Archive for the ‘Machine Learning’ Category

Quantiphi Wins Google Cloud Social Impact Partner of the Year Award – AiThority

Awarded to recognize Google Cloud partners who have made a positive impact on the world

Quantiphi, an award-winning applied artificial intelligence and data science software and services company, announced today that it has been named 2019 Social Impact Partner of the Year by Google Cloud. Quantiphi was recognized for its achievements for working with nonprofits, research institutions, and healthcare providers, to leverage AI for Social Good.

We are believers in the power of human acumen and technology to solve the worlds toughest challenges. This award is a recognition of our mission driven culture and our passion to apply AI for social good, said Asif Hasan, Co-founder, Quantiphi. Partnering with Google Cloud has given us the opportunity to work with the worlds leading nonprofit, healthcare and research institutions and we are truly humbled by this recognition.

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Were delighted to recognize Quantiphis commitment to social impact, said Carolee Gearhart, Vice President, Worldwide Channel Sales at Google Cloud. By applying its capabilities in AI and ML to important causes, Quantiphi has demonstrated how Google Cloud partners are contributing to positive change in the world.

A few initiatives that helped Quantiphi earn this recognition:

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Quantiphi previously earned the Google Cloud Machine Learning Partner of the Year twice in a row for 2018 and 2017 and is a premier partner for Google Cloud and holds Specializations in machine learning, data analytics and marketing analytics.

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Quantiphi Wins Google Cloud Social Impact Partner of the Year Award - AiThority

Tyto Care Raises $50M to Expand Its Telehealth Exam Offering Globally – AiThority

The growth round doubles the telehealth companys total funding after serving over 100 health organizations, thousands of clinicians, and hundreds of thousands of patients in 2019

Tyto Care, the healthcare industrys first all-in-one modular device and telehealth platform for on-demand, remote medical examinations, announced that it has raised $50Min an oversubscribed round co-led by Insight Partners, Olive Tree Ventures,and Qualcomm Ventures LLC with participation from previous investors, bringing the companys total funding to over$105M. The additional funding comes as Tyto Care experiences surging demand with rapid global telehealth adoption, having witnessed 3X growth in sales in 2019 alone.

The funding will allow Tyto Care to continue to expand commercialization throughout the U.S.,EuropeandAsiaas well as to introduce new advanced product capabilities including AI and machine learning-based home diagnostics solutions and other patented technologies.

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Tyto Care has experienced double-digit telehealth utilization, over 10 times higher than standard virtual care programs, which see less than 5% utilization on average. In the wake of COVID-19, hospitals and health organizations around the world are further expanding their use of Tyto Cares telehealth solution to remotely examine quarantined patients in hospitals and isolated patients at home.

Tyto Cares solution enables remote medical exams of the lungs, heart, throat and ears, among other exams and vitals, allowing healthcare organizations to protect providers and avoid exposure during the COVID-19 pandemic. It also enables families and the general population to receive care without entering medical facilities, preventing the spread of the virus and significantly reducing the increased burden on already overworked health organizations. To meet the skyrocketing demand, Tyto Care is currently expediting production to fulfill three times more devices than originally forecasted for the coming quarters.

Over the past two years, Tyto Care has increased momentum faster than ever before and is playing a leading role in changing how people receive healthcare. Telehealth is heeding the call of the COVID-19 pandemic and we are proud that our unique solution is aiding health systems and consumers around the world in the fight against the virus, saidDedi Gilad, Co-Founder and CEO of Tyto Care. This new funding comes at a pivotal moment in the evolution of telehealth andwill enable us to continue to transform the global healthcare industry with the best virtual care solutions. We look forward to further expanding the reach of telehealth and introducing new solutions as demand for remote care continues to soar.

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The on-demand era has finally reached healthcare, saidJeff Horing, co-founder and Managing Director at Insight Partners. Adoption of telehealth is at an all-time high and as the only solution on the market with diagnostic capabilities that can deliver clinic-quality remote care, Tyto Care is significantly disrupting the health ecosystem. As a partner that empowers fast-growing ScaleUp software companies transforming daily life, we are excited to work with Tyto Care to help usher in the next generation of healthcare.

