized by the researcher as a "full infrastructure compromise," a cyberattacker could have free reign to cause utter havoc for DJI, stealing data, compromising systems, and much more. The problems started in August, when the Chinese firm announced a bug bounty program that invited external researchers to find, submit, and be rewarded for responsibly disclosing vulnerabilities in the company's products.


Machine learning, containers and DevOps among McKinsey top 10 enterprise infrastructure trends

#artificialintelligence

Machine learning-optimised stacks, container-first architectures and DevOps for both software and hardware are among the key trends redefining enterprise IT infrastructure, according to a new report from McKinsey. The piece, authored by Arul Elumalai, Kara Sprague, Sid Tandon, and Lareina Yee, looks at what is changing and how companies need to fight back. Many of these have frequently been covered by this publication; some, like the public cloud going mainstream, are long overdue. Yet there is an interesting titbit here. Given the long-established leadership of Amazon Web Services (AWS), Microsoft, and Google in public cloud, McKinsey argues that their entrenched dominance will mean only organisations with'significant capital investment capabilities' will be able to compete in future.


2018-banking-financial-institution-predictions-forrester

#artificialintelligence

According to Forrester, 2018 will be a challenge for most financial services organizations, with external forces and internal stagnation impacting profits and the ability to remain competitive. In the report, "Predictions 2018: Financial Services Companies Get Serious About Digital Transformation," Forrester issues a dire warning to organizations not prepared for the external changes occurring in the marketplace, or not willing to make internal adjustments that will differentiate their organization. According to Forrester, "Most companies will spend 2018 working on new initiatives to better win, serve, and engage customers, as regulators continue to promote competition. But while 2018 will bring many digital upgrades, few financial services companies will do enough to truly differentiate their brands and remain relevant to customers." In this early forecast of the financial services environment for 2018, Forrester shares 16 predictions and recommendations regarding external threats, competitive opportunities and organizational shortcomings, as well as recommended strategic action plans for each prediction.


Edge, core, and cloud: Where all the workloads go

ZDNet

There is a strange and uneasy tension standing at the base of a wind turbine, amid a power generation farm full of dozens more. The air can seem still even though you can clearly see, and hear, the turbines moving. Indeed, the sound never dies down, although you're standing in precisely the space where you would most expect it to. With all these rotating blades the size of softball fields, it indeed feels and sounds like a place you'd expect to find something called "the edge." There's no methodology for any of the world's power grids to distinguish renewable power, such as wind-generated, from coal-based or hydroelectric power.


Fascinating Chaotic Sequences with Cool Applications

@machinelearnbot

Here we describe well-known chaotic sequences, including new generalizations, with application to random number generation, highly non-linear auto-regressive models for times series, simulation, random permutations, and the use of big numbers (libraries available in programming languages to work with numbers with hundreds of decimals) as standard computer precision almost always produces completely erroneous results after a few iterations -- a fact rarely if ever mentioned in the scientific literature, but illustrated here, together with a solution. It is possible that all scientists who published on chaotic processes, used faulty numbers because of this issue. This article is accessible to non-experts, even though we solve a special stochastic equation for the first time, providing an unexpected exact solution, for a new chaotic process that generalizes the logistic map. We also describe a general framework for continuous random number generators, and investigate the interesting auto-correlation structure associated with some of these sequences. References are provided, as well as fast source code to process big numbers accurately, and even an elegant mathematical proof in the last section.


Fascinating Chaotic Sequences with Cool Applications

@machinelearnbot

Here we describe well-known chaotic sequences, including new generalizations, with application to random number generation, highly non-linear auto-regressive models for times series, simulation, random permutations, and the use of big numbers (libraries available in programming languages to work with numbers with hundreds of decimals) as standard computer precision almost always produces completely erroneous results after a few iterations -- a fact rarely if ever mentioned in the scientific literature, but illustrated here, together with a solution. It is possible that all scientists who published on chaotic processes, used faulty numbers because of this issue. This article is accessible to non-experts, even though we solve a special stochastic equation for the first time, providing an unexpected exact solution, for a new chaotic process that generalizes the logistic map. We also describe a general framework for continuous random number generators, and investigate the interesting auto-correlation structure associated with some of these sequences. References are provided, as well as fast source code to process big numbers accurately, and even an elegant mathematical proof in the last section.


Introducing STACK That, a New Podcast from HPE HPE Newsroom

#artificialintelligence

Ever wonder about how the technology behind autonomous driving can be applied to businesses in other sectors? What about open source communities and their ability to drive innovation? And what about the cloud -- will it really consume the world? We explore these topics and more in our newest podcast -- STACK That. STACK That dives into the world of emerging trends, taking a look at what's hot, what's secure and how you can leverage new technologies for your business' benefit.


Firmware Update For The New Amazon Echo Delivers Better Audio Quality

International Business Times

The second-generation Amazon Echo smart speaker has received a new firmware update that fixes an audio issue. The firmware update has finally pumped up the bass of the Echo speaker, which is now able to deliver better sound quality. The second generation Amazon Echo received mostly positive reviews when it was first released on Oct. 31. However, many users as well as reviewers complained about the lack of bass that the speaker was able to output compared to the first generation Echo speaker. The Verge said on its initial review that the new Echo speaker sounded "thin and flat," while CNET said that it had "weak bass at high volumes."


The Turing Test And The Turing Machine

#artificialintelligence

This week's milestones in the history of technology include Microsoft unleashing MS-DOS and Windows, the first Turing Test and the introduction of the Turing Machine, and IBM launching a breakthrough in computer storage technology. IBM and Microsoft sign a contract under which Microsoft will develop an operating system for IBM's upcoming personal computer (PC). To meet its obligations, Microsoft acquired an existing product developed by a Seattle company for the Intel 8086 CPU card, originally called Quick and Dirty Operating System (QDOS). IBM released the Microsoft operating system with its first PC in 1981. Within a year Microsoft licensed the software (MS-DOS) to over 70 other companies, making it the dominant PC software company for years to come.