Algorithmic Trading with Artificial Intelligence: In Defense of the US Dollar

About 3,500 publicly listed companies can trade in the US Stock Market, but more than 80% of the daily price moves are algorithmic. Financial trading has evolved as a traditional brain-driven rationalism to a data-driven empiricism. Below I walkthrough a thorough justification of selecting the US Dollar for Algorithmic Trading with Artificial Intelligence because the reserve currency of the US Dollar is widely misunderstood. Let’s first begin with operational definitions.

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5 Ways AI is Improving Supermarkets

COVID-19 is ruthlessly shaping ordinary stores into supermarkets of the future. They must accommodate all the new grocery shopping trends from panic-buying to delivery and pickup options, all with disrupted supply chains. Grocery retailers are responding differently. Some are cutting back on the number of products they sell, some are skipping distributors and contacting product manufacturers directly, and some are giving their brick-and-mortar stores a complete digital overhaul. No matter which line of action your company has selected, AI retail solutions will enhance your operations significantly.

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Nike uses AI to directly sell to Customers, others will ‘Just Do It’ soon


Celect is a predictive analytics company based in Boston, USA, which Nike acquired on the 25th of August 2019. This acquisition allowed Nike to integrate their inventories with the website and app of the company. This not only claimed to allow a more efficient interface with the customers, but also more efficient inventory management, leading to a reduction in operating costs of the company. This was part of Nike’s project to sell its products directly to the customers through its online retail platforms.

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[IBM Survey] Global Business AI Adoption Flat in 2020, but growth expected to rebound

think IBM

That’s the conclusion of a new “Global AI Adoption Index 2021” report from IBM’s Institute for Business Value and the IBM Watson business unit that includes input on AI plans and challenges from some 5,501 business decision-makers in 15 markets around the world. The report was released May 11 (Tuesday) as part of IBM’s Think 2021 virtual conference. The 13-page report, which was conducted by market research firm Morning Consult for IBM, found that about one-third of the respondents reported that their companies are using AI, while 43 percent said their companies accelerated their rollouts of the technology due to the pandemic.

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ServiceNow acquires Lightstep to gain Observability Platform

Roadrunner service dashboard

ServiceNow today announced it has acquired Lightstep as part of an effort to add an observability platform to its IT operations portfolio. Terms of the deal, expected to close this quarter, were not disclosed. The Change Intelligence observability platform from Lightstep is based on a time-series database that is capable of processing a trillion events each day. It was built by the same team that created Monarch, the globally distributed in-memory time series database system that Google employs to monitor its applications and systems.

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Hill International and partner to advance Artificial Intelligence (AI) in improving Construction jobsite safety

Hill International

Hill International and announced they are bringing best-in-class technologies – including artificial intelligence (AI) and sensor fusion – to construction companies focused on improving worker health and safety. This collaboration, enabled through the Qualcomm Smart Cities Accelerator Program and Qualcomm IoT Services Suite, will bring Everguard’s Sentri360 platform and ecosystem to Hill International customers, creating a paradigm shift from a reactive to a proactive approach to prevent jobsite injuries and accidents.

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Human in the loop: (how) will it work?

Human in the loop

Artificial intelligence (AI) is used more and more in real-life business situations. Many businesses implement AI technology to reduce operational costs, increase efficiency, grow revenue, and improve customer experience. But sometimes, they are confronted with ill-behaving AI. AI decisions can be biased, discriminatory, or even malicious. The need to keep AI in check is real and human supervision seems necessary to restrain AI.

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5 reasons why companies need to develop and prioritize their AI Business strategies now!

Man playing chess

In 2018, a study by MIT Sloan Management Review exposed that 58% of companies believed AI will significantly change their business models by 2023. And in 2019, a Forbes article that indicated 73% of top U.S. executives have a goal to increase investment in technology dramatically. Now more than ever, companies recognize that AI is essential to their business growth.

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Brightflag sets standard for Legal AI, invests 100,000 hours in Machine Learning Model


Brightflag, the AI-powered enterprise legal management company, surpassed a significant product milestone with 100,000 hours now invested in the development and training of its proprietary machine learning model by its in-house team of data science and corporate legal experts. The insights generated by Brightflag’s AI have been validated and applied by hundreds of corporate legal teams while managing live legal matters.

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Applying Design & Agile thinking to your Data Science project — Part 2

Think of a data-driven solution as a puzzle piece. This piece needs to have a suitable shape and color to fit into a bigger puzzle. Our world is this puzzle, which is not complete yet. We want to make a suitable puzzle piece and then place it into the puzzle to make it more complete. In other words, we want to bring a suitable solution to this world. Designing and bringing an appropriate solution can be complex. Design Thinking makes the shape of the solution, while Agile Thinking ensures its implementation, taking the outcome of the Design Thinking.

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Applying Design & Agile thinking to your Data Science project — Part 1

Imagine the world as a gigantic puzzle with millions of pieces. The puzzle is still not complete, some pieces are already placed, but there is still space for new ones. We want to make our solution a puzzle piece that fits into this huge puzzle, but we do not know-how. Design and Agile Thinking help us shape our solution into a puzzle piece that fits into this huge puzzle. Creating a data product can be chaotic and hard. My advice is to not give up easily when it at first seems as if there is no solution, but to keep trying to build the pieces!

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Why Board Directors And CEOs Need To Learn AI Knowledge Foundations: Building AI Leadership Brain Trust Is A Business Imperative: Are You Ready?

Why Fortune 1000 Leaders need to build AI Brain Trust? In reviewing over 200 board of director compositions on the Fortune 1000, many of them do not have sufficient technology depth and knowledge expertise. The majority have operations knowledge particular in finance, legal and have often held a CEO or high profiled leadership role in a prior company. The major of larger companies all have a technology strategy and risk committee working with their CIO and Cybersecurity or Risk officers, but if you look across the broader board director skill knowledge on the depth of AI and digital transformation leadership skills and solid execution experiences, you will find less relevant and current knowledge know-how.

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The Analytics Lifecycle, Analytics Maturity, Analytics Canvas, and Absorptive Capacity

Analytics lifecycle

In today’s article, we will learn about four main concepts that are important to consider when starting to lead analytical projects. These concepts include tools and frameworks that will assist you and your team to structure your analytics projects in a professional manner to consider all aspects involved in the use case. These collaboration tools will guide you from getting the raw data to the final step of making an important decision that will affect your company on a big scale.

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Video Highlights: Business Analyst or Data Scientist?

Head wireframe

What field to choose if you want to launch a Startup in the future. This Data Science Salon (DSS) video is presented by Julia Khan, Vice President of Analytics at SEMrush. This presentation will be most useful for young data professionals, who are trying to choose their own path within the wide range of specializations inside the data science field.

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