Neuromorphic computing market is expected to reach USD 22.7 billion by 2027 and will witness its market growth at a rate of 52.04% in the forecast period of 2020 to 2027.\nSegmentation : Global Neuromorphic Computing MarketNeuromorphic computing market on the basis of offering has been segmented as hardware and software.\nDistributors and traders on marketing strategy analysis focusing on region wise needs in covid-19 pandemic is also added in the Neuromorphic Computing market report.\nThe last segment of COVID-19 impact chapter include recovery and major changes opted by major players involved in Neuromorphic Computing market.\nData Bridge Market Research set forth itself as an unconventional and neoteric Market research and consulting firm with an unparalleled level of resilience and integrated approaches.
"}}}},{"node":{"postTitle":"First Kenworth T680 Next Gen Goes to Werner","slug":"first-kenworth-t680-next-gen-goes-to-werner","publishDate":"None","createdLocal":"2021-05-29 14:30:50.573515","feedName":"Autonomous Trucks","postSummary":{"childMarkdownRemark":{"html":"Kenworth general manager and Paccar vice president Kevin Baney presented a plaque signifying the delivery of the first production T680 Next Gen to Werner Enterprises.\nPhoto: KenworthWerner Enterprises received the first Kenworth T680 Next Generation production truck during a ceremony at the Kenworth manufacturing plant in Chillicothe, Ohio.\nKenworth’s T680 Next Gen on-highway flagship expands on the success of the classic T680 model, Kenworth officials said in a press release.\nThe Kenworth T680 Next Gen provides drivers with the new customizable 15-inch digital display, next generation Kenworth SmartWheel, additional advanced driver assistance systems, forward lighting with signature LED headlamps, and a sleek aerodynamic design.\n\"Our team worked diligently and enthusiastically to produce this milestone Kenworth T680 Next Gen equipped with a 76-inch sleeper for Werner Enterprises.\"
"}}}},{"node":{"postTitle":"A Credit Score For Your Health: Startup Story Of FEDO","slug":"a-credit-score-for-your-health-startup-story-of-fedo","publishDate":"2021-05-29 07:30:00+00:00","createdLocal":"2021-05-29 14:30:50.124567","feedName":"Image Recognition","postSummary":{"childMarkdownRemark":{"html":"Founded by Arun Mallavarapu and Prasanth Madavana in 2017, Fedo is a health-tech startup that uses an AI-enabled system to generate a health score which is more like a Trans Union credit score for finance.\nThe Fedo health score was built by medical professionals and data scientists using 250+ medical studies, 2000+ plus quality controlled and academic and research documents from all over the world and analysing over 50 million global health records and 1.5 million claims data.\nIt also segments the FEDO score into three different categories – unhealthy (<400), moderately healthy (400-600), healthy (>600) so individual health can be better mapped.\nRoad aheadMallavarapu said Fedo will help in quantifying the health risk of people and will make the underwriting process much easier and faster.\nMaking Fedo Score the gold standard of health score globally.
"}}}},{"node":{"postTitle":"Continental AG, NVIDIA Corporation, Intel Corporation, Microsoft Corporation, Alphabet Inc., ZF Friedrichshafen AG, Robert Bosch GmbH, Valeo SA, – Clark County Blog","slug":"continental-ag-nvidia-corporation-intel-corporation-microsoft-corporation-alphabet-inc-zf-friedrichshafen-ag-robert-bosch-gmbh-valeo-sa-clark-county-blog","publishDate":"None","createdLocal":"2021-05-29 14:30:49.871784","feedName":"Autonomous Trucks","postSummary":{"childMarkdownRemark":{"html":"The global Artificial Intelligence In Transportation market provides in-depth market analysis as well as pictorial representations of key statistical findings.\nOverall, the report offers detailed coverage of the Artificial Intelligence In Transportation industry and presents main market trends.\nLikewise, the Artificial Intelligence In Transportation research report looks at a range of opportunities and risks.\nArtificial Intelligence In Transportation Market Top Players: Continental AG, NVIDIA Corporation, Intel Corporation, Microsoft Corporation, Alphabet Inc., ZF Friedrichshafen AG, Robert Bosch GmbH, Valeo SA, and more others.\n• Different product types and applications of the global industry, market revenue of each type & application by revenue.
