Ricardo De Armas

  • Student

Submitted

NewYork-Presbyterian: Becoming the Hospital of the Future
Ricardo De Armas
Posted on November 13, 2018 at 2:39 pm
NewYork-Presbyterian hospital is using machine learning technology to streamline hospital operations, free up more time for clinicians, and improve overall quality of care.

Activity Feed

On November 15, 2018, Ricardo De Armas commented on Does the CIA want your geopolitical input? Yes, it actually does! :

Matt, very interesting piece on how open innovation is being used by intelligence to crowd-source information. I too am concerned about the potential for abuse by the public and the volume of information entering the funnel. As some have touched upon, I wonder what role this information will play in investigations by intelligence agencies. Will it be used as supplemental information in an already-targeted investigation or as a screening tool for new, potential security threats. In either case, this will create new challenges for agencies as they will have to read through massive amounts of information (some potentially falsified) and decide which data merits more attention and priority than others. As I would imagine, if this platform exists for reporting public concerns, everything on that database should represent some degree of public threat and it will be up to the interpreter of that data to decide what is important and what is not. Perhaps this is an area where machine learning can be used to screen and make decisions or alerts based on a historical database of security threats.

On November 15, 2018, Ricardo De Armas commented on UNICEF: Open innovation to tackle humanitarian crises :

KRiver, thank you for the wonderful article on the use of open innovation at UNICEF. It is great to see an example of this as it applies to non-profits, especially in the humanitarian sector. As I read your piece, the big question that came to my mind was access and whether an open innovation platform is reaching the most vulnerable and affected populations. I agree that this is a tremendous step forward in the direction of open collaboration and the sharing of ideas and key learnings. I certainly believe this will foster a community of more conversation and engagement in UNICEF’s projects. However, I wonder how the local voice is being heard given that the majority of these populations do not have reliable access to the internet. As others have mentioned above, this is a great movement and I would recommend that the next step be in the direction of creating access for these local, inflicted populations.

On November 15, 2018, Ricardo De Armas commented on 3D-printed razor handles – the best a man can get? :

Ldepoorter, very interesting read on how Gillette is using 3D printing to stay relevant. While I find this topic fascinating, I too am skeptical about the direction they are taking. My reasons why:

1) It does not meet the consumer need
Most consumers want a razor that is affordable and convenient. As you discussed, this is what made Dollar Shave club so successful in just a few years. They realized that men go through razors frequently and that it is very expensive to replace them. So what did they do: they created a $1 subscription and delivered it right to your door. Gillette has missed the ball on this value proposition. Instead, they are focusing on a niche group of men who are willing to spend $19-45 on a customizable handle that does not make their shave neither cheaper nor more convenient.

2) The money is in blades, not handles
What made Gillette and other razor-makers successful is that they created a product with a constant revenue stream. You buy a handle once and then you spend to replace the blades every 1-2 weeks. Gillette is using 3D printing as a way to salvage declining revenues, but it is difficult to do that when you offer one product with an extremely long inter-purchase cycle. Once a customer buys the handle, you have exhausted that customer’s revenue stream.

3) Customization is not scalable
As we learned in TOM, customization introduces longer lead times in operations. As such, it will be difficult to scale a product that is not reproduceable. I imagine this market will remain small and may introduce more variation in their already efficient operations of streamlined razors.

User deleted this comment on November 15, 2018
On November 15, 2018, Ricardo De Armas commented on 3D-printed razor handles – the best a man can get? :

Ldepoorter, very interesting read on how Gillette is using 3D printing to stay relevant. While I find this topic fascinating, I too am skeptical about the direction they are taking. My reasons why:

1) It does not meet the consumer need
Most consumers want a razor that is affordable and convenient. As you discussed, this is what made Dollar Shave club so successful in just a few years. They realized that men go through razors frequently and that it is very expensive to replace them. So what did they do: they created a $1 subscription and delivered it right to your door. Gillette has missed the ball on this value proposition. Instead, they are focusing on a niche group of men who are willing to spend $19-45 on a customizable blade that does not make their shave neither cheaper nor more convenient.

