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Does An Invention Discovered With Artificial Intelligence Obtain Patent Protection? – JD Supra

May 6, 2020 | Author: admin

Updated: May 25, 2018:

JD Supra is a legal publishing service that connects experts and their content with broader audiences of professionals, journalists and associations.

This Privacy Policy describes how JD Supra, LLC ("JD Supra" or "we," "us," or "our") collects, uses and shares personal data collected from visitors to our website (located at http://www.jdsupra.com) (our "Website") who view only publicly-available content as well as subscribers to our services (such as our email digests or author tools)(our "Services"). By using our Website and registering for one of our Services, you are agreeing to the terms of this Privacy Policy.

Please note that if you subscribe to one of our Services, you can make choices about how we collect, use and share your information through our Privacy Center under the "My Account" dashboard (available if you are logged into your JD Supra account).

Registration Information. When you register with JD Supra for our Website and Services, either as an author or as a subscriber, you will be asked to provide identifying information to create your JD Supra account ("Registration Data"), such as your:

Other Information: We also collect other information you may voluntarily provide. This may include content you provide for publication. We may also receive your communications with others through our Website and Services (such as contacting an author through our Website) or communications directly with us (such as through email, feedback or other forms or social media). If you are a subscribed user, we will also collect your user preferences, such as the types of articles you would like to read.

Information from third parties (such as, from your employer or LinkedIn): We may also receive information about you from third party sources. For example, your employer may provide your information to us, such as in connection with an article submitted by your employer for publication. If you choose to use LinkedIn to subscribe to our Website and Services, we also collect information related to your LinkedIn account and profile.

Your interactions with our Website and Services: As is true of most websites, we gather certain information automatically. This information includes IP addresses, browser type, Internet service provider (ISP), referring/exit pages, operating system, date/time stamp and clickstream data. We use this information to analyze trends, to administer the Website and our Services, to improve the content and performance of our Website and Services, and to track users' movements around the site. We may also link this automatically-collected data to personal information, for example, to inform authors about who has read their articles. Some of this data is collected through information sent by your web browser. We also use cookies and other tracking technologies to collect this information. To learn more about cookies and other tracking technologies that JD Supra may use on our Website and Services please see our "Cookies Guide" page.

We use the information and data we collect principally in order to provide our Website and Services. More specifically, we may use your personal information to:

JD Supra takes reasonable and appropriate precautions to insure that user information is protected from loss, misuse and unauthorized access, disclosure, alteration and destruction. We restrict access to user information to those individuals who reasonably need access to perform their job functions, such as our third party email service, customer service personnel and technical staff. You should keep in mind that no Internet transmission is ever 100% secure or error-free. Where you use log-in credentials (usernames, passwords) on our Website, please remember that it is your responsibility to safeguard them. If you believe that your log-in credentials have been compromised, please contact us at privacy@jdsupra.com.

Our Website and Services are not directed at children under the age of 16 and we do not knowingly collect personal information from children under the age of 16 through our Website and/or Services. If you have reason to believe that a child under the age of 16 has provided personal information to us, please contact us, and we will endeavor to delete that information from our databases.

Our Website and Services may contain links to other websites. The operators of such other websites may collect information about you, including through cookies or other technologies. If you are using our Website or Services and click a link to another site, you will leave our Website and this Policy will not apply to your use of and activity on those other sites. We encourage you to read the legal notices posted on those sites, including their privacy policies. We are not responsible for the data collection and use practices of such other sites. This Policy applies solely to the information collected in connection with your use of our Website and Services and does not apply to any practices conducted offline or in connection with any other websites.

JD Supra's principal place of business is in the United States. By subscribing to our website, you expressly consent to your information being processed in the United States.

You can make a request to exercise any of these rights by emailing us at privacy@jdsupra.com or by writing to us at:

You can also manage your profile and subscriptions through our Privacy Center under the "My Account" dashboard.

We will make all practical efforts to respect your wishes. There may be times, however, where we are not able to fulfill your request, for example, if applicable law prohibits our compliance. Please note that JD Supra does not use "automatic decision making" or "profiling" as those terms are defined in the GDPR.

Pursuant to Section 1798.83 of the California Civil Code, our customers who are California residents have the right to request certain information regarding our disclosure of personal information to third parties for their direct marketing purposes.

You can make a request for this information by emailing us at privacy@jdsupra.com or by writing to us at:

Some browsers have incorporated a Do Not Track (DNT) feature. These features, when turned on, send a signal that you prefer that the website you are visiting not collect and use data regarding your online searching and browsing activities. As there is not yet a common understanding on how to interpret the DNT signal, we currently do not respond to DNT signals on our site.

For non-EU/Swiss residents, if you would like to know what personal information we have about you, you can send an e-mail to privacy@jdsupra.com. We will be in contact with you (by mail or otherwise) to verify your identity and provide you the information you request. We will respond within 30 days to your request for access to your personal information. In some cases, we may not be able to remove your personal information, in which case we will let you know if we are unable to do so and why. If you would like to correct or update your personal information, you can manage your profile and subscriptions through our Privacy Center under the "My Account" dashboard. If you would like to delete your account or remove your information from our Website and Services, send an e-mail to privacy@jdsupra.com.

We reserve the right to change this Privacy Policy at any time. Please refer to the date at the top of this page to determine when this Policy was last revised. Any changes to our Privacy Policy will become effective upon posting of the revised policy on the Website. By continuing to use our Website and Services following such changes, you will be deemed to have agreed to such changes.

If you have any questions about this Privacy Policy, the practices of this site, your dealings with our Website or Services, or if you would like to change any of the information you have provided to us, please contact us at: privacy@jdsupra.com.

As with many websites, JD Supra's website (located at http://www.jdsupra.com) (our "Website") and our services (such as our email article digests)(our "Services") use a standard technology called a "cookie" and other similar technologies (such as, pixels and web beacons), which are small data files that are transferred to your computer when you use our Website and Services. These technologies automatically identify your browser whenever you interact with our Website and Services.

We use cookies and other tracking technologies to:

There are different types of cookies and other technologies used our Website, notably:

JD Supra Cookies. We place our own cookies on your computer to track certain information about you while you are using our Website and Services. For example, we place a session cookie on your computer each time you visit our Website. We use these cookies to allow you to log-in to your subscriber account. In addition, through these cookies we are able to collect information about how you use the Website, including what browser you may be using, your IP address, and the URL address you came from upon visiting our Website and the URL you next visit (even if those URLs are not on our Website). We also utilize email web beacons to monitor whether our emails are being delivered and read. We also use these tools to help deliver reader analytics to our authors to give them insight into their readership and help them to improve their content, so that it is most useful for our users.

