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Category: Computing & data (Page 67 of 80)

Computing and data is a broad category. Our coverage of computing is largely limited to software, and we are mostly focused on unstructured data, semi-structured data, or mixed data that includes structured data.

Topics include computing platforms, analytics, data science, data modeling, database technologies, machine learning / AI, Internet of Things (IoT), blockchain, augmented reality, bots, programming languages, natural language processing applications such as machine translation, and knowledge graphs.

Related categories: Semantic technologies, Web technologies & information standards, and Internet and platforms.

Microsoft open sources Fluid Framework – announces Fluid Workspaces and Fluid Components for Office 365

Microsoft introduced the first way for end users to experience the Fluid Framework in Microsoft 365 with the upcoming availability in preview of Fluid Workspaces and Fluid Components. Fluid Workspaces and Components work like the web to bring the right level of context and connection as well as seamlessly capture follow-ups in-line and edit action items with an entire team. Fluid Components and Fluid Workspaces will become available in more places over time. This initial public preview includes basic text, tables, lists, agendas and action items. These Fluid components will be available for creation in Outlook for the web and Office.com. Microsoft also announced the Fluid Framework will be made open source and hosted as a repository available on GitHub in the next month, allowing developers and creators to use infrastructure from Fluid Framework in their own applications. Coupled with the release of additional developer documentation and tooling, developers can work alongside Microsoft to create and evolve Fluid Framework as it is developed. Developers can take advantage of JavaScript APIs that give them access to collaborative, shared data structures which can be used to power collaborative experiences. They also can create Fluid components — elements that can be reused within Microsoft 365 and across applications.

https://www.microsoft.com/en-us/microsoft-365/blog/2020/05/19/microsoft-teams-fluid-framework-new-microsoft-365/

Hugging Face dives into machine translation with release of 1,000 models

Hugging Face is taking its first step into machine translation this week with the release of more than 1,000 models. Researchers trained models using unsupervised learning and the Open Parallel Corpus (OPUS). OPUS is a project undertaken by the University of Helsinki and global partners to gather and open-source a wide variety of language data sets, particularly for low resource languages. Low resource languages are those with less training data than more commonly used languages like English.

Models trained with OPUS data now make up the majority of models provided by Hugging Face and the University of Helsinki’s Language Technology and Research Group the largest contributing organization. Before this week, Hugging Face was best known for enabling easy access to state-of-the-art language models and language generation models, like Google’s BERT, which can predict the next characters, words, or sentences that will appear in text. The Hugging Face Transformers library for Python includes pretrained versions of advanced and state-of-the-art NLP models like versions of Google AI’s BERT and XLNet, Facebook AI’s RoBERTa, and OpenAI’s GPT-2.

https://huggingface.co h/t: VentureBeat

Amazon releases Kendra to solve enterprise search with AI and machine learning

Amazon Web Services announced the general availability of Amazon Kendra, an enterprise search service. Amazon Kendra uses machine learning to enable organizations to index all of their internal data sources, make that data searchable, and allow users to get precise answers to natural language queries. When users ask a question, Amazon Kendra uses finely tuned machine learning algorithms to understand the context and return the most relevant results, whether that be a precise answer or an entire document. For example, businesses can use Amazon Kendra to search internal documents spread across portals and wikis, research organizations can create a searchable archive of experiments and notes, and contact centers can use Amazon Kendra to find the right answer to customer questions across the complete library of support documentation. Amazon Kendra requires no machine learning expertise and can be set up completely within the AWS Management Console. Amazon Kendra provides a wide range of native cloud and on-premises connectors to popular data sources such as SharePoint, OneDrive, Salesforce, ServiceNow, Amazon Simple Storage Service, and relational databases.

https://aws.amazon.com/kendra/ ht: Techcrunch

walled-garden

In the context of the the internet “walled-garden” refers to privately controlled proprietary sections of the internet as opposed to the world wide web vision of an open web. Facebook is an obvious example.

blockchain

A blockchain is a decentralized, distributed, and oftentimes public, digital ledger consisting of records called blocks that is used to record transactions across many computers so that any involved block cannot be altered retroactively, without the alteration of all subsequent blocks.[1][18] This allows the participants to verify and audit transactions independently and relatively inexpensively.[19] A blockchain database is managed autonomously using a peer-to-peer network and a distributed timestamping server. They are authenticated by mass collaboration powered by collective self-interests.[20] Such a design facilitates robust workflow where participants’ uncertainty regarding data security is marginal. The use of a blockchain removes the characteristic of infinite reproducibility from a digital asset. It confirms that each unit of value was transferred only once, solving the long-standing problem of double spending. A blockchain has been described as a value-exchange protocol.[21] A blockchain can maintain title rights because, when properly set up to detail the exchange agreement, it provides a record that compels offer and acceptance.

Tim Berners-Lee

Sir Timothy John Berners-Lee OM KBE FRS FREng FRSA FBCS, also known as TimBL, is an English computer scientist best known as the inventor of the World Wide Web. He is a Professorial Fellow of Computer Science at the University of Oxford and a professor at the Massachusetts Institute of Technology.

He is the co-founder and CTO of Inrupt.com, a tech start-up which uses, promotes and helps develop the open source Solid platform. Solid aims to give people control and agency over their data, questioning many assumptions about how the web has to work. Solid technically is is new level of standard at the web layer, which adds things never put into the original spec, such as global single sign-on, universal access control, and a universal data API so that any app can store data in any storage place. Socially Solid is a movement away from much of the issues with the current WWW, and toward a world in which users are in control, and empowered by large amounts of data, private, shared, and public.

Sir Tim is the Director of the World Wide Web Consortium (W3C), a Web standards organization founded in 1994 which develops interoperable technologies (specifications, guidelines, software, and tools) to lead the Web to its full potential. He is a Director of the World Wide Web Foundation which was launched in 2009 to coordinate efforts to further the potential of the Web to benefit humanity.

open web

The ‘open web’ refers to the non-proprietary portion of the world wide web (WWW). That is, the portion that is free and freely accessible, as it was when it was launched. The opposite of the open web is a proprietary “walled-garden”, such as Facebook.

Document Computing

‘Document computing’ was a term used to cover a collection of technologies that emerged as computer, or electronic publishing became a growing industry late 1980s and early 1990s. The idea was to differentiate the creation, management and delivery of unstructured data from the traditional and still prevalent structured data orientation of computing applications. It was one of the keynote topics at the first Documation conference in 1994 . Also see the more current, largely overlapping ‘content technology’.

Also see:

Gilbane Report Vol 6, Num 1 — Document Computing – Is This Our Business?

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