Nayya raises $11 million to guide employee health benefits decisions with AI

Nayya, an insurance benefits management platform, today announced it has closed $11 million in a series A round led by Felicis Ventures. Nayya says the funds will be put toward product research and development as it seeks to acquire new talent and customers.

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Molecula raises $17.6 million for its AI feature store technology

Molecula, which is developing a cloud-based feature store for AI and machine learning workloads, today announced it has raised $17.6 million. The company says the proceeds will be put toward accelerating the launch of its managed cloud service and bolstering its sales and marketing efforts.

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Rapyd raises $300 million for its unified payments platform

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Rapyd, which is developing an all-in-one payments solutions platform, today announced it has raised $300 million, bringing the company’s total raised to over $450 million. CEO Arik Shtilman said the funds will be used to double the size of Rapyd’s engineering and product teams and explore acquisitions globally.
Virtual card spend is projected to grow to $355 billion by 2022, up from $136 billion in 2017, according to Accenture. With annual transaction volumes anticipated to surpass $9 trillion, businesses are increasingly investigating unified payment solutions.

Rapyd offers solutions on the web and mobile, including the ability to accept cash, bank transfers, e-wallets, local debit cards, and over 900 alternative payment methods in more than 100 regions. The platform supports disbursements in over 170 countries and multicurrency settlement to a single file across 65 currencies. Moreover, it delivers real-time foreign exchange, ID verification via document scanning, and anti-money laundering and counter financing terrorism (AML/CFT) services.
Rapyd offers an API, a software development kit that integrates with existing apps, and responsive designs for merchant checkout flows. The checkout solution can stand alone or coexist with gateways and local payment systems, while Rapyd’s white-label wallet platform ships with features targeting retail shops and rewards programs.
Rapyd competes with a number of well-established companies in a financial tech sector estimated at $147.37 billion as of year-end 2018, including Ayden, PayPal, and Stripe. But Rapyd hit around $100 million in revenue last year at a pre-money valuation of $1.2 billion, driven by the fees it levies on payments and multicurrency transactions (3.5% plus 30 cents for funds in and $1.50 plus 1% for exchanges).

Over the past year, Rapyd has expanded its network with new and existing products for Thailand, South Korea, Mexico, India, Brazil, and the U.K. It also acquired Iceland-based payment card service provider Korta, inked agreements with Visa and Mastercard, launched an anti-fraud service called Rapyd Protect, and partnered with payments technology company InComm to support cash bill pay and load solutions at participating retailers in the U.S.
“The demand for online payments has skyrocketed following the restrictions due to the effects of COVID-19, and as a company, we are well-placed to provide businesses across the globe with the solutions they need and to get them up and running fast,” Shtilman said in a statement. “To kick off 2021 with this substantial round of funding to further invest in our platform is a tremendous vote of confidence both in the growing need for local payment solutions that can be deployed at scale globally, and more specifically in our vision and company.”
Coatue led the series D funding round announced today, with participation from Spark Capital, Avid Ventures, FJ Labs, and Latitude. Current backers General Catalyst, Oak HC/FT, Tiger Global, Target Global, Durable Capital, Tal Capital, and Entrée Capital also contributed. Rapyd has offices in London and Mountain View, California.

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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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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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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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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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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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OpenAI debuts DALL-E for generating images from text

OpenAI today debuted two multimodal AI systems that combine computer vision and NLP: DALL-E, a system that generates images from text, and CLIP, a network trained on 400 million pairs of images and text. The photo above was generated by DALL-E from the text prompt “an illustration of a baby daikon radish in a tutu walking a dog.” DALL-E uses a 12-billion parameter version of GPT-3, and like GPT-3 is a Transformer language model. The name is meant to evoke the artist Salvador Dali and the robot WALL-E.

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iLobby raises $100 million to help enterprises manage on-site visitors

Enterprise-focused visitor management software provider iLobby has raised $100 million in a round of funding from Insight Partners. Despite the rapid push to embrace remote working in 2020, many — if not most — businesses will likely return to physical office spaces in some capacity once it’s safe to do so. And, of course, some businesses are not well-suited to fully remote work.

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Oxbotica raises $47 million to bring autonomy to vehicles in challenging environments

Oxbotica, a U.K.-based developer of autonomous vehicle software, today announced it has raised $47 million in a series B round led by BP Ventures. The startup says the funding will be used to accelerate commercial deployment of its software platform across key industries and markets.

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Accelerating Innovation: How Covid has prompted technological evolution within Healthcare

Every industry across the world is feeling the impact of the demands posed by Covid. While healthcare is undoubtedly the heaviest impacted sector, the rapid evolution of e-health throughout 2020 promises to carry a lasting beneficial impact on the industry. Significantly, innovations are occurring at break-neck speeds and all are being rolled out as a means of protecting from the dangers of the pandemic. 

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