Analytics/Performance Cookies. JD Supra also uses the following analytic tools to help us analyze the performance of our Website and Services as well as how visitors use our Website and Services:

Facebook, Twitter and other Social Network Cookies. Our content pages allow you to share content appearing on our Website and Services to your social media accounts through the "Like," "Tweet," or similar buttons displayed on such pages. To accomplish this Service, we embed code that such third party social networks provide and that we do not control. These buttons know that you are logged in to your social network account and therefore such social networks could also know that you are viewing the JD Supra Website.

If you would like to change how a browser uses cookies, including blocking or deleting cookies from the JD Supra Website and Services you can do so by changing the settings in your web browser. To control cookies, most browsers allow you to either accept or reject all cookies, only accept certain types of cookies, or prompt you every time a site wishes to save a cookie. It's also easy to delete cookies that are already saved on your device by a browser.

The processes for controlling and deleting cookies vary depending on which browser you use. To find out how to do so with a particular browser, you can use your browser's "Help" function or alternatively, you can visit http://www.aboutcookies.org which explains, step-by-step, how to control and delete cookies in most browsers.

We may update this cookie policy and our Privacy Policy from time-to-time, particularly as technology changes. You can always check this page for the latest version. We may also notify you of changes to our privacy policy by email.

If you have any questions about how we use cookies and other tracking technologies, please contact us at: privacy@jdsupra.com.

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Does An Invention Discovered With Artificial Intelligence Obtain Patent Protection? - JD Supra

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How Artificial Intelligence could help Wales prevent the spread of Covid-19 – Nation.Cymru

May 6, 2020 | Author: admin

Photo by engin akyurt on Unsplash

Keith Darlington, AI consultant and author

As most of the world has now gone into lockdown, the entire scientific research community has gone into overdrive trying to understand the nature of the COVID-19 virus.

Technology, including Artificial Intelligence (AI), is helping with this task. From the beginning, AI applications have been working behind the scenes assisting the limitations of human knowledge in this massive endeavour. In this article, I briefly describe examples of different ways that this is happening.

Machine learning, as it is known, is the main driving force behind AI. In essence, what machine learning does is to take large amounts of data called Big Data and learns to detect patterns in the data. Future outcomes can be predicted, and other useful insights about the data can sometimes be revealed.

But having access to large amounts of data is essential to ensure that a high confidence level can be assigned to these predictions. The machine learning methods can be applied to many problems, as described below.

Tracking

AI has played a role since the very earliest stages of this virus. A Canadian AI company called BlueDot developed an AI program that alerted the world to the virus after the first case was detected in China on December 31st.

This program was designed to predict infectious diseases and locate and track their spread. It works by combining AI with the knowledge of epidemiologists who identify how and where to look for evidence of emerging diseases.

BlueDot analyses over 100,000 reports daily in many languages and then sends out regular alerts to health care, government, business, and public health clients. The alerts provide brief synopses of anomalous disease outbreaks that its AI program has discovered and the risks they may pose.

But other AI applications have rapidly appeared to monitor not only the spread of information about COVID-19 but also the spread of humans infected and detect humans carrying symptoms. For example, contact tracing smartphone apps were first used in Wuhan to track and trace possible carriers of the virus (see later).

Another AI program is being used in cities in China to detect symptoms of people in bus and train stations as well as other public places where there is a high concentration of people. In this application, AI is combined with sensor detecting temperature measurement technology using computer vision. This technology makes it possible to take body temperature, a key symptom of COVID-19, in a contactless way without affecting normal behaviour.

With this technology in place, those whose body temperatures exceeded the threshold could be located. Doing this manually would be time-consuming and could increase the risk of cross-infection.

Scanning

Testing has become a key issue in the fight against COVID-19. Countries like South Korea and Germany have been seen as successful in handling the virus because of the amount of testing that is done in those countries. Health authorities are keen to increase the numbers being tested but the main testing methods are labour intensive and time-consuming.

But AI is now assisting with other forms of testing, such as x-ray scanning. Various AI programs are now available for chest screening that can highlight lung abnormalities in a chest X-ray scan and provide a COVID-19 risk evaluation much faster than human radiologists.

Resistance

AI has been used in healthcare systems for many years for a range of applications and has encountered some resistance particularly with regard to use of medical patient data. Having access to medical data raises many sensitive issues of privacy and confidentiality.

This became a contentious matter when the British NHS system failed to comply withdata protection rules when it provided 1.6 million patient records to a Google-owned company in 2017 for machine learning analysis.

This, in part, explains the concern with the use of contact-tracing apps, which are already in widespread use in Asia in countries like China, Hong Kong, Singapore and South Korea. They are also now being used in other parts of the world such as India, Italy, and Israel and development in other nation-states continue apace.

Contact-tracing apps vary in the way they work but generally use the fact that smartphone users whereabouts are detectable and therefore, can monitor close contact with other users. AI algorithms can then determine the risk of cross infection and then alert users of such risks by learning from the data collected.

In the last few days, it has been announced that an app has been proposed by the UK government for use in England, that may also be rolled out in Wales. This app is now being trialled in the Isle of Wight.

Mark Drakeford said on the 4th May, that there are some difficulties that need to be resolved because of the differences between NHS England and NHS Wales. As Drakeford said at his daily press conference: At the moment we are working with the UK government on that app to see if we could make use of it here in Wales.

It works by using the Bluetooth protocol to identify other smartphone owners who are in close proximity to each other. Thus, if someone develops Covid-19 symptoms, he or she can notify the app of these symptoms. This data can then be uploaded onto the NHS server and people who have been in contact with this person can be notified and possibly given advice such as requesting self-isolation.

There have been concerns about privacy and the possibility of government surveillance of individuals i.e., the emergence of the Big Brother State particularly with using this app because of its access to centralised data. However, the proposed app will only require participants to enter part of their postcode and will not ask them to enter their names. This offers some level of anonymity because the data will be stored under an anonymous ID.

An important distinction between this contact-tracing app and others is that the data will be centralised and stored on the NHS servers unlike some apps used in other countries which work on individual phones rather than collected centrally. The advantages of doing this is that the hotspots are in the country can be detected. And even if there is a low participation rate in the project, of around 20%, then some important insights may be gained into how the virus is spreading.

