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‘We discovered 1320 new Teslas’

In less than twelve months’ time, smart algorithms scanned 10,000 companies for their contribution to a better world.

These smart algorithms can identify sustainable companies as well as pick up on hidden clues to help investors assess opportunities for return and risks earlier and more accurately.

To speed up the pace of innovation, APG acquired Deloitte’s data analysis team last year: thirteen women and men who apply artificial intelligence and big data to sustainable investment.

To find out, Entis scanned all annual reports, websites, and Chamber of Commerce registration details of these 10,000 companies using artificial intelligence and machine learning.’ Was it a lot of work?

Take the theme ‘affordable and sustainable energy:’ smart algorithms were able to analyze all sources for key words like ‘solar panels,’ ‘carbon emissions,’ and ‘climate change’ at lightning speed.

This typically indicates issues and future share price drops, according to Lazy Prices, a report by Harvard researchers analyzing the annual reports of American listed companies.

A study from Tilburg University showed that companies with a high level of diversity on the board achieve a 0.4 percent higher return per month than companies whose board is virtually homogenous.

Entis reproduced this study, but did not consider the results sufficiently convincing to include diversity as a criterium in our investment strategy as yet.’ What else has the Entis team worked on in the past year?

In future, this will allow the investment policy for our pension clients and their participants to benefit from Entis’ innovative insights on a daily basis.’ What challenges have you faced in the past year?

We want to consider this carefully: after all, we are now talking about a quantitative equities portfolio of around fifty billion euro under management on behalf of our pension clients.’ What can these innovative investment methods offer our pension fund clients and participants?

For example, it allows us to identify SDI companies and help achieve our clients’ sustainability ambitions: the 1320 Teslas offer us the opportunity to invest in this type of high-potential business early on.

That way, innovations in quantitative investment can help contribute to higher returns and thereby better pensions for the participants: our predictions of when to invest in which companies are getting increasingly accurate, and so is our assessment of risk.’ So Entis was worth the investment?

We are now exploring the possibility of granting other pension funds access to the classifications.’ How will investing look in the future - will humans still be involved, or will all investment decisions be made by algorithms and robots? ‘We

Our robo-advisor does the work, so you don’t have to.

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Narrator: We'll recommend a portfolio based on your responses, and we'll track your progress against the goal you've set.

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are designed to monitor portfolios on a daily basis and will also automatically rebalance as needed to keep the portfolio consistent with the client's selected risk profile.

Diversification, automatic investing, and rebalancing strategies do not ensure a profit and do not protect against losses.

Robot, MD: How Artificial Intelligence Will Revolutionize Health

Mechanized exoskeletons like Iron Man’s armor and Ellen Ripley’s power loader in Aliens helped create functional blueprints for exosuits being used in military and manufacturing applications, as well as for robotic devices like ReWalk which assists paralyzed individuals to sit, stand and walk.

As for the U.S. military’s research and development agency, the neural-interface technology developed by the Defense Advanced Research Projects Agency (DARPA) has helped amputees to experience touch with a prosthetic hand or control an advanced prosthetic arm with their mind.

Impact evaluation and market sizing from McKinsey estimates that AI will generate value between $3.5 trillion to $5.8 trillion annually across nine business functions in 19 industries.

According to a recent Accenture survey of health care executives, a majority (85 percent) agree that every human will be directly impacted daily by an AI-based decision within the next three years.

Accenture expects the AI health market to reach $6.6 billion by 2021, growing 40 percent annually, and potentially generating $150 billion in health care savings by 2026.

From sifting through piles of data and generating insights, imaging and diagnostics, drug discovery to remote patient monitoring and purpose-built digital assistants, AI will also impact every aspect of health care.

Frost and Sullivan, a consulting firm, predicts that by 2025, AI systems could be involved in nearly all aspects of global health care, from AI doctors responding to specific patient care needs to managing entire health care systems.

An International Data Corporation (IDC) report estimates that in 2013 the volume of global health care data was nearly 150 billion gigabytes, a number it expects will grow 15 times by 2020 to roughly 2.3 trillion gigabytes.

Even if we had the time and resources to integrate and analyze the data, the overwhelming nature of data collection rapidly outpaces our capacity to process, associate and find patterns and knowledge.

Armed with this extraordinary ability to draw correlation and connections between seemingly distinct and unrelated data sets and tools for natural language processing, AI systems can tackle challenges for which we previously had no other means of recourse.

Accenture’s 2018 Consumer Survey on Digital Health found 75 percent of U.S. adults believe it’s important to use digital technology to manage their health, with nearly half using their mobile devices and another third using wearables to do so.

The Fitbit coach app, paired with a Fitbit wearable, has one of the largest health databases, and takes advantage of complex algorithms to extract meaningful insights from user data, to provide highly-tailored workout recommendations.

Early trials of the wearable among 500 patients registered an 87 percent successful cancer detection rate, even with patients with dense breast tissue, which often hides small tumors.

Another AI-driven cancer detection system built by researchers at the University of Heidelberg in Germany, pitted an AI system against a team of dermatologists and found that the AI achieved a 95 percent accuracy in identifying skin cancers, compared to the 86.6 percent achieved by trained professionals.

The proliferation of consumer wearables and other medical devices combined with AI is also being applied to oversee early-stage heart disease, enabling doctors and other caregivers to better monitor and detect potentially life-threatening events.

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