Artificial Intelligence Startups in Healthcare

CBInsights_AI-healthcare-Q2-16

CB Insights:

The startups [above] have raised more than $870M in aggregate funding since 2011.

This year has seen some notable deals involving companies on the map: New York-based AiCure raised $12.3M in Series A funding and London-based health services startup, Babylon Health, raised a $25M Series A round from investors including Google-owned DeepMind Technologies and Hoxton Ventures. Babylon will reportedly roll out a Siri-like voice recognition interface this year. The largest round so far in 2016 (as of 5/24/2016) was raised by China-based iCarbonX ($154M Series A round).

 

Posted in Artificial Intelligence, Deep Learning, Machine Learning, startups | Tagged | Leave a comment

Israeli Startups Disrupting the Car Industry

Israel_car_startups

There are more than 150 automotive startups and research groups in Israel, almost 100% growth over the last 4 years. Over the last 2 years, car-related startups have raised $820 million.

Posted in Misc | Leave a comment

What Are Amazon Echo, Apple Siri and Google Now Good For?

Voice_assistance

Posted in Misc | Leave a comment

600+ companies investing in deep learning

DeepLearing_investment

DeepLearning_investments

 

O’Reilly Data:

…more than 600 companies have jumped into applying deep learning with real budgets. …about 90 companies (level 3), have made strategic investments in deep learning for their businesses. Another 177 companies (level 2) are developing projects using deep learning with dedicated resources in staff. And more than 350 companies (level 1) are experimenting with deep learning in their labs.

Given how early deep learning is as a technology, the majority of companies investing in deep learning are IT and software businesses. However, we discovered interesting champions in other industries that are adopting deep learning as well. [Above] are some examples of companies that are not in traditional software or IT businesses, but that are adopting deep learning. Given that deep learning has early roots in image processing, it is exciting to see health care companies like Siemens Healthcare and GE Healthcare leading the pack, along with research institutions like the NIH and Lawrence Livermore National Labs.

 

Posted in Deep Learning | Tagged | Leave a comment

Where should you put your data scientists?

[slideshare id=61486991&doc=whereshouldyouputyourdatascientists-160429025555]

Posted in Data Science | Leave a comment

A Few Internet of Things (IoT) Facts (Infographic)

IoT_facts_infographic.jpg

Posted in Internet of Things | Leave a comment

Why the Growing Threat of Ransomware is Good for You

“Unbelievable” is what FBI Cyber Division Assistant Director James Trainor called last week the increase in the amount and sophistication of ransomware attacks in the first quarter of 2016, according to CIO Journal.

Last year, there were 2,453 reported ransomware incidents in the U.S., in which victims paid about $24.1 million. We can expect much more in 2016, says the FBI, defining ransomware as “an insidious type of malware that encrypts, or locks, valuable digital files and demands a ransom to release them.”

Yaki_Varonis

Yaki Faitelson, CEO, Varonis

Yaki Faitelson, CEO of Varonis, sees a silver lining in the changing threat environment. Ransomware, he argues, is the only type of cybersecurity infiltration where the attackers want their presence to be known, typically shortly after succeeding in obtaining access to the victim’s files and encrypting them.

”Ransomware is very vocal,” says Faitelson, “but it acts exactly like other malicious insider threats.” As such, it can serve as a sort of cybersecurity training exercise, exposing to the victims specific vulnerabilities in their defenses.

“This is what we call security from the inside out,” says Faitelson. “Nearly all data breaches come, in one form or another, from insiders.” Data breaches can originate with a disgruntled employee or one seeking a material gain. But for the most part, they are the result of inadequate management of data access permissions compounded by innocent mistakes committed by insiders, such as clicking on an e-mail with a malware attachment.

You may think that with all the publicity about “phishing” attempts, people are much more careful about opening email attachments from unknown sources. But the 2016 Data Breach Investigations Report found that 30% of phishing messages were opened, up from 24% last year, and that 12% of email users went on to click the malicious attachment.

An additional fuel to the ransomware fire is its increased sophistication, now spreading to your organization not only via email but also with the help of infected websites, taking advantage of unpatched software on end-user computers.

So what’s the best protection? “Ransomware is about backups, more so than anything else,” says the FBI’s Trainor. Faitelson begs to differ.  “Most organizations don’t have effective backup,” he says. Their physical backup is not up-to-date and is costly to recover. Their up-to-date backup files are increasingly being targeted by the ransomware attackers who make sure to encrypt them as well.

Instead of relying solely on physical backup, Varonis recommends constant monitoring of the IT infrastructure, looking for mass encryption beyond a certain threshold and looking for the typical extensions that the ransomware software creates.

“The best way to find today’s sophisticated attackers is user behavior analytics, understanding what is normal and what is not, identifying behavioral anomalies for accounts that are targeted by hackers,” says Faitelson.