For all the privacy concerns, many will feel its a price worth paying particularly if assurances are given that this data will be used for this purpose only. Mark Drakeford thought people would be willing to part with some personal freedoms to take part in the project, and many experts believe that having access to track and trace data is essential.

For example, Dirk Brockmann, an epidemiologist who leads a project tackling the coronavirus pandemic at the Robert Koch Institute in Germany says: There is a simple way that people can help the fight against coronavirus, beyond washing their hands donate their data.

Most people now own smartphones and, if they can be persuaded that it is used for the good of all and used anonymously, then individuals may be persuaded to submit data voluntarily. This is vitally important because according to the University of Oxfords Big Data Institute, a contact-tracing app could help stop this pandemic, but 80% of smartphone owners would need to use it.

Another concern with contact-tracing is that the data may not be a good reflection of the population because the elderly are less likely to use smartphones. But as Mathew Gould, the head of the NHS unit that developed the app, says: Im conscious that smartphone use goes down with the more elderly population. This is part of a strategy, so were making sure were not just relying on the app.

Conclusions

Fighting this pandemic has been helped by AI adoption from its inception. The use contact-tracing is likely to begin a new phase which we hear a great deal about in the coming months.

Its use is controversial but may turn out to be crucial in our battle with COVID-19.

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How Artificial Intelligence could help Wales prevent the spread of Covid-19 - Nation.Cymru

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FTC Provides Guidance on Using Artificial Intelligence and Algorithms – JD Supra

May 6, 2020 | Author: admin

Updated: May 25, 2018:

JD Supra is a legal publishing service that connects experts and their content with broader audiences of professionals, journalists and associations.

This Privacy Policy describes how JD Supra, LLC ("JD Supra" or "we," "us," or "our") collects, uses and shares personal data collected from visitors to our website (located at http://www.jdsupra.com) (our "Website") who view only publicly-available content as well as subscribers to our services (such as our email digests or author tools)(our "Services"). By using our Website and registering for one of our Services, you are agreeing to the terms of this Privacy Policy.

Please note that if you subscribe to one of our Services, you can make choices about how we collect, use and share your information through our Privacy Center under the "My Account" dashboard (available if you are logged into your JD Supra account).

Registration Information. When you register with JD Supra for our Website and Services, either as an author or as a subscriber, you will be asked to provide identifying information to create your JD Supra account ("Registration Data"), such as your:

Other Information: We also collect other information you may voluntarily provide. This may include content you provide for publication. We may also receive your communications with others through our Website and Services (such as contacting an author through our Website) or communications directly with us (such as through email, feedback or other forms or social media). If you are a subscribed user, we will also collect your user preferences, such as the types of articles you would like to read.

Information from third parties (such as, from your employer or LinkedIn): We may also receive information about you from third party sources. For example, your employer may provide your information to us, such as in connection with an article submitted by your employer for publication. If you choose to use LinkedIn to subscribe to our Website and Services, we also collect information related to your LinkedIn account and profile.

Your interactions with our Website and Services: As is true of most websites, we gather certain information automatically. This information includes IP addresses, browser type, Internet service provider (ISP), referring/exit pages, operating system, date/time stamp and clickstream data. We use this information to analyze trends, to administer the Website and our Services, to improve the content and performance of our Website and Services, and to track users' movements around the site. We may also link this automatically-collected data to personal information, for example, to inform authors about who has read their articles. Some of this data is collected through information sent by your web browser. We also use cookies and other tracking technologies to collect this information. To learn more about cookies and other tracking technologies that JD Supra may use on our Website and Services please see our "Cookies Guide" page.

We use the information and data we collect principally in order to provide our Website and Services. More specifically, we may use your personal information to:

JD Supra takes reasonable and appropriate precautions to insure that user information is protected from loss, misuse and unauthorized access, disclosure, alteration and destruction. We restrict access to user information to those individuals who reasonably need access to perform their job functions, such as our third party email service, customer service personnel and technical staff. You should keep in mind that no Internet transmission is ever 100% secure or error-free. Where you use log-in credentials (usernames, passwords) on our Website, please remember that it is your responsibility to safeguard them. If you believe that your log-in credentials have been compromised, please contact us at privacy@jdsupra.com.

Our Website and Services are not directed at children under the age of 16 and we do not knowingly collect personal information from children under the age of 16 through our Website and/or Services. If you have reason to believe that a child under the age of 16 has provided personal information to us, please contact us, and we will endeavor to delete that information from our databases.

Our Website and Services may contain links to other websites. The operators of such other websites may collect information about you, including through cookies or other technologies. If you are using our Website or Services and click a link to another site, you will leave our Website and this Policy will not apply to your use of and activity on those other sites. We encourage you to read the legal notices posted on those sites, including their privacy policies. We are not responsible for the data collection and use practices of such other sites. This Policy applies solely to the information collected in connection with your use of our Website and Services and does not apply to any practices conducted offline or in connection with any other websites.

JD Supra's principal place of business is in the United States. By subscribing to our website, you expressly consent to your information being processed in the United States.

You can make a request to exercise any of these rights by emailing us at privacy@jdsupra.com or by writing to us at:

You can also manage your profile and subscriptions through our Privacy Center under the "My Account" dashboard.

We will make all practical efforts to respect your wishes. There may be times, however, where we are not able to fulfill your request, for example, if applicable law prohibits our compliance. Please note that JD Supra does not use "automatic decision making" or "profiling" as those terms are defined in the GDPR.

Pursuant to Section 1798.83 of the California Civil Code, our customers who are California residents have the right to request certain information regarding our disclosure of personal information to third parties for their direct marketing purposes.

You can make a request for this information by emailing us at privacy@jdsupra.com or by writing to us at:

Some browsers have incorporated a Do Not Track (DNT) feature. These features, when turned on, send a signal that you prefer that the website you are visiting not collect and use data regarding your online searching and browsing activities. As there is not yet a common understanding on how to interpret the DNT signal, we currently do not respond to DNT signals on our site.

For non-EU/Swiss residents, if you would like to know what personal information we have about you, you can send an e-mail to privacy@jdsupra.com. We will be in contact with you (by mail or otherwise) to verify your identity and provide you the information you request. We will respond within 30 days to your request for access to your personal information. In some cases, we may not be able to remove your personal information, in which case we will let you know if we are unable to do so and why. If you would like to correct or update your personal information, you can manage your profile and subscriptions through our Privacy Center under the "My Account" dashboard. If you would like to delete your account or remove your information from our Website and Services, send an e-mail to privacy@jdsupra.com.