Olive Tree Ventures, a digital healthfund, is ecstatic to partner with Tyto Care to accelerate the adoption of global telehealth solutions. We experienced first-hand the value of Tyto Cares solution in the Israeli market. As digital health investors, we strongly believe in the promise of telehealth and are excited to collaborate with the visionary management at Tyto Care, saidAmir Lahat, General Partner, Olive Tree Ventures.

Tyto Care witnessed threefold growth in 2019 and is working with hundreds of hospitals and over 100 health organizations including health systems, payers and strategic partners, primarily inNorth America,EuropeandIsrael. The company served hundreds of thousands of patients and performed over 200,000 telehealth exams in 2019 alone, a testament to the growing adoption of its virtual medical exam solution as an efficient, convenient and high-quality means of delivering primary care.

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Tyto Care Raises $50M to Expand Its Telehealth Exam Offering Globally - AiThority

Machine Learning in Finance Market Provides in-depth analysis of the Industry, with Current Trends and Future Estimations to Elucidate the Investment…

TheGlobal Machine Learning in Finance MarketResearch report provided by Market Expertz is a detailed study report of theGlobal Machine Learning in Finance Market, which covers all the necessary information required by a new market entrant as well as the existing players to gain a deeper understanding of the market. The Global Machine Learning in Finance Marketreport is segmented in terms of regions, product type, applications, key players, and several other essential factors. The report also covers the global market scenario, providing deep insights into the cost structure of the product, production, and manufacturing processes, and other essential factors.

The report also covers the global market scenario, highlighting the pricing of the product, production and consumption volume, cost analysis, industry value, barriers and growth drivers, dominant market players, demand and supply ratio of the market, the growth rate of the market and forecast till 2026.

Get PDFSample copy of Machine Learning in Finance Market Report2020, Click [emailprotected] https://www.marketexpertz.com/sample-enquiry-form/86930

The report includes accurately drawn facts and figures, along with graphical representations of vital market data. The research report sheds light on the emerging market segments and significant factors influencing the growth of the industry to help investors capitalize on the existing growth opportunities.

In market segmentation by manufacturers, the report covers the following companies-

Ignite LtdYodleeTrill A.I.MindTitanAccentureZestFinanceOthers

Get to know the business better:The global Machine Learning in Finance market research is carried out at the different stages of the business lifecycle from the production of a product, cost, launch, application, consumption volume and sale. The research offers valuable insights into the marketplace from the beginning including some sound business plans chalked out by prominent market leaders to establish a strong foothold and expand their products into one thats better than others.

In market segmentation by types of Machine Learning in Finance, the report covers-

Supervised LearningUnsupervised LearningSemi Supervised LearningReinforced LeaningOthers

In market segmentation by applications of the Machine Learning in Finance, the report covers the following uses-

BanksSecurities CompanyOthers

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A conscious effort is made by the subject matter experts to analyze how some business owners succeed in maintaining a competitive edge while the others fail to do so makes the research interesting. A quick review of the realistic competitors makes the overall study a lot more interesting. Opportunities that are helping product owners size up their business further add value to the overall study.

With this global Machine Learning in Finance market research report, all the manufacturers and vendors will be aware of the growth factors, shortcomings, opportunities, and threats that the market has to offer in the forecast period. The report also highlights the revenue, industry size, types, applications, players share, production volume, and consumption to gain a proper understanding of the demand and supply chain of the market.

Years that have been considered for the study of this report are as follows:

Major Geographies mentioned in this report are as follows:

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The complete downstream and upstream essentials and value chains are carefully studied in this report. Current trends that are impacting and controlling the global Machine Learning in Finance market growth like globalization, industrialization, regulations, and ecological concerns are mentioned extensively. The Global Machine Learning in Finance market research report also contains technical data, raw materials, volumes, and manufacturing analysis of Machine Learning in Finance. It explains which product has the highest penetration in which market, their profit margins, break-even analysis, and R&D status. The report makes future projections for the key opportunities based on the analysis of the segment of the market.