User behavior analytics is a relatively new cybercrime-fighting tool for Varonis and the industry.  Realizing that protecting the perimeter and the endpoints of the IT infrastructure is not enough, the industry is moving rapidly to developing and providing machine learning tools that detect anomalies and alert security staff to unusual activity. Faitelson argues that Varonis has a headstart in this field as it has been monitoring and analyzing how users interact with data and file systems since 2005.

Before he and Ohad Korkus founded Varonis, they worked in professional services for NetApp. While implementing a project in Angola for a large energy exploration firm, someone deleted many critical files: images taken from the ocean floor at great expense.  Attempting to find out who deleted the files became a monumental task.

It was then that they realized that enterprises needed a much better way to track, visualize, analyze and protect their data. That led to Varonis’ initial focus on data management, on understanding, mapping, and organizing data ownership, rights, and responsibilities across the enterprise.

That decade-plus experience, specifically the gathering and analyzing of metadata, data about the data, its use, and users’ interactions with it, now informs the algorithms and automated rules Varonis uses to identify abnormal behavior without generating lots of distracting “false positives,” alerts triggered by benign activity. Given the 33% revenue growth announced by Varonis last week, the move to applying its data management expertise to cybersecurity seems to be working.

Ransomware may be changing the dynamics of cyber defense, but it may also change how organizations value their information. That maybe another ransomware silver lining: It quantifies, in monetary terms, what it costs not to have access to specific records and files. Says Faitelson: “Ransomware shows the organization the value of the data.”

Originally published on Forbes.com

Posted in Misc | Tagged | Leave a comment

10 Inventions Predicted By The Simpsons (Video)

[youtube https://www.youtube.com/watch?v=ndTglH25dDY?rel=0]

Posted in Misc | Leave a comment

Data Scientists Still Hot, Salaries Cool Off

Burtch16_Figure 5
Burtch16_Figure 6

The third annual Burtch Works Study: Salaries of Data Scientists April 2016 is out, documenting the continuation of a very favorable market for those with the sexiest job of the 21st century.  However, the salaries of data scientists appear to be leveling off: Every job category except one (entry-level individual contributors) experienced a marginal single-digit shift in median base salary over the past year. This compared to the overall increase in compensation of 14% in last year’s report.

The Burtch Works Study is based on compensation and demographic data for 374 data scientists collected in interviews conducted by Burtch’s recruiting staff during the 12 months ending March 2016. It focuses on data scientists as distinguished from other analytics professionals, defining them as follows:

Data scientists apply sophisticated quantitative and computer science skills to both structure and analyze massive unstructured datasets or continuously streaming data, with the intent to derive insights and prescribe action. The depth and breadth of their coding skills distinguishes them from other predictive analytics professionals and allows them to exploit data regardless of its source, size, or format. Through the use of one or more general-purpose coding languages and data infrastructures, data scientists can tackle problems made very difficult by the size and disorganization of the data.

 

Here are the highlights of the new report.

Individual contributors: Median base salaries range from $97,000 at level 1 to $152,000 at level 3 plus bonuses ranging from $10,000 to $21,000 (over 73% of all individual contributors are eligible for bonuses).

Managers: Median base salaries range from $140,000 at level 1 to $240,000 at level 3 plus bonuses ranging from $15,000 to $80,000 (over 80% of managers are eligible for bonuses).

Salary changes from last year’s study: Base salaries for individual contributors have increased 7% at level 1 and 1% at level 3, while salaries remained steady at level 2. For managers, salaries remained steady at level 1 while those at level 2 increased 3%. At level 3, the median base salary decreased by 4% ($10,000).

Data scientists continue to get top compensation for analytics professionals: Data scientists earn base salaries up to 39% higher than other predictive analytics professionals depending on job category.

Burtch16_Figure 9.jpg

A shift in the educational background of data scientists: 59% of level 1 individual contributors’ highest degree is a Master’s, a significant increase from last year’s 48%.

An increase in the number of U.S. citizens in the data science talent pool: Among level 1 individual contributors, only 43% of this year’s professionals are foreign-born vs. 53% last year.

It appears that the increase in the number of graduate-level programs in data science has started to make its mark and is contributing to an increase in the supply of entry-level data scientists with a Master’s degree. Other trends Burtch Works has observed in its recent conversations with data scientists are increased desire to work for “more mission-driven organizations attempting to make an impact on society” rather than large companies such as Facebook or Google and “the increasing pressure on many startups to show their value,” otherwise known as the coming burst of the Unicorn Bubble.

If we do see a contraction in startup activity and attractiveness over the next year, it may well be that larger and more stable companies, even in traditional industries, will become more desirable for budding—and even experienced—data scientists, regardless of their desire to “change the world.” The job opportunities—and the high compensation—will certainly be there as the practice of data science spreads into all corners of the economy. As Burtch Works predicts: “The use of data science will become more ubiquitous, the talent supply will improve, and there will be even more use cases for these techniques.”

Originally published on Forbes.com

Posted in Data Science | Tagged | Leave a comment

The Economic Impact of the Internet of Things

IoT_economic impact

Source: Digitlistmag

Posted in Internet of Things | Leave a comment