We reserve the right to change this Privacy Policy at any time. Please refer to the date at the top of this page to determine when this Policy was last revised. Any changes to our Privacy Policy will become effective upon posting of the revised policy on the Website. By continuing to use our Website and Services following such changes, you will be deemed to have agreed to such changes.

If you have any questions about this Privacy Policy, the practices of this site, your dealings with our Website or Services, or if you would like to change any of the information you have provided to us, please contact us at: privacy@jdsupra.com.

As with many websites, JD Supra's website (located at http://www.jdsupra.com) (our "Website") and our services (such as our email article digests)(our "Services") use a standard technology called a "cookie" and other similar technologies (such as, pixels and web beacons), which are small data files that are transferred to your computer when you use our Website and Services. These technologies automatically identify your browser whenever you interact with our Website and Services.

We use cookies and other tracking technologies to:

There are different types of cookies and other technologies used our Website, notably:

JD Supra Cookies. We place our own cookies on your computer to track certain information about you while you are using our Website and Services. For example, we place a session cookie on your computer each time you visit our Website. We use these cookies to allow you to log-in to your subscriber account. In addition, through these cookies we are able to collect information about how you use the Website, including what browser you may be using, your IP address, and the URL address you came from upon visiting our Website and the URL you next visit (even if those URLs are not on our Website). We also utilize email web beacons to monitor whether our emails are being delivered and read. We also use these tools to help deliver reader analytics to our authors to give them insight into their readership and help them to improve their content, so that it is most useful for our users.

Analytics/Performance Cookies. JD Supra also uses the following analytic tools to help us analyze the performance of our Website and Services as well as how visitors use our Website and Services:

Facebook, Twitter and other Social Network Cookies. Our content pages allow you to share content appearing on our Website and Services to your social media accounts through the "Like," "Tweet," or similar buttons displayed on such pages. To accomplish this Service, we embed code that such third party social networks provide and that we do not control. These buttons know that you are logged in to your social network account and therefore such social networks could also know that you are viewing the JD Supra Website.

If you would like to change how a browser uses cookies, including blocking or deleting cookies from the JD Supra Website and Services you can do so by changing the settings in your web browser. To control cookies, most browsers allow you to either accept or reject all cookies, only accept certain types of cookies, or prompt you every time a site wishes to save a cookie. It's also easy to delete cookies that are already saved on your device by a browser.

The processes for controlling and deleting cookies vary depending on which browser you use. To find out how to do so with a particular browser, you can use your browser's "Help" function or alternatively, you can visit http://www.aboutcookies.org which explains, step-by-step, how to control and delete cookies in most browsers.

We may update this cookie policy and our Privacy Policy from time-to-time, particularly as technology changes. You can always check this page for the latest version. We may also notify you of changes to our privacy policy by email.

If you have any questions about how we use cookies and other tracking technologies, please contact us at: privacy@jdsupra.com.

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Boosted.ai Raises $8 Million in Series A Funding to Bring Artificial Intelligence in Investment Management to the Mainstream – Financial Post

May 6, 2020 | Author: admin

AI Platform Offers Machine Learning Techniques to Global Financial Industry

NEW YORK & TORONTO Boosted.ai, the leading distributed machine learning platform for global investment professionals, today announced the closing of an $8 million USD Series A financing round, led by Portag3 Ventures. Dunamu & Partners and Polar Equity Partners also participated in the round. Inclusive of seed capital, Boosted.ais total funding now stands at $11 million.

Boosted.ai will use the funding to continue enhancing Boosted Insights, its proprietary machine learning platform that empowers portfolio managers, analysts and chief investment officers to augment their existing investment processes, source new ideas and manage risks. Boosted Insights is a first-to-market AI platform for investment professionals, supporting idea generation, portfolio construction and portfolio monitoring without requiring users to be coders, software engineers or data scientists. The platform also allows investment professionals to find value in alternative datasets that otherwise require extensive quantitative experience to unlock.

Co-founded in 2017 by Joshua Pantony, Jon Dorando and Nicholas Abe, Boosted.ai currently has more than a dozen active clients and services the full spectrum of asset managers, including long-only mutual funds, long-short hedge funds, family offices and the investment arms of commercial banks. Combined assets under management managed by the Boosted.ai client base is in excess of $500 billion.

According to the CFA Institute, there are five main hurdles to using artificial intelligence within investment management: cost, talent, technology, vision and time. Boosted Insights solves all five hurdles for managers, said Joshua Pantony, CEO of Boosted.ai. Our mission is to bring elements of quantitative management to the finance industry at large as data becomes the difference between winning and losing for investors globally.

Quantitative overlays, factors and stand-alone strategies are no longer options for the investment management industry they are a requirement to compete. The challenge the industry faces is systematically and efficiently implementing them, alongside unique data sources, to stay ahead of the competition, said Adam Felesky, CEO of Portag3 Ventures. The Boosted.ai platform enables asset managers of any sophistication to do this by tapping into the most advanced machine learning tools available, augmenting their existing investment process through a user-friendly interface that does not require coding expertise.

Funding will also be used to hire additional talent in Toronto and New York City, as well as enhance marketing and sales processes.

In conjunction with the funding round, Adam Felesky from Portag3 Ventures has joined Boosted.ais Board of Directors.

To learn more or schedule a demo of Boosted Insights, visit here.

About Boosted.ai

Boosted.ai is an artificial intelligence company that enhances portfolio management outcomes for the global financial industry through distributed machine learning. Co-founded by Joshua Pantony, Jon Dorando and Nicholas Abe in 2017, the company and its proprietary web-based platform, Boosted Insights, bring advanced quantitative investing techniques to portfolio managers, without requiring any coding or data science background. Headquartered in Toronto and New York City, Boosted.ai is backed by Portag3 Ventures, Dunamu & Partners and Polar Equity Partners. Learn more at boosted.ai and follow us on LinkedIn.

About Portag3 Ventures

Portag3 Ventures is an early-stage investor supporting the worlds most innovative financial technology companies. Its team has deep entrepreneurial and industry experience and provides its founders with full access to the firms partners, in-house experts, and broader global ecosystem. Portag3 alongside Diagram Ventures, a fintech venture builder is a part of the venture capital strategy of Sagard Holdings, a multi-strategy alternative investment platform. Portag3 has a presence in Toronto, Montreal, New York, San Francisco, Europe and Southeast Asia. To learn more, visit p3vc.com.

