How Industries will move past the Pandemic and thrive in 2021 using AI

The response from COVID-19’s gradual recovery will be top of mind for nearly every firm and industry in 2021. Some businesses may become stagnant or never recover. Others will view the shakeup as an unprecedented opportunity to understand and improve their data and analytical assets, operationalize and update their model production process, and reassure customers that their AI can be trusted.

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What this bald eagle and neural network depiction have to do with future U.S. AI strategy

The White House Office of Science and Technology Policy (OSTP) today announced the launch of the National Artificial Intelligence Initiative Office, an organization that will coordinate and oversee national AI policy initiatives for the United States government. “The Office is charged with overseeing and implementing the United States national AI strategy and will serve as the central hub for federal coordination and collaboration in AI research and policymaking across the government, as well as with private sector, academia, and other stakeholders,” according to a White House statement.

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Google trained a trillion-parameter AI language model

Parameters are the key to machine learning algorithms. They’re the part of the model that’s learned from historical training data. Generally speaking, in the language domain, the correlation between the number of parameters and sophistication has held up remarkably well. For example, OpenAI’s GPT-3 — one of the largest language models ever trained, at 175 billion parameters — can make primitive analogies, generate recipes, and even complete basic code.

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Workato raises $110 million for its business workflow automation platform

Workato, which offers an integration and automation platform for businesses, today announced it has raised $110 million at a post-money valuation of $1.7 billion. The company says it will put the funds toward product innovation and technology development, expanding its customer success program, launching its first user conference in 2021, and investing in scaling teams in the U.S. and internationally.

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M-Files raises $80 million for AI that automates enterprise information management

M-Files announced it has raised $80 million as the Finnish company develops AI that automates the messy process of organizing and tracking internal documents and data for enterprises. Bregal Milestone led the round, which included previous investors Partech, Tesi, and Draper Esprit.

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Pegasystems acquires Qurious.io to apply speech analytics to customer service

Pegasystems announced today it has acquired Qurious.io, a provider of a cloud service that analyzes voice calls in real time to enable customer service representatives to better determine their next best course of action. Terms of the deal were not disclosed.

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Komodo raises $44 million and acquires Mavens to bring data-driven insights to life sciences

Komodo Health, a company that is meshing big data, AI, and analytics to create a digital map of the U.S. health care system, announced that it quietly secured a $44 million cash injection last year in a series D round of funding led by Iconiq.

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Dina raises $7 million for its AI-powered at-home care platform

Dina, a Chicago-based startup developing an AI-powered at-home care platform, today announced it has raised $7 million. The company says the capital will be used to expand its products and support its mission to help the health care industry transition to in-home care.

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Ambarella unveils 8K AI vision processor for car, drone, and robot cameras

Ambarella has unveiled the CV5 AI Vision Processor to handle 8K image processing for car, consumer, crone, and robot cameras. The new 5-nanometer camera system on chip (SoC) is the latest in the company’s CVflow family, and it consumes under 2 watts of power. The chip is about 4 times more powerful than the previous-generation chip.

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Equifax will pay $640 million for Kount’s AI-driven identity and fraud prevention tools

Equifax today announced that it would pay $640 million to acquire Kount, a company that uses artificial intelligence to drive its fraud prevention and digital identity services. In a press release, Equifax executives said the deal would allow the company to further expand into these markets. Kount uses AI to analyze 32 billion transactions across 17 billion devices. As the system builds its intelligence, it is shifting from only analysis to predictive modes with the goal of helping companies prevent digital fraud.

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Blue Prism launches venture fund to expand global use of cloud RPA

Last April, robotic process automation firm Blue Prism bolstered its own balance sheet with a $124 million financing round, enabling the maker of enterprise-class software robots to expand its suite of AI agents and dashboards. Now the company is launching a venture fund to bring RPA technologies to new clients, starting with the Asia-Pacific region before expanding to “the entire globe.”

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Stanford researchers propose AI that figures out how to use real-world objects

One longstanding goal of AI research is to allow robots to meaningfully interact with real-world environments. In a recent paper, researchers at Stanford and Facebook took a step toward this by extracting information related to actions like pushing or pulling objects with movable parts and using it to train an AI model. For example, given a drawer, their model can predict that applying a pulling force on the handle would open the drawer.

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Glia raises $78 million to digitize customer service interactions

Customer service startup Glia today announced it raised $78 million. The funds will be used to expand departments across its organization, the company says, with a focus on product development and strategic acquisitions. Multimodality is fast becoming the norm in the $350 billion customer service industry.

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U.K. competition regulator to probe Nvidia’s $40 billion Arm takeover

(Reuters) — Britain’s competition regulator said on Wednesday it would start an investigation into Nvidia Corp’s $40 billion deal to buy UK-based chip designer Arm Holdings. The Competition and Markets Authority (CMA) said it was “likely to consider whether, following the takeover, Arm has an incentive to withdraw, raise prices or reduce the quality of its IP licensing services to Nvidia’s rivals.”

