Apple Watch Put to the Phoneless Challenge
Over a seven-day period last week, the Loup Ventures team decided to go phoneless. We used only a cellular Apple Watch S4 and left our iPhones turned off.
- Apple Watch is the most viable (and most expensive) wearable available today to go phoneless.
- The Watch does not replace the iPhone, but using the Watch in lieu of the phone made our lives mostly better.
- We no longer believe an Apple Glasses product (best guess Dec 2021 launch) will cannibalize iPhone, rather they’re complementary.
- We spent significantly less time consuming media, which gave us a sense of having more free time.
- Battery life was the most acute challenge we faced for the phoneless use case (on average lasting until late afternoon).
We wrote more about the psychology of going lite here, so this note’s focus is the functionality of the Apple Watch as an alternative to the iPhone.
An Important Point Before We Begin
We set out to use the Apple Watch as our only device – a use case for which it is not intended. It’s clear that in terms of battery life, functionality, and the user experience, Apple designed the Apple Watch as a companion device for the iPhone. The cellular Apple Watch is great for temporarily leaving your phone behind, but not for powering it down permanently.
Likes:
Going phoneless was less painful than we thought it would be. Even core phone use cases like making and receiving calls (with AirPods), reading emails, and checking calendars are easy on an Apple Watch. There is certainly not feature parity from iPhone to Apple Watch, but the Apple Watch fared mostly well doing the basics. Below are our top likes:
- Email: Reading short (two-sentence) emails is easy on Apple Watch.
- Siri: Dictation on Apple Watch works exceptionally well and solves much of the text input challenge.
- iMessage: Receiving, reading and responding to iMessages on Apple Watch is simple.
- Apple Pay: We finally broke the habit of reaching into our pocket to use Apple Pay on iPhone. The Watch is a better tool for Apple Pay.
- Peace of mind: It’s harder to lose your Watch because it stays on your wrist. We lose our phones, if only temporarily, often.
Dislikes:
Throughout the week there were lots of things we couldn’t do or didn’t want to take the extra time to do on the Apple Watch. Below are our top dislikes:
- Email: Even though Siri dictation works well, sending a reply of more than a sentence or two is a hassle. If Siri made mistakes, the editing process is laborious. Instead, the best option is to wait and send the email later via laptop (a productivity hit). One of us was asked every day to re-authenticate Google email accounts on the iPhone to push to the Watch. We would have expected a better experience receiving non-iCloud emails on Apple Watch.
- Messages: We were consistently having trouble sending non-iMessage messages over cellular.
- Photos: Camera and Photos are daily iPhone uses cases. With Apple Watch, you can’t take a photo or send a photo already in your library.
- Maps: We realized how dependent we were on Google Maps/Waze on iPhone. At one point, one of us pulled out a laptop, connected to a distant wi-fi network, and found a route on Google Maps (via web). Throughout the week, we learned to use Apple Maps for turn by turn directions with some level of success, but not as seamless as using Google Maps iOS app.
- Privacy: Because dictation is the optimal text input, composing a message in public can’t be done privately like it can be on an iPhone.
- Compatibility: We couldn’t connect to Sonos or CarPlay. Also, there was limited app availability and functionally.
- Conferencing: Apple Watch isn’t capable of merging two calls into a conference.
Apple Watch Experiment Observations
Quotes on behavior:
- Often reaching for my phone even though it’s not in my pocket.
- Think cannibalization risk to phones (from any wearable) is lower than I did before.
- Can’t really text privately in public (Scribble takes too long for a text of any length, so Siri/dictation is the only way to text).
- Can’t multi task.
- Dictation for texting is really good.
- Scribble worked better than I thought.
Battery:
- Battery died at 1pm.
- Battery died at 3pm.
- Battery died at 5pm.
- Battery died at 5pm.
- Battery died at 7pm.
- Battery failed on conference call.
Apps:
- Asked to enter email credentials on phone.
- Asked to upgrade to AnyList Complete to access my shopping list on my watch.
- Asked to set up August app on my phone.
- Felt like the iMessages app on Mac is a lifesaver.
- Email on desktop is so much better, and email takes so long (seems not to be push) on the Apple Watch.
- Saw iMessage threads turn to text message threads on the Watch, and texts won’t go through.
- Can’t send iMessages.
- Can’t add a contact.
- Can’t search emails.
- Can’t scan a document to email or save to cloud storage.
- Can’t Venmo.
- Can’t send iMessages consistently (cellular and WiFi).
- Can’t use grocery list app (AnyList) at grocery store. Don’t have premium access to Watch app. Used iPad instead.
- Parking app not available.
- Calendar not syncing in a timely manner.
- No mobile web.
- August locks don’t work.
- Can’t add or fix a Wemo switch.
- Can’t edit a note.
Calling:
- Watch connectivity (either the cellular or the bluetooth connection) was inconsistent. Not a reliable phone connection for longer calls.
- It’s too easy to hang up on a call.
- Cant add participates on a conference calls.
- Can’t tap a phone number in Calendar to place a call.
- Choppy cell coverage.
Photos:
- Can’t text a picture.
- Can’t take a picture of the whiteboard with my phone, needed to use MacBook Pro Photo Booth app.
- No camera.
- Can’t easily add a photo to photostream.
Connecting:
- Can’t use the Apple TV Remote app without having iPhone in range and connected to the same network.
- AirPods don’t connect quickly enough to seamlessly pick up a call on the Watch when I’m not already wearing AirPods.
- Can’t control Sonos.
- Can’t Airplay a phone call from Watch to HomePod.
- Changing settings in Home app needs to be from the phone.
- Can’t pair with Bluetooth in car.