About Dunamu & Partners

Dunamu & Partners invests in disruptive tech companies in diverse geographies, including North America, East and Southeast Asia. It has mainly backed innovative AI-empowered, data-driven fintech companies. Dunamu & Partners is an investment arm of Dunamu, Inc., an operator of #1 digital asset exchange Upbit and Stockplus (a.k.a. Kakao Stock), a leading multi-asset trading platform in South Korea. With deep experience in investment management and entrepreneurship, the teams leaders act as supportive confidants to founders around the world. To learn more, visit Dunamu & Partners.

View source version on businesswire.com: https://www.businesswire.com/news/home/20200505005225/en/

Contacts

Matthew Luongo Prosek Partners for Boosted.ai mluongo@prosek.com +1 (646) 818-9279

#distro

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Boosted.ai Raises $8 Million in Series A Funding to Bring Artificial Intelligence in Investment Management to the Mainstream - Financial Post

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Artificial intelligence is predicting coronavirus outbreaks before they start – TechRepublic

May 6, 2020 | Author: admin

Artificial intelligence has played a central role in the fight against the coronavirus. Cotiviti has leveraged AI to predict COVID-19 hot spots around the country before an outbreak happens.

As the coronavirus continues to spread around the globe, we've seen a surge in the use of cutting edge technologies to track and control the pandemic, especially artificial intelligence. It seems like only a distant memory when artificial intelligence (AI) was being discussed as an emergent "existential threat" to humanity. However, with the rise of a pandemic, we've quickly embraced the ever-expanding capabilities of AI as a part of our first line of defense.

Recently, an AI platform fed mountains of pharmaceutical data and research studies journals determined that a rheumatoid arthritis medication could potentially be used to treat COVID-19 patients. As we reported earlier this month, some companies are deploying surveillance systems harnessing AI to pinpoint potential infections and mitigate the spread of the pandemic.

SEE: Coronavirus: Critical IT policies and tools every business needs (TechRepublic Premium)

One of the tremendous advantages of AI is the ability to absorb databases of information at warp speed. It's simply too labor-intensive (if not virtually impossible) for a human being to review every single study and every clinical trial directly or indirectly related to a medical phenomenon.

"That's how I spend my time between 2 o'clock in the morning and 4 o'clock in the morning, trying to catch up on a lot of the clinical information," explained Dr. Emad Rizk, chairman, president and CEO of Cotiviti.

The healthcare analytics and solution company Cotiviti is now using AI and a mass of health data to predict future coronavirus hot spots around the US before these clusters emerge. During our interview, Rizk expressed his belief that AI and deep learning can greatly benefit mankind, from accelerating treatment to potentially improving current pharmaceuticals, but he does reiterate a sense of caution about the data being fed to the algorithms.

"You have to be careful that the algorithms are not using a small window of data. In other words, using just two to three data elements to come to a conclusion is a lot different than using 100 data elements," Rizk said.

Cotiviti processes patient screening information and medical claims in its Caspian Insights Platform and uses this information to identify trends. The platform leverages machine learning alongside a wide spectrum of healthcare data to illustrate a "longitudinal" view of patient treatment and care outcomes over time.

The platform plays a central role in Cotiviti's recently unveiled COVID-19 Outbreak Tracker. The interactive map provides weekly predictions about potentially hidden hot spots around the US. The map also highlights areas where coronavirus mitigation efforts may be working, illustrating a decreased probability of a hidden outbreak. Cotiviti uses a vast array of medical information including chest X-rays, emergency department visits, CPT codes, ICD-9 codes, and more to pinpoint hotbeds.

For more on mapping, check out our Flipboard magazine, Coronavirus maps

"We're not looking at confirmed cases only, we're looking at leading indicators by using our technology and comprehensive database [to] potentially see anything that might be occurring so we can raise the flag and say [these] ZIP codes look suspicious," Rizk said.

In early March, the company used Caspian data to pinpoint nearly 2 dozen states with signs indicating a potential future coronavirus outbreak. Within two weeks, 80 percent of these predicted hot spots became a reality, according to Cotiviti. Since then the company has refined its algorithm and pinpointed future hot spots with up to 91% accuracy, per Rizk.

New clinical data is available around the clock, and this information can be applied to advance the model as the virus spreads and other hot spots contract. The data will also be closely monitored when it comes to seasonal flu trends and using this information to pinpoint anomalies indicative of potential coronavirus cases. In the coming weeks and months, there will be interesting predictive indicator updates to gauge as cities and states slowly begin to reopen for business.

"When we go to ZIP code X-Y-Z, we can use our model to hone in and begin to see if there was any correlation with opening up that ZIP code to an increase in amplitude and volume of flu-like symptoms using our deep machine learning and our AI incidence," Rizk said.

For this particular crisis, feeding an algorithm the appropriate information to do its task is one challenge. People are also struggling to glean useful insights amid a deluge of seemingly never-ending coronavirus news coverage and, at times, conflicting reports. Rizk concluded our conversation touching on his colleagues and comrades at the forefront of this pandemic and reiterating the importance of taking a comprehensive 360-degree approach to information.

"I have many friends out on the front line serving and doing everything that they can. And we are all trying to get through the bombardment of information out there. Everyone is trying to help. But again, everybody is coming at it from a different lens," he said.

"One angle, you'll only see one angle, not the whole picture," he continued.

Be in the know about smart cities, AI, Internet of Things, VR, AR, robotics, drones, autonomous driving, and more of the coolest tech innovations. Delivered Wednesdays and Fridays

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How China used robots, drones and artificial intelligence to control the spread of the coronavirus – MarketWatch

May 6, 2020 | Author: admin

While most countries in the world are fighting exponential growth of coronavirus infections, China seems to have gotten the situation under control.

Thats been largely due to the Chinese governments ability to enforce preventive measures more successfully than Western democracies. Individualism, a patchwork approach and fear of stopping economic growth backfired in the U.S. and some European countries.

An overlooked factor that helped flatten the curve in China: Technology.

Social distancing, contactless transactions, cleaning and gathering diagnostic data have been made possible by automated technologies developed at Chinese companies.

Pudu Technology from Shenzhen employed its repurposed catering robots in more than 40 hospitals across the country. The robots help medical staff deliver supplies and medicine to patients and limit health-care workers exposure.