Key features of the report:

What does the report offer?

For more details on the Machine Learning in Finance Report, click here @ https://www.marketexpertz.com/industry-overview/machine-learning-in-finance-market

Well-versed in economics and mergers and acquisitions, Jashi writes about companies and their corporate stratagem. She has been recognized for her near-accurate predictions by the business world, garnering trust in her written word.

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Machine Learning in Finance Market Provides in-depth analysis of the Industry, with Current Trends and Future Estimations to Elucidate the Investment...

Call for netizens to demand scraped pics from Clearview, ML weather forecasts, and Star Trek goes high def with AI – The Register

Roundup Hello Reg readers. Here's a quick roundup of bits and pieces from the worlds of machine learning and AI.

Are you in Clearview's database? Probably: Folks covered by the EUs GDPR, the California Consumer Privacy Act, and similar laws, can ask Clearview the controversial face-recognition startup that scraped three billion images of people from the internet to reveal what images it may have of you in its database and delete them.

Thats what Thomas Smith, co-founder and CEO of Gado Images, a computer vision startup, did for OneZero. As a resident of America's Golden State, Smith filled out a California Consumer Privacy Act (CCPA) form demanding Clearview send him the profile they had on him. He could see what images Clearview had managed to scrape from the internet, and where they got them from.

He had to provide Clearview with a picture of himself along with a copy of his drivers license. Clearview had collected 10 images of Smith; some were taken from social media, such as Facebook, but it also went as far as to download snaps from he and his wifes personal blog and a Python meetup group in San Francisco. One of the 10 images, however, looks like a case of mistaken identity.

The images in Smiths profile are accompanied by URLs pointing to where each photo was nabbed. By clicking through these links, a Clearview customer typically the police running a search using Smith's photo would be able to figure out personal details like where he works, where he went to university, whom hes married to, and who some of his friends are. That means things like stills from CCTV could be used to pull up the entire life of those pictured in the image.

The app has been served cease-and-desist letters from Google, YouTube, Twitter, and Facebook to stop lifting images from their platforms, and to delete any existing ones it has in its database.

If you want to get your data from Clearview, and are eligible under CCPA or GDPR, Smith recommends sending Clearview an email to privacy@clearview.ai to request your profile. Follow any instructions you receive, he said.

Expect your request to take up to two months to process. Be persistent in following up. And remember that once you receive your data, you have the option to demand that Clearview delete it or amend it if youd like them to do so.

But if you dont live in California or in the European Union, or somewhere with similar laws, the best thing to do to prevent startups like Clearview from snaffling your data is to make your social media profiles private. Dont post snaps of your mug anywhere on the internet that is available for anyone to see.

This isn't totally avoidable, however. If your friends upload pictures of you, Clearview can still scrape them as long as theyre public.

Hey AI, is it going to rain today? Training machine learning models to predict whether it's going to rain or not by looking at the movement of clouds gathered by weather stations or satellites is all the rage at the moment.

Researchers over at Google have developed MetNet, a deep neural network that can forecast where its going to rain in the US up to eight hours before it happens. The team claims that its system was more accurate than the predictive tools employed by the National Oceanic and Atmospheric Administration (NOAA) a US federal scientific agency that monitors the weather, oceans, and the atmosphere on Earth when it comes to forecasting rain.

MetNet inspects data recorded by the radar stations in the Multi-Radar/Multi-Sensor System (MRMS) and the Geostationary Operational Environmental Satellite system, both operated by the NOAA. Images of a top down view of clouds, and atmospheric measurements are given as inputs and MetNet spits out a probability distribution of precipitation over an area spanning 64 square kilometers, covering the entire US at one kilometer resolution.

There are advantages and disadvantages to using neural networks like MetNet to forecast the weather. Although machine learning models provide a cheap alternative to supercomputers, which have to carry out complex calculations, they are generally less accurate and dont deal well with freak weather events that they havent been trained on.

We are actively researching how to improve global weather forecasting, especially in regions where the impacts of rapid climate change are most profound, the researchers said.

