#futureofhealth a combination of #robotics and #ai will help us stay healthy and independent

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Problem:

As we age, mental and physical challenges do creep up. And we need assistance to stay healthy, mobile, and independent.

Solutions:

A combination of a trained AI and installed sensor platform in mock living room, kitchen, hospital room, and retail space.

Features:

  • It can do everything from “see” someone who has fallen (and help them if they can’t get up)
  • answer health-related questions, such as “what are symptoms of a stroke?”,
  • Scan and monitor health data: read heart rate, heart rate variability, and breathing rate.

Open Questions:

  • How do people want to interact with a computer when they’re sick?
  • What’s the most-effective way to connect this data to third parties, such as emergency medical services?
  • Where do you store a robot in someone’s home?

Implementation:

  • speech-to-text
  • text-to-speech
  • natural language processing
  • Chat bot interface for Q&A,
  • visual recognition technology (the systems eyes)
  • are funneled and analyzed through a body of the system, e.g. a SoftBank Pepper robot connected to the cloud.

Example Technology:

  • IBM Multi-Purpose Eldercare Robot Assistant (IBM MERA )
  • http://sh.rice.edu/camera_vitals.html

More on IBM MERA:

  •  The sensor network built into the lab is connected to that same toolkit of technology. With sensors in the floor, walls, ceiling, and other objects, like wearables, this cognitive agent “collective” can learn patterns of how and when the elderly wake up in the morning, eat breakfast, exercise, or take medication — and offer verbal reminders to take a medication if they forget (or maybe change the light color for those who are hearing impaired). Some of this IBM Accessibility technology is already out in the real world, like the homes of some over-65 residents of Bolzano, Italy, where we’re testing solutions with local government to help their citizens live independently, longer.

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#FutureOfWork: The impact of #AI on the workplace and employee engagement

• The digital workplace merges work and life — a virtual space with applications, services and information on demand. For users, this means access to the technology they need, when they need it, on whichever device they prefer to use.

• Employees expect their enterprise systems to be as engaging, exciting and intuitive as consumer devices. Technology research company Gartner calls this a shift from technology-literate people to people-literate technology.

• Companies now have more exquisitely detailed data about how their products and services are used than they ever had before, thanks to a vast network of sensors and advanced analytic tools.

• Cognitive systems can parse all that data and learn what employees need to do their job better — even if they don’t yet know it themselves. Cognitive systems will deliver the ability to visualize vast amounts of data, curated and analyzed, for a unique task and a unique user.

• The workplace of the future will embrace emerging new cognitive and analytic capabilities. These tools can provide insights into how employees engage most effectively, what the best technologies are for each task and for each individual, and help provide a seamless work environment — an environment that will help to attract and retain the best talent.

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#futureofhealth: research shows metformin might slow aging and cancer


Harvard researchers discover an ancient, unified mechanism by which metformin both kills cancer cells and extends lifespan with anti-aging effects. from longevity

  • Hypothesis: Does Metformin reduces the statistical occurrence of a cancer and other age related metabolic diseases in patients?
  • What is Metformin: A substance marketed under the tradename Glucophage among others, is the first-line medication for the treatment of type 2 diabetes.[3][4]
  • Data Analysis:
    • Multiple Studies show that patients treated with Metformin show a 30+ percent reduction in cancer risk.[21][22][23][24]
    • Data on the relation between Metformin and age related metabolic diseases[1]
  • Further Questions you can help me with:
    • How does this effect occur?
    • How can Metformin be produced? Can it be produced in “home/popup labs” also in developing countries?
  • Further Information:
    • In the autumn of 2015, the US drug agency FDA approved a study with 3,000 volunteers for the year 2016. It is intended to participate in persons aged between 70 and 80 who are suffering from cancer, cardiovascular disease or disorders of cognition (eg dementia) Or have an increased risk of this. It is to be investigated whether the life expectancy of the subjects can be prolonged by metformin and the course of already existing diseases is influenced positively. The FDA’s decision attracted particular attention as it approved for the first time a study aimed not directly at preventing, treating or curing a disease, but slowing down the aging process.[26][27][28]

 

 

 

#futureofwork: How AI will change fintech jobs, and advice to college grads how to benefit from this