Another company from Shenzhen, MMC (MicroMultiCopter), used megaphone-equipped drones to patrol the streets, warning groups of people who failed to wear masks to disperse. The drones are capable of spraying disinfectants in public places and measuring individual thermal signatures, helping to reduce the spread of the virus. In addition, the MMC drones monitored traffic, enabling uncongested vehicle movement and faster response rates in case of medical emergencies.

Other technologies have been employed as well. Chengdu city in Sichuan Province armed epidemic-control personnel with high-tech smart helmets that can automatically measure peoples temperature when they enter a five-meter range. The helmet sounds an alarm if anyone has a fever.

If you think that something is missing, youre right. We havent mentioned AI artificial intelligence. Alibaba BABA, +0.07%, the Chinese tech and e-commerce multinational company, has developed AI that allegedly can detect coronavirus infections with 96% accuracy.

Finally, Chinas vast surveillance system is finally being put to a good use: Facial-recognition cameras come equipped with thermal sensors that can detect people with fevers and those not wearing masks.

Mobile apps also play a big role here Tencent TCEHY, +0.74% and Alipay have developed apps that inform users if theyve been in contact with a virus carrier and whether they should stay at home or be allowed in public spaces.

For these apps to work, however, additional personal data need to be provided by the user. Alipays app, which is in use in over 200 cities, classifies people by color codes: Red is for supervised quarantine, yellow is for self-quarantine and green means unrestricted movement.

The lack of transparency of how these codes are generated has already led to much confusion and frustration, which is only amplified by the fact that the data entered in the app are shared with the government and police. The same is true of the surveillance. Privacy was never a big topic in the Peoples Republic of China (PRC), and now the last shreds are being obliterated in the name of public safety. The country may eventually subdue the coronavirus infection, but at what cost?

Still, there are things that we Westerners could learn from the Chinese. Seeing empty streets of European and American cities on the news gives me hope that people are finally realizing this isnt just a flu and that we need to take things seriously.

Tech can help, but this time it plays second fiddle to staying home and abiding by protective measures against the virus. Until a vaccine is approved, this is the best way the curve can be flattened and the burden on health-care professionals can be reduced to a sustainable level. So, until further notice, stay home and stay safe.

Jurica Dujmovic is a MarketWatch columnist.

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Customer experience, innovation, artificial intelligence, culture.a look inside Amazon Interview with Claire Whitaker – Customer Think

May 6, 2020 | Author: admin

Todays interview is with Claire Whitaker, a product and artificial intelligence (AI) consultant, who over the last nine years has worked in lean innovation, customer experience (CX), product management and technology including AI teams at top companies across industries, including Amazon. Claire joins me today to share some insights from her experience and, particularly, from her time at Amazon.

This interview follows on from my recent interview The nature of service and how weve grown up with a service economy which is now finding it very hard to actually serve customers Interview with Joel Bailey of EY Seren and is number 340 in the series of interviews with authors and business leaders that are doing great things, providing valuable insights, helping businesses innovate and delivering great service and experience to both their customers and their employees.

Heres the highlights of my chat with Claire:

About Claire

Claire is a product and AI consultant. Over the last nine years, she has worked in innovation and CX teams at top companies across industries, including Amazon. She has been involved in a variety of projects looking at how to use advanced technologies like AI and AR to improve customer experience. Now as a certified SME consultant, she helps tech companies move from feeling overwhelmed in your business unable to scale, to have a product roadmap the team is excited about delivering.

You can found out more about Claire at Artificially Intelligent Consulting, say Hi to her on Twitter @ElizabetClaire and do connect with her on LinkedIn here.

Image by 272447 from Pixabay

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Artificial Intelligence in BFSI Market Latest State Of Affairs On Innovation, Revolutionary Opportunities Customers 2026 – Cole of Duty

May 6, 2020 | Author: admin

The Artificial Intelligence in BFSI market report [6 Years Forecast 2020-2026] focuses on the COVID19 Outbreak Impact analysis of key points influencing the growth of the market. Providing info like market competitive situation, product scope, market overview, opportunities, driving force and market risks. Profile the Top Key Players of Artificial Intelligence in BFSI, with sales, revenue and global market share of Artificial Intelligence in BFSI are analyzed emphatically by landscape contrast and speak to info. Upstream raw materials and instrumentation and downstream demand analysis is additionally administrated. The Artificial Intelligence in BFSI market business development trends and selling channels square measure analyzed. From a global perspective, It also represents overall industry size by analyzing qualitative insights and historical data.

The study encompasses profiles of major companies operating in the global Artificial Intelligence in BFSI market. Key players profiled in the report includes : IBM, Baidu, Brighterion, Microsoft, Google, SAP, Intel, IPsoft, NVIDIA, MicroStrategy, IFlyTek, Infosys, Albert Technologies, Megvii Technology, and among others.

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The Artificial Intelligence in BFSI market report provides a comprehensive analysis of:Industry overview, cost structure analysis, technical data and competitive analysis, topmost players analysis, development trend analysis, overall market overview, regional market analysis, consumers analysis and marketing type analysis.

Scope of Artificial Intelligence in BFSI Market:

The global Artificial Intelligence in BFSI market is valued at million US$ in 2019 and will reach million US$ by the end of 2026, growing at a CAGR of during 2020-2026. The objectives of this study are to define, segment, and project the size of the Artificial Intelligence in BFSI market based on company, product type, application and key regions.

This report studies the global market size of Artificial Intelligence in BFSI in key regions like North America, Europe, Asia Pacific, Central & South America and Middle East & Africa, focuses on the consumption of Artificial Intelligence in BFSI in these regions.

This research report categorizes the global Artificial Intelligence in BFSI market by players/brands, region, type and application. This report also studies the global market status, competition landscape, market share, growth rate, future trends, market drivers, opportunities and challenges, sales channels, distributors, customers, research findings & conclusion, appendix & data source and Porters Five Forces Analysis.

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On the basis on the end users/applications,this report focuses on the status and outlook for major applications/end users, sales volume, market share and growth rate foreach application.

On the basis of product,this report displays the sales volume, revenue (Million USD), product price, market share and growth rate ofeach type.

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Quantum Physics Overview, Concepts, and History

May 6, 2020 | Author: admin

Quantum physics is the study of the behavior of matter and energy at the molecular, atomic, nuclear, and even smaller microscopic levels. In the early 20th century, scientists discovered that the laws governing macroscopic objects do not function the same in such small realms.