While we demonstrate the present MetNet model for the continental US, it could be extended to cover any region for which adequate radar and optical satellite data are available.

You can read more about how MetNet works here.

Star Trek Voyager and Deep Space Nine get an AI makeover: Heres something that will please Star Trek fans: you can now watch clips from Star Trek Voyager and Deep Space Nine in much better quality now that theyve been revamped with the help of AI algorithms.

A YouTube user, going by the name Billy Reichard, has posted a series of videos for Trekkies to watch. Old clips taken from both TV series have been run through Gigapixel AI, a commercial AI tool developed by Topaz Labs, a computer vision company based in Texas, to increase the quality. This is necessary because, it appears, portions of the Voyager and DS9 archives are NTSC-grade and it would be too much faff to restore them in full high definition.

Reichard explained his work on Reddit's r/StarTrek group and compared the AI-generated quality to 4K. He said he planned to play around with the Gigapixel AI software more and will be producing more Star Trek clips for people to enjoy.

Heres one from Voyager...

Youtube Video

And one from Deep Space Nine. Enjoy

Youtube Video

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Call for netizens to demand scraped pics from Clearview, ML weather forecasts, and Star Trek goes high def with AI - The Register

Machine Learning as a Service Market 2020 Size, Share, Technological Innovations & Growth Forecast To 2026 – Daily Science

Machine Learning as a Service Market report provide pin-point analysis of theMachine Learning as a Service industry: Capacity, Production, Value, Consumption and Status(2014-2019) and Six- Year Forecast (2020-2026). BedsidesMachine Learning as a Service marketresearch report enriched on worldwide competition by topmost prime manufactures (Amazon, Oracle Corporation, IBM, Microsoft Corporation, Google Inc., Salesforce.Com, Tencent, Alibaba, UCloud, Baidu, Rackspace, SAP AG, Century Link Inc., CSC (Computer Science Corporation), Heroku, Clustrix, Xeround) which providing information such asCompany Profiles, Product Picture and Specification, Product Details, Capacity, Price, Cost, Gross Consumption, Revenue and contact information is provided for better understanding. In addition, this report discusses the key drivers influencing Market Growth, Opportunities, The Challenges and the Risks faced by key manufacturers and the market as a whole.

Machine Learning as a Service Market Major Factors: Machine Learning as a Service Market Overview, Machine Learning as a Service Market Analysis by Application, Economic Impact on Market, Market Competition, Industrial Chain, Sourcing Strategy and Downstream Buyers, Machine Learning as a Service Market Effect, Factors, Analysis, Machine Learning as a Service Market Forecast, Marketing Strategy Analysis, Distributors/Traders.

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Summation of Machine Learning as a Service Market:Machine learning is a field of artificial intelligence that uses statistical techniques to give computer systems the ability to learn (e.g., progressively improve performance on a specific task) from data, without being explicitly programmed.

Based onProduct Type, Machine Learning as a Service market report displays the manufacture, profits, value, and market segment and growth rate of each type, covers:

Private clouds Public clouds Hybrid cloud

Based onend users/applications, Machine Learning as a Service market report focuses on the status and outlook for major applications/end users, sales volume, market share and growth rate for each application, this can be divided into:

Personal Business

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The report offers in-depth assessment of the growth and other aspects of the Machine Learning as a Service market in important countries (regions), including:

The key insights of the Machine Learning as a Service Market report:

The report provides Key Statistics on the Market Status of the Machine Learning as a Service market manufacturers and is a valuable source of guidance and direction for companies and individuals interested in the industry.

The Machine Learning as a Service market report provides a basic overview of the industry including its definition, applications and manufacturing technology.

The report presents the Company Profile, Product Specifications, Capacity, Production Value, and 2013-2020 market shares for key vendors.

The total Machine Learning as a Service market is further divided By Company, By Country, And By Application/Type for the competitive landscape analysis.

The report estimates 2020-2026 market Development Trends of Machine Learning as a Service industry.

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Machine Learning as a Service Market 2020 Size, Share, Technological Innovations & Growth Forecast To 2026 - Daily Science