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AI models from Microsoft and Google already surpass human performance on the SuperGLUE language benchmark

In late 2019, researchers affiliated with Facebook, New York University (NYU), the University of Washington, and DeepMind proposed SuperGLUE, a new benchmark for AI designed to summarize research progress on a diverse set of language tasks. Building on the GLUE benchmark, which had been introduced one year prior, SuperGLUE includes a set of more difficult language understanding challenges, improved resources, and a publicly available leaderboard.

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Intel launches RealSense ID for on-device facial recognition

Intel today launched the newest addition to RealSense, its product range of depth and tracking technologies designed to give machines depth perception capabilities. Called RealSense ID, it’s an on-device solution that combines an active depth sensor with a machine learning model to perform facial authentication.

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Hootsuite acquires Sparkcentral to unify and automate social customer service

Social media management stalwart Hootsuite has acquired Sparkcentral, a messaging app-focused customer engagement platform that offers virtual agents and automated message distribution. Terms of the deal were not disclosed. The acquisition comes as more companies seek tools that will help them support customers online while working collaboratively with team members based in any number of locations.

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Dremio raises $135 million to help companies rapidly analyze data

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Dremio, a startup offering tools to help streamline and curate data, today announced that it raised $135 million in series D funding at a post-money valuation of $1 billion. The company says it’ll use the funds, which come nine months after a $70 million round, to invest in cloud data lake technologies that could benefit businesses looking to connect, analyze, and process data while accelerating database queries. Specifically, Dremio plans to expand its engineering centers of excellence and grow its customer-facing organizations to keep pace with new customer acquisitions.
Due to its scalability, low cost, and simplicity of management, cloud data lake storage has become the destination of choice for storing high volumes of data. According to a recent Allied Market Research report, the global data warehousing market size was valued at $18.61 billion in 2017, growing at a compound annual growth rate of 8.2% from 2018 to 2025. However, to audit that data, it has to be moved and copied into proprietary data warehouses, a process that can become costly, complex, and inflexible.

MapR veterans Jacques Nadeau and Tomer Shiran founded Santa Clara, California-based Dremio in 2015 to solve this challenge. CEO Billy Bosworth tells VentureBeat that Tomer, a former product manager at Microsoft who’s held engineering and research roles at IBM and HP, saw the rise of public clouds like Amazon Web Services, Microsoft Azure, and Google Cloud Platform as an opportunity to reinvent big data technology and develop a cloud data lake engine, enabling companies with large storage volumes to rapidly analyze their data.
“Dremio customers are running millions of queries per day for high concurrency BI with tools like Tableau and Power BI, ad-hoc data processing, and mission-critical dashboards. This is made possible by fundamentally simplifying the workflow for data engineers who are already centralizing data from many sources into cloud stores like AWS S3 and Microsoft ADLS,” Bosworth said in an email interview with VentureBeat. “With Dremio, that data does not need to be further moved or copied into data warehouses for analytics; instead, the full data set is available directly in native cloud storage.”
Dremio offers a virtualization toolkit that bridges the gaps among relational databases, Hadoop, NoSQL, ElasticSearch, and other data stores, connecting to business intelligence software as if it were a primary data source and querying it via SQL. (SQL is the domain-specific language designed for stream processing and managing data held in a relational database management system.) The startup’s eponymous platform maintains a catalog of sources, physical and virtual datasets, and datasets’ lineage, making it easier to search and find datasets and see how data are being transformed.

Above: A few of the data sources Dremio’s platform supports.
Image Credit: Dremio

Dremio is available in an open source Community edition as well as a commercial Enterprise edition. It runs in the cloud via Kubernetes or in a Hadoop cluster, and subscription pricing scales based on the number of nodes to which Dremio is deployed.
Joining capabilities native to Dremio enable data lakes to benefit from other stores, including Oracle, SQL Server, and PostgreSQL databases. And Dremio automatically detects schemas and supports cloud data lakes in Amazon S3 and other cloud storage providers, leveraging the Apache Arrow data structure to speed up performance by 1,000 times, the company claims.
Thanks to features like automatic failover, Dremio can automatically select new nodes in the event of node and instance cluster failures. The platform’s dynamic access, moreover, delivers programmatic security controls through integration with Kerberos, LDAP, and other centralized providers.
On the AI side of the equation, Dremio taps machine learning to recommend datasets to users and adapt catalogs in response to changes in schema and execution. It also algorithmically caches and indexes metadata as needed, in real time and on the fly.
Asked whether the pandemic has affected business, Bosworth said it hadn’t, pointing to Dremio’s 60% growth in headcount since March. Other than a delayed sales cycle when the startup’s customers transitioned to working from home, Dremio weathered the storm well, growing its customer base to 100 companies — a majority of which are from the Forbes Global 2000 — with over 75,000 users.
“Data analytics has always been important to our customers. This year, it has become more imperative than ever as we navigate this pandemic,” Bosworth said. “Dremio was already a distributed company, so we did not experience any loss of productivity.”
Dremio’s series D round announced today was led by Sapphire Ventures and included participation from existing Dremio investors Insight Partners, Lightspeed Ventures, Norwest Venture Partners, Redpoint Ventures, and Cisco Investments. As of today, the company has about 160 employees — a number it expects will double by the end of 2021 — and has raised $247 million in venture capital.

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