"Quantum" comes from the Latin meaning "how much." It refers to the discrete units of matter and energy that are predicted by and observed in quantum physics. Even space and time, which appear to be extremely continuous, have the smallest possible values.

As scientists gained the technology to measure with greater precision, strange phenomena was observed. The birth of quantum physics is attributed to Max Planck's 1900 paper on blackbody radiation. Development of the field was done by Max Planck, Albert Einstein, Niels Bohr, Richard Feynman, Werner Heisenberg, Erwin Schroedinger, and other luminary figures in the field. Ironically, Albert Einstein had serious theoretical issues with quantum mechanics and tried for many years to disprove or modify it.

In the realm of quantum physics, observing something actually influences the physical processes taking place. Light waves act like particles and particles act like waves (called wave particle duality). Matter can go from one spot to another without moving through the intervening space (called quantum tunnelling). Information moves instantly across vast distances. In fact, in quantum mechanics we discover that the entire universe is actually a series of probabilities. Fortunately, it breaks down when dealing with large objects, as demonstrated by the Schrodinger's Cat thought experiment.

One of the key concepts is quantum entanglement, which describes a situation where multiple particles are associated in such a way that measuring the quantum state of one particle also places constraints on the measurements of the other particles. This is best exemplified by the EPR Paradox. Though originally a thought experiment, this has now been confirmed experimentally through tests of something known as Bell's Theorem.

Quantum optics is a branch of quantum physics that focuses primarily on the behavior of light, or photons. At the level of quantum optics, the behavior of individual photons has a bearing on the outcoming light, as opposed to classical optics, which was developed by Sir Isaac Newton. Lasers are one application that has come out of the study of quantum optics.

Quantum electrodynamics (QED) is the study of how electrons and photons interact. It was developed in the late 1940s by Richard Feynman, Julian Schwinger, Sinitro Tomonage, and others. The predictions of QED regarding the scattering of photons and electrons are accurate to eleven decimal places.

Quantum physics is sometimes called quantum mechanics or quantum field theory. It also has various subfields, as discussed above, which are sometimes used interchangeably with quantum physics, though quantum physics is actually the broader term for all of these disciplines.

Causality in Quantum Physics - Thought Experiments and Interpretations

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What Is Quantum Mechanics? Quantum Physics Defined …

May 6, 2020 | Author: admin

Quantum mechanics is the branch of physics relating to the very small.

It results in what may appear to be some very strange conclusions about the physical world. At the scale of atoms and electrons, many of the equations ofclassical mechanics, which describe how things move at everyday sizes and speeds, cease to be useful. In classical mechanics, objects exist in a specific place at a specific time. However, in quantum mechanics, objects instead exist in a haze of probability; they have a certain chance of being at point A, another chance of being at point B and so on.

Quantum mechanics (QM) developed over many decades, beginning as a set of controversial mathematical explanations of experiments that the math of classical mechanics could not explain. It began at the turn of the 20th century, around the same time that Albert Einstein published histheory of relativity, a separate mathematical revolution in physics that describes the motion of things at high speeds. Unlike relativity, however, the origins of QM cannot be attributed to any one scientist. Rather, multiple scientists contributed to a foundation of three revolutionary principles that gradually gained acceptance and experimental verification between 1900 and 1930. They are:

Quantized properties: Certain properties, such as position, speed and color, can sometimes only occur in specific, set amounts, much like a dial that "clicks" from number to number. This challenged a fundamental assumption of classical mechanics, which said that such properties should exist on a smooth, continuous spectrum. To describe the idea that some properties "clicked" like a dial with specific settings, scientists coined the word "quantized."

Particles of light: Light can sometimes behave as a particle. This was initially met with harsh criticism, as it ran contrary to 200 years of experiments showing that light behaved as a wave; much like ripples on the surface of a calm lake. Light behaves similarly in that it bounces off walls and bends around corners, and that the crests and troughs of the wave can add up or cancel out. Added wave crests result in brighter light, while waves that cancel out produce darkness. A light source can be thought of as a ball on a stick beingrhythmically dipped in the center of a lake. The color emitted corresponds to the distance between the crests, which is determined by the speed of the ball's rhythm.

Waves of matter: Matter can also behave as a wave. This ran counter to the roughly 30 years of experiments showing that matter (such as electrons) exists as particles.

In 1900, German physicist Max Planck sought to explain the distribution of colors emitted over the spectrum in the glow of red-hot and white-hot objects, such as light-bulb filaments. When making physical sense of the equation he had derived to describe this distribution, Planck realized it implied that combinations of only certaincolors(albeit a great number of them) were emitted, specifically those that were whole-number multiples of some base value. Somehow, colors were quantized! This was unexpected because light was understood to act as a wave, meaning that values of color should be a continuous spectrum. What could be forbiddingatomsfrom producing the colors between these whole-number multiples? This seemed so strange that Planck regarded quantization as nothing more than a mathematical trick. According to Helge Kragh in his 2000 article in Physics World magazine, "Max Planck, the Reluctant Revolutionary," "If a revolution occurred in physics in December 1900, nobody seemed to notice it. Planck was no exception "

Planck's equation also contained a number that would later become very important to future development of QM; today, it's known as "Planck's Constant."

Quantization helped to explain other mysteries of physics. In 1907, Einstein used Planck's hypothesis of quantization to explain why the temperature of a solid changed by different amounts if you put the same amount of heat into the material but changed the starting temperature.

Since the early 1800s, the science ofspectroscopyhad shown that different elements emit and absorb specific colors of light called "spectral lines." Though spectroscopy was a reliable method for determining the elements contained in objects such as distant stars, scientists were puzzled aboutwhyeach element gave off those specific lines in the first place. In 1888, Johannes Rydberg derived an equation that described the spectral lines emitted by hydrogen, though nobody could explain why the equation worked. This changed in 1913 whenNiels Bohrapplied Planck's hypothesis of quantization to Ernest Rutherford's 1911 "planetary" model of the atom, which postulated that electrons orbited the nucleus the same way that planets orbit the sun. According toPhysics 2000(a site from the University of Colorado), Bohr proposed that electrons were restricted to "special" orbits around an atom's nucleus. They could "jump" between special orbits, and the energy produced by the jump caused specific colors of light, observed as spectral lines. Though quantized properties were invented as but a mere mathematical trick, they explained so much that they became the founding principle of QM.