2) The money is in blades, not handles
What made Gillette and other razor-makers successful is that they created a product with a constant revenue stream. You buy a handle once and then you spend to replace the blades every 1-2 weeks. Gillette is using 3D printing as a way to salvage declining revenues, but it is difficult to do when you offer one product with an extremely long inter-purchase cycle. Once a customer buys the handle, you have exhausted that customer’s revenue stream.

3) Customization is not scalable
As we learned in TOM, customization introduces longer lead times in operations. As such, it will be difficult to scale a product that is not reproduceable. I imagine this market will remain small and may introduce more variation in their efficient operations of uniform razors.

On November 15, 2018, Ricardo De Armas commented on The long awaited tech disruption of the legal sector :

Geek Squad, very interesting piece on the application of AI in the legal space. As I read your piece, I drew a similar analogy to the work of junior radiologists and pathologists in medicine. As AI is becoming more advanced in these spaces, there is a growing consensus that machines will be better equipped to read high volumes of imaging studies with less variability. That being said, the job of these physicians will not be replaced, but rather facilitated by machines. I see something similar happening at Clifford Chance where AI has facilitated the role of Junior Lawyers such that they will be spending less time reading legal documents. This will shift their work from the mundane to the complex; that is, spending more time interpreting the AI’s output. There are ethical and legal implications of shifting major responsibilities like M&A’s to machines. I believe a human will always be required in those transactions and AI is actually allowing us to spend more time on these more complex tasks. With that said, I don’t believe Junior Lawyers are at risk of being replaced, but rather, these positions will require a higher level of knowledge and training to be able to deal with higher-level analytical tasks.

On November 15, 2018, Ricardo De Armas commented on Bioprinting: How the Manufacturing of Human Organs Will Disrupt Healthcare :

RJ – very interesting piece on Organovo and their use of 3D bioprinting. As has been commented, FDA regulations are an important bottleneck in the advancement of bioprinting. However, as all things in medicine, the policies they put in place for animal testing first and clinical trials second exist for the sole safety of the patient. Actually, I would argue that FDA regulation is NOT the limiting factor in the advancement of bioprinting. The limiting factor is the science. It is true that bioprinting will solve many problems in medicine, notably: 1) alleviate the demand for organ transplants, 2) get rid of the need for immunosuppression or risk of transplant rejection, 3) it is a more cost effective option. However, the MAIN limitation of 3D bioprinting of organs is that we can’t get organs to function the way they normally would. Bioprinting is great at making structure (eg, making a liver look like a liver), but has not been successful in function (eg, making a liver work like a liver). There are many reasons for this, a big one being that we can’t get the right blood supply to the organ so the organ will often die. With that said, I still see a bright future for 3D bioprinting, and certainly companies like Organovo will be in the forefront in the advancement of functional organs.

On November 15, 2018, Ricardo De Armas commented on Fitbit: Will Machine Learning Help Fitbit Change Consumer Health and Regain Leadership in Tech Wearables? :

Jake – I really enjoyed reading your article and learning more about the direction that FitBit is taking. I agree with the above comments that FitBit is in a difficult position in the competition for wrist share. It seems that the winner will likely be the company that can not only deliver the most services on a single platform, but that will integrate most effectively into the daily lifestyle of the consumer. I think FitBit is realizing this, and as you point out, is changing course into a direction where it has (until now) had a leg up on its competitors – the healthcare delivery space. I see a great potential for FitBit being used by patients and insurance companies to incentivize healthy behaviors. It is a win-win for both parties: the consumer wants to become healthier, and the insurance companies benefit from having a healthier pool of patients that are less likely to require acute medical interventions. The future of healthcare is trending towards preventative medicine. This will be an area where FitBit will thrive given its historic success in the clinical community and also, where machine learning will be most useful as hospitals realize the importance of collecting more patient data and making that data available to improve outcomes and reduce health care spending.