"}}}},{"node":{"postTitle":"Should you quit Google Photos in 2021?","slug":"should-you-quit-google-photos-in-2021","publishDate":"2021-05-29 08:00:48+00:00","createdLocal":"2021-05-29 14:30:48.023728","feedName":"Image Recognition","postSummary":{"childMarkdownRemark":{"html":"Google Photos is a very smart way to store your photos(Image credit: Future)Rivals aside, Google Photos does plenty to justify a modest monthly fee.\nGoogle Photos integrates seamlessly across most devicesFlexibility is another reason to stick with Google Photos.\nEqually, for iPad or iPhone owners, Google Photos represents an excellent substitute for the default Photos app.\nGoogle Photos also plays nice with other Google products, such as Google Drive and Docs, which is handy if those form part of your online workflow.\nAnd with competitively priced expansion tiers, there’s little reason to quit and make a time-consuming switch away from Google Photos.
"}}}},{"node":{"postTitle":"High Speed Cameras Market – Growth, Trends, and Forecast (2020 – 2025) – The Shotcaller","slug":"high-speed-cameras-market-growth-trends-and-forecast-2020-2025-the-shotcaller","publishDate":"None","createdLocal":"2021-05-29 14:30:46.866614","feedName":"Image Recognition","postSummary":{"childMarkdownRemark":{"html":"The High-Speed Cameras market was valued at USD 563.25 million in 2019�and is expected to reach USD 1008.37 million by 2025, at a CAGR of 9.25% over the forecast period 2020�– 2025.\nHigh-speed cameras are the sophisticated version of normal digital cameras with high-resolution capacity and ability to capture ultra-high speed events.\n– Due to advanced features of high-speed cameras over other cameras, its demand is growing across industries.\n– However, long product replacement cycle coupled with the high cost of the high-speed camera are some of the factors which act as a restraint for the high-speed camera market.\nCompetitive LandscapeThe high-speed cameras market are highly competitive in nature because of the presence of the many international players who dominates the global market.
"}}}},{"node":{"postTitle":"Image Recognition Software Market Technology Advancement and Future Scope Till 2025 – The Courier","slug":"image-recognition-software-market-technology-advancement-and-future-scope-till-2025-the-courier","publishDate":"None","createdLocal":"2021-05-29 14:30:46.070743","feedName":"Image Recognition","postSummary":{"childMarkdownRemark":{"html":"Image Recognition Software Market research report documents in-depth analysis of the global and the regional markets on various parameters that drives the market.\nThe Image Recognition Software was valued at 12500 Billion US$ in 2021 and is projected to reach 17700 Billion US$ by 2025, at a CAGR of 5.1% during the forecast period.\nTrending factors that are impacting the Image Recognition Software MarketThe purpose of this study is to define the overview of the Rising Demand for Image Recognition Software Market with respect to market size, shares, sales patterns, and pricing structures.\nWhat are the key factors driving the Rising Demand for the Image Recognition Software Market?\nWhich are the global opportunities for expanding the Rising Demand for the Image Recognition Software Market?
"}}}},{"node":{"postTitle":"How ML Forms The Backbone Of Neo-Banking Startup StashFin","slug":"how-ml-forms-the-backbone-of-neo-banking-startup-stashfin","publishDate":"2021-05-29 12:30:00+00:00","createdLocal":"2021-05-29 14:30:45.386233","feedName":"Image Recognition","postSummary":{"childMarkdownRemark":{"html":"Then, the ML model extracts details to fill the registration form.\nStashFin uses basic models and standard APIs to examine the validity of official documents.\nOnce a credit is allocated, the ML model figures out any anomalies in the pattern of usage.\nFinally, StashFin uses ML models to help users make informed financial choices.\nFor instance, the platform guides users to nearest ATMs, and stores where Stashfin users can redeem their reward points.
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