Artificial Intelligence (AI) market size, share & COVID-19 impact analysis

Artificial Intelligence (AI) Market Size, Share & COVID-19 Impact Analysis, By Component (Hardware, Software, and Services), By Technology (Computer Vision, Machine Learning, Natural Language Processing, and Others), By Deployment (Cloud, On-premises), By Industry (Healthcare, Retail, IT & Telecom, BFSI, Automotive, Advertising & Media, Manufacturing, and Others) and Regional Forecast, 2020-2027

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Top business and technology trends in 2021

Let’s imagine customer experience in a post-Covid world. We should anticipate that the changes in consumer preferences and business models will outlast the immediate crisis. Once consumers acclimate to new digital or remote models, I expect some of them to change people’s expectations permanently — accelerating shifts already under way before the crisis.

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Value Investing. Step to the next level

If you are interested in value investing, you probably know that fundamental analysis is the most effective and at the same time, the most complicated way to determine the intrinsic value of a company. But this approach takes a lot of time and effort, limiting the investor’s horizons. To solve this problem, I started the COVANN project. Today, it is a cascade of artificial intelligence models whose task…

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Algorithmia 2020 state of enterprise Machine Learning

The main takeaway from the 2020 State of Enterprise Machine Learning survey is that a growing number of companies are entering the early stages of ML development, but challenges in deployment, scaling, versioning, and other sophistication efforts still hinder teams from extracting value from their ML investments.

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The Work of the Future – Building better jobs in an age of Intelligent Machines

Three years ago, robots, artificial intelligence (AI), and self-driving cars seemed to be coming fast. A widely cited study projected nearly half of all jobs in industrialized countries could soon be performed by robots or AI. One beer advertisement showed robots gleefully surpassing humans in running, bicycling, and golfing, but ended with a robot gazing wistfully through a window at people socializing in a bar. Humans would soon be outcompeted in every arena except social drinking, this ad seemed to say.

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White House: Recommendations for leveraging cloud computing resources for federally funded artificial intelligence research and development

The United States Government [will] sustain and enhance the scientific, technological, and economic leadership position of the United States in AI R&D and deployment through a coordinated Federal Government strategy … [that includes] better enabling the use of cloud computing resources for federally funded AI R&D.

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Google: The Language Interpretability Tool (LIT): Interactive Exploration and Analysis of NLP Models

As natural language processing (NLP) models become more powerful and are deployed in more real-world contexts, understanding their behavior is becoming increasingly critical. While advances in modeling have brought unprecedented performance on many NLP tasks, many research questions remain.

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Top 100 Machine Learning Companies

Machine learning can help predict user behavior, which helps businesses acquire new customers, optimize products and pricing, and increase customer engagement. Finding a machine learning company to meet your company’s needs, however, can be difficult. That’s why we’ve created this list of the best machine learning companies for you to review. Read through company descriptions, former clients, and notable projects to find the best fit for your business.

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AI/ML Applications in Law and Compliance

Some industries are a clear slam-dunk for AI/ML applications and some less so. The legal, regulatory, and compliance businesses (law firms, internal legal departments, and the contract review and regulatory compliance departments of heavily regulated industries) fall in this last category. This is a review of seven companies found by TopBots to be successful; pointing to opportunities others can follow.

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MIT: Building the algorithm commons: Who discovered the algorithms that underpin computing in the modern enterprise?

Analyzing this “Algorithm Commons” reveals that the United States has been the largest contributor to algorithm progress, with universities and large private labs (e.g., IBM) leading the way, but that U.S. leadership has faded in recent decades.

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