  • The automation of the finance industry will hollow out jobs in that field in the same way that robotics and other technologies have reduced manufacturing employment. That is how:
    • Floor trader, of course, has long been the archetypal job on stock exchanges. But there are precious few left of them.
      • Most trading jobs have been taken over by servers running trading algorithms.
    • Much of Wall Street’s back office operations involve the performance of relatively structured tasks.
      • Many of these could probably be taken over by tools like robotic process automation, which can reach into multiple systems for needed data and apply rule-based decision logic.
    • Regulatory compliance has been one of the few growth areas in recent years on Wall Street, but systems from Digital Reasoning are automating internal fraud investigations.
      • IpSoft’s Amelia is focused in part on facilitating compliance in customer conversations.
      • Narrative Science automates the creation of anti-money laundering reports.
      • RAGE Frameworks automates the extraction of data for credit and wealth management, and can create automated compliance reports on the process.
    • Many entry-level jobs on Wall Street involve combing through data to make a case for a particular financial transaction. That is an it job:
      • Kensho, for example, is a startup that analyzes data on markets and generates reports on their implications.
  • Another common task of financial analysts and attorneys is to prepare disclosure data on a company’s financial history for potential investors.
    • iDisclose does that automatically.
  • Another common role in the finance industry is to provide investment advice.
    • The “robo-advisor” concept / automated advice is becoming pervasive at the lower end of investing.
      • Vanguard, Charles Schwab, and Fidelity have all taken some steps in that direction
      • startups like Betterment, Wealthfront, and Personal Capital are pursuing Millennial customers with money to invest.
      • The capabilities already exist for higher-end versions of robo-advice, and a few banks like UBS have begun to explore them.
      • Investment advice is complex, data-intensive, and rapidly changing, so it seems very likely that there will be substantially fewer human investment advisors in the future.
  • There are other finance-oriented tasks that will be performed by automation, including some new ones involving ongoing financial management for consumers that should have been done by banks long ago.
  • It is a process: Job after job will be whittled away over time. Entry-level jobs will probably be the hardest hit; if you can teach a recent college grad to do a task, you can probably teach a machine to do it.
  • Advice for entry level grads:
    • There will be a substantial number of jobs that involve working alongside machines.
    • If you’re already familiar with key financial processes, you’ll have a much better chance of keeping your job if you learn to work alongside smart machines that perform key aspects of those processes — monitoring the machines, fixing them, and picking up the ball when they drop it.
    • Or you can become skilled at overseeing them, understanding when the financial world has changed and when the algorithms are no longer well-equipped to deal with it.
    • Finally, of course, there will be many jobs involved in building intelligent finance systems.

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Regular Feedback Cycles Pattern: How I should embrace more feedback

Feedback is the most valuable thing that one might get, as without feedback it is tremendously hard to improve. While I think I do a good job, I want to do a great job. To enable this I will apply the following at least once a month:
  • I consider who can help me grow and I seek them out.
  • I am clear that I want honest feedback.
  • I ask open-ended questions (not yes or no) on what I can do better in the future.
  • I listen and ensure I am open to hear the feedback.
  • I express thanks and play back the feedback that I heard.
  • I ask if I accurately heard the feedback—if I need to, make adjustments and play back again.
  • I decide how to move forward

You can find the complete pattern description below.

I will apply this in the private and the professional areas. As I think growth is important in every part of my life. The first persons I will ask will be four persons which opinions I value: my brother, my girlfriend, my manager and a client. In fact I will schedule the first meeting right now.
I can only encourage you to do the same and I will keep you up to date how this works out for me.
THE PATTERN DESCRIPTION:
name:
regular feedback cycles
problem:
How to realise what is the best area to spend your limited time improving?
context/situation:
You are active in your life every day, at work or at home. And you do your daily routines and interactions with others. And you produce results.
conflicting issues:

There is you who wants to get stuff done and don’t waste time on feedback.

There is you who needs to know where to spend your limited time to improve.

There is other people who expect you to improve but don’t speak their mind for not wanting to offend you or not having the time.

There is other people who also have limited time to give you feedback.

solution:
          Establish a feedback culture with important people/stakeholders in your life:
          I consider who can help me grow and I seek them out.
          I am clear that I want honest feedback.
          I ask open-ended questions (not yes or no) on what I can do better in the future.
          – what you can keep?
          – what should start?
        – what you should stop?
        I listen and ensure I am open to hear the feedback.
        I express thanks and play back the feedback that I heard.
        I ask if I accurately heard the feedback—if I need to, make adjustments and play back again.
        I decide how to move forward
resulting context:

benefits:

People get comfortable giving you feedback.

You get feedback and know where to spend you time to improve.

issues to resolve:

how to find the right people to get you feedback.

how to do it regularly.

how to act on the feedback.

related patterns:

Future of manufacturing? Build large scale 3d objects fast and efficient, combining AI and 3d printing and give robots sight and speed the process up.

“We wanted to push the boundaries of how intricate we could design things through computation and how we could create them through 3D printing,” AiBuild says. 3D printing may be seen as the future of fabrication but it can be an expensive, time-consuming, and unscalable endeavour.

To scale up the printing process, AiBuild strapped foam guns to KUKA robotic arms and programmed them to print intricate structures.To cut costs and expedite construction, they combined the standard layer-by-layer design with a lattice work design that printed filament at angles while small fans simultaneously cooled and hardened the material.

Fabrication leaves little room for error, so the robots had to print at a snail’s pace, excreting filament precisely and uniformly, then waiting for it to dry. If Ai Build wanted quicker – and thus cheaper – printing, it would either risk structural defects or have to overcome a fundamental flaw in robotics – blindness.

They attached cameras to their robots and used machine vision algorithms to analyze the structures as they were being printed. To create a feedback loop between the physical environment and the digital environment.

With its new set of eyes, the robotic arm could detect defects and compensate for them in subsequent layers.

The advantages are

  • high speed, because errors can be seen and corrected by the robot itself.
  • cost, less material and time is needed and
  • structures can be build as a single, complete unit

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