The Google for Predictive Analytics
IT Prof. Alex Pentland and Director of the MIT Media Lab Entrepreneurship Program, named by Forbes as “one of the world's 7 most powerful data scientists,” developed a new paradigm for Machine Learning based on AI.
Instead of building a data model for each predictive question, it uses a new social theory of human behavior that predicts future choices through behavioral commonalities. With the interplay of social and the kind of cause of effect interaction associated with physics, naturally enough, he called it Social Physics.
What his research demonstrated was that people behave in mathematically predictable ways. Just like physics determines the state of the natural universe, Social Physics governs the human universe.
But this was not just academic knowledge for Pentland.
Pentland was well-versed in real-life business dealings. He served as a founding member of the Scientific Advisory Boards at Google, AT&T, Nissan, and the UN Secretary General for cutting edge technology. On that basis of combining knowledge, skills, experience, and innovation, he created an automated engine that can answer any natural-language question.
That is the cornerstone of the business Pentland cofounded in 2014: Endor. Endor extended Social Physics using proprietary technology into a powerful engine that is able to explain and predict human behavior.
More AI-enabled prediction to arrive at a Google-like capability
Endor enables the automation and democratization of Al and data science, allowing a company to advance from paying a lot for getting the answers to just a limited number of predictive questions each year to affordable and easy access to unlimited answers.
It addresses the problem that has hampered businesses that do not have the deep pockets to fund the data science teams that had been necessary to become truly data-driven and capitalize on the power of predictive analytics. That meant that the power of predicting the future was only within reach of tech-giants who could afford to invest millions of dollars in building their data science resources.
Smaller companies that wanted to be able to direct their business strategy on the basis of predictions had to work off slow, complex, and expensive machine learning solutions. But now the are able the automated AI predictions provided by Endor, which MIT dubbed the “Google for predictive analytics.”
The same MIT article quotes the other Endor co-founder and its CEO, Dr. Yaniv Altshuler, reinforcing the Google comparison:
“It’s just like Google. You don’t have to spend time thinking, ‘Am I going to spend time asking Google this question?’ You just Google it.”
Altshuler declared, “It’s as simple as that.”
Altshuler has his own list of impressive credentials. He is a recognized expert on Machine Learning, Swarm Intelligence and Data Analysis who has authored over 60 scientific papers and filed 15 patents.
He expressed the great potential in Endor as follows:
“Imagine if you can ask any predictive business question such as ‘Who will complete a transaction tomorrow?’ or ‘Who will upgrade to Premium services in the next week?’ — this is a gamechanger for businesses and enterprises who want to act on their data in a speedy and accurate manner.”
Althshuler is featured in the video below in a conversation with Charles Hoskinson, Senior member of Endor's Advisory Board about the future of Predictive Analytics:
What it can do for businesses
Endor delivers faster response times, as no data scientist input, including modeling, coding or data gathering, is called for. It embeds actionable insights into an organization’s workflow by allowing it BI, sales, marketing and all business teams to self-find predictions ‘do-it-yourself’ style
Now Endor makes accurate predictions scalable and accessible to businesses of all sizes (Enterprise to SMB) through proprietary Social Physics technology developed through years of research at MIT (Not through NLP). It enables business users to ask predictive questions, and get automated accurate predictions without having to hire data scientists.
It is particularly convenient for those without data scientist resources to prepare the data. Endor is agnostic about its use of big data. Even if has not been prepared through cleaning it can be analyzed.
Plus Endor has the industry-first capability to compute on encrypted data without decrypting it. That means that it meets the standards set for global privacy and data security regulations, which should be a major relief for businesses that have to deal with European entities and prove themselves to be GDPR compliant.
Since its founding in 2014, Endor has successfully grown an impressive clientele, including national banks, large Financial Services, and Fortune 500 companies, such as Coca Cola and MasterCard.
Endor is a pioneer in the merging of legacy infrastructure with innovative Blockchain services, thus supporting the transition of its large, Fortune 500 customers, enterprise customers to the Endorprotocol. The convergence of platforms will ensure a larger pool of aggregate data (new data sources), to the Endor Protocol, which in turn, will work to further increase the accuracy of its predictions.
Above is the HubCulture interview with both Pentland and Altshuler,
Beyond commercial applications
While it is primarily marketed to businesses, including wholesalers, retailers, and financial institutions, Endor’s technology can also be applied to other goals, including that of national security. MIT reported that it used its analytics for analyzing terrorist threats on the basis of Twitter data:
“Endor was given 15 million data points containing examples of 50 Twitter accounts of identified ISIS activists, based on identifiers in the metadata. From that, they asked the startup to detect 74 with identifiers extremely well hidden in the metadata.”
It only took an Endor employee 24 minutes to identify 80 “lookalike” ISIS accounts, more than half of which were in the pool of 74 well-hidden accounts named by the agency. The efficiency of the system is not just manifested in the relatively short time it took to do the analysis but also in the very low false-positive rate.
What’s in a name?
As the video above clarifies, the company’s name comes from Star Wars. Fans may recall Endor as the home of the cute and furry, pint-sized beings who help the rebels against the Empire forces that went there to build the second Death Star in Return of the Jedi.
Here’s a clip to remind you of the scene at Endor.
The thing is that the name Endor was not actually born out of George Lucas’ imagination. It actually first appears in the Bible in the 28th chapter of the Book of Samuel. That is the account of the witch of Endor whom the king calls on for divination.
In the Bible’s account, King Saul requests that she summon the now-dead prophet Samuel to instruct him on what to do. So really the name Endor is more appropriate for predictive technology because of its original context than for the more geeky-cool Star Wars connection.
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