In 1905, Einstein published a paper, "Concerning an Heuristic Point of View Toward the Emission and Transformation of Light," in which he envisioned light traveling not as a wave, but as some manner of "energy quanta." This packet of energy, Einstein suggested, could "be absorbed or generated only as a whole," specifically when an atom "jumps" between quantized vibration rates. This would also apply, as would be shown a few years later, when an electron "jumps" between quantized orbits. Under this model, Einstein's "energy quanta" contained the energy difference of the jump; when divided by Plancks constant, that energy difference determined the color of light carried by those quanta.

With this new way to envision light, Einstein offered insights into the behavior of nine different phenomena, including the specific colors that Planck described being emitted from a light-bulb filament. It also explained how certain colors of light could eject electrons off metal surfaces, a phenomenon known as the "photoelectric effect." However, Einstein wasn't wholly justified in taking this leap, said Stephen Klassen, an associate professor of physics at the University of Winnipeg. In a 2008 paper, "The Photoelectric Effect: Rehabilitating the Story for the Physics Classroom," Klassen states that Einstein's energy quanta aren't necessary for explaining all of those nine phenomena. Certain mathematical treatments of light as a wave are still capable of describing both the specific colors that Planck described being emitted from a light-bulb filament and the photoelectric effect. Indeed, in Einstein's controversial winning of the 1921Nobel Prize, the Nobel committee only acknowledged "his discovery of the law of the photoelectric effect," which specifically did not rely on the notion of energy quanta.

Roughly two decades after Einstein's paper, the term "photon" was popularized for describing energy quanta, thanks to the 1923 work of Arthur Compton, who showed that light scattered by an electron beam changed in color. This showed that particles of light (photons) were indeed colliding with particles of matter (electrons), thus confirming Einstein's hypothesis. By now, it was clear that light could behave both as a wave and a particle, placing light's "wave-particle duality" into the foundation of QM.

Since the discovery of the electron in 1896, evidence that all matter existed in the form of particles was slowly building. Still, the demonstration of light's wave-particle duality made scientists question whether matter was limited to actingonlyas particles. Perhaps wave-particle duality could ring true for matter as well? The first scientist to make substantial headway with this reasoning was a French physicist named Louis de Broglie. In 1924, de Broglie used the equations of Einstein'stheory of special relativityto show that particles can exhibit wave-like characteristics, and that waves can exhibit particle-like characteristics. Then in 1925, two scientists, working independently and using separate lines of mathematical thinking, applied de Broglie's reasoning to explain how electrons whizzed around in atoms (a phenomenon that was unexplainable using the equations ofclassical mechanics). In Germany, physicist Werner Heisenberg (teaming with Max Born and Pascual Jordan) accomplished this by developing "matrix mechanics." Austrian physicist ErwinSchrdingerdeveloped a similar theory called "wave mechanics." Schrdinger showed in 1926 that these two approaches were equivalent (though Swiss physicist Wolfgang Pauli sent anunpublished resultto Jordan showing that matrix mechanics was more complete).

The Heisenberg-Schrdinger model of the atom, in which each electron acts as a wave (sometimes referred to as a "cloud") around the nucleus of an atom replaced the Rutherford-Bohr model. One stipulation of the new model was that the ends of the wave that forms an electron must meet. In "Quantum Mechanics in Chemistry, 3rd Ed." (W.A. Benjamin, 1981), Melvin Hanna writes, "The imposition of the boundary conditions has restricted the energy to discrete values." A consequence of this stipulation is that only whole numbers of crests and troughs are allowed, which explains why some properties are quantized. In the Heisenberg-Schrdinger model of the atom, electrons obey a "wave function" and occupy "orbitals" rather than orbits. Unlike the circular orbits of the Rutherford-Bohr model, atomic orbitals have a variety of shapes ranging from spheres to dumbbells to daisies.

In 1927, Walter Heitler and Fritz London further developed wave mechanics to show how atomic orbitals could combine to form molecular orbitals, effectively showing why atoms bond to one another to formmolecules. This was yet another problem that had been unsolvable using the math of classical mechanics. These insights gave rise to the field of "quantum chemistry."

Also in 1927, Heisenberg made another major contribution to quantum physics. He reasoned that since matter acts as waves, some properties, such as an electron's position and speed, are "complementary," meaning there's a limit (related to Planck's constant) to how well the precision of each property can be known. Under what would come to be called "Heisenberg'suncertainty principle," it was reasoned that the more precisely an electron's position is known, the less precisely its speed can be known, and vice versa. This uncertainty principle applies to everyday-size objects as well, but is not noticeable because the lack of precision is extraordinarily tiny. According to Dave Slaven of Morningside College (Sioux City, IA), if a baseball's speed is known to within aprecision of 0.1 mph, the maximum precision to which it is possible to know the ball's position is 0.000000000000000000000000000008 millimeters.

The principles of quantization, wave-particle duality and the uncertainty principle ushered in a new era for QM. In 1927, Paul Dirac applied a quantum understanding of electric and magnetic fields to give rise to the study of "quantum field theory" (QFT), which treated particles (such as photons and electrons) as excited states of an underlying physical field. Work in QFT continued for a decade until scientists hit a roadblock: Many equations in QFT stopped making physical sense because they produced results of infinity. After a decade of stagnation, Hans Bethe made a breakthrough in 1947 using a technique called "renormalization." Here, Bethe realized that all infinite results related to two phenomena (specifically "electron self-energy" and "vacuum polarization") such that the observed values of electron mass and electron charge could be used to make all the infinities disappear.

Since the breakthrough of renormalization, QFT has served as the foundation for developing quantum theories about the four fundamental forces of nature: 1) electromagnetism, 2) the weak nuclear force, 3) the strong nuclear force and 4) gravity. The first insight provided by QFT was a quantum description of electromagnetism through "quantum electrodynamics" (QED), which made strides in the late 1940s and early 1950s. Next was a quantum description of the weak nuclear force, which was unified with electromagnetism to build "electroweak theory" (EWT) throughout the 1960s. Finally came a quantum treatment of the strong nuclear force using "quantum chromodynamics" (QCD) in the 1960s and 1970s. The theories of QED, EWT and QCD together form the basis of theStandard Modelof particle physics. Unfortunately, QFT has yet to produce a quantum theory of gravity. That quest continues today in the studies of string theory and loop quantum gravity.

Robert Coolman is a graduate researcher at the University of Wisconsin-Madison, finishing up his Ph.D. in chemical engineering. He writes about math, science and how they interact with history. Follow Robert@PrimeViridian. Followus@LiveScience,Facebook&Google+.

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