- Can’t start a hotspot.
Maps:
- Can’t share a location from the maps app.
- Needed addresses in my events for maps/directions.
Other:
- Asked to view image on iPhone.
- Asked to view .gif on iPhone.
Disclaimer: We actively write about the themes in which we invest or may invest: virtual reality, augmented reality, artificial intelligence, and robotics. From time to time, we may write about companies that are in our portfolio. As managers of the portfolio, we may earn carried interest, management fees or other compensation from such portfolio. Content on this site including opinions on specific themes in technology, market estimates, and estimates and commentary regarding publicly traded or private companies is not intended for use in making any investment decisions and provided solely for informational purposes. We hold no obligation to update any of our projections and the content on this site should not be relied upon. We express no warranties about any estimates or opinions we make.
Apple’s Upcoming “There’s More in the Making” Event
Apple announced (October 18th) a special event in Brooklyn on October 30th. This is the fifth time in seven years that Apple has hosted two fall product events. Typically, the second event is less impactful than the September iPhone launch. That said, the collective upcoming product announcements will have an incremental impact on Apple’s overall business.
Key takeaways
- We expect the event to over-index to refreshes of products used by creative professionals, based on the numerous artful event invite designs and the “making” reference.
- This likely includes a new, lower-cost MacBook, new iPad Pros and Mac Mini, along with an outside chance of an iMac refresh.
- Collectively, we estimate these products account for about 10% of Apple’s overall revenue (Mac and iPad segments in total will account for 17% of revenue in FY18).
- Exiting the October 30th event, Apple will have refreshed products that account for about 50% of revenue in FY19. This compares to last year when the company refreshed products accounting for 37% of revenue. This is a near-term (1 year) positive for unit growth and, while our estimates remain unchanged, our confidence in those estimates has increased.
The Bigger Picture: Apple as a Service
Though the October event is incremental to Apple’s business, the specifics are less relevant to Apple’s long-term (> 1 year) valuation. Taking a step back, the historical view is that shares of AAPL move higher in anticipation of new products and trade off after they are announced. Investors are increasingly less focused on the latest features around product announcements and more focused on the ability of these products to retain and slightly grow its current user base with increasing revenue per user. We call this emerging view Apple as a Service: stable iPhone business, Services growth, a significant capital return, and new markets.
Disclaimer: We actively write about the themes in which we invest or may invest: virtual reality, augmented reality, artificial intelligence, and robotics. From time to time, we may write about companies that are in our portfolio. As managers of the portfolio, we may earn carried interest, management fees or other compensation from such portfolio. Content on this site including opinions on specific themes in technology, market estimates, and estimates and commentary regarding publicly traded or private companies is not intended for use in making any investment decisions and provided solely for informational purposes. We hold no obligation to update any of our projections and the content on this site should not be relied upon. We express no warranties about any estimates or opinions we make.
Google’s Cancer-Detecting AI and The Future of Work
Google recently announced a milestone for its applications of deep-learning in medicine. Their algorithm for detecting metastatic breast cancer, Lymph Node Assistant (LYNA), is not only able to positively classify metastatic cancer with 99% accuracy but is also able to accurately highlight the location of the cancerous cells and other suspicious regions within Lymph nodes. In brief:
- Google announced it has developed a deep-learning algorithm capable of more accurately identifying metastatic cancer with 99% accuracy. One recent study found that humans miss metastatic cancer 62% of the time when under time constraints.
- Google’s technology won’t replace Pathologists, who add the critical human element of considering diagnoses in context on a case by case basis, but it offers Pathologists a new and important tool.
- This technology will be to enable doctors to more accurately diagnose conditions in less time.
- We consider this human-in-the-loop automation — a collaboration between human and machine that will make us more productive.
Human-in-the-Loop Automation
Even though the algorithm by itself is very successful, the best results are shown when pathologists are working with LYNA, suggesting the future is using machine learning to enhance the capabilities of human doctors. Human-in-the-loop automation involves human labor augmented – not replaced – by machines. In this case, a machine would make a first pass. screening samples and flagging possible positives for human review. In a study Google conducted, six board-certified pathologists worked alongside LYNA. The pathologists reported that LYNA made diagnosis easier and, on average, cut the review time per slide in half. This is significant because studies have shown that under time pressure, sensitivity for detecting small metastasis (True Positive / (True Positive + False Negative)) can be as low as 38%. The study also showed a reduction in the rate of missed micrometastases classification by a factor of two.
Limitations Exist, but Results Are Promising
There is still a long way to commercial use and clinical trials will need to be done. Some limitations of the two studies are limited data set sizes and simplified workflow of diagnosis. The studies only looked at one slide per patient but typically multiple will be used. With those limitations in mind, these early results are still very impressive. We are in the early days of integrating deep-learning technology into medicine and are already able to see the dramatic improvement it offers in accuracy. The cost of this accuracy an increase in false positives. This is another reason why pathologists should still be the decision makers of the diagnosis because they have a contextual understanding of these implications that algorithms cannot consider.
Doctors still have contextual awareness and ability to view diagnosis and symptoms on a case-by-case basis to determine the best treatment plan. With the use of machine learning, doctors will be able to navigate this process more quickly and with better accuracy. The most important takeaway from this announcement is that we are getting closer to working versions of deep-learning applications in medicine and that it has a demonstrated power to enhance the ability of doctors.
Disclaimer: We actively write about the themes in which we invest or may invest: virtual reality, augmented reality, artificial intelligence, and robotics. From time to time, we may write about companies that are in our portfolio. As managers of the portfolio, we may earn carried interest, management fees or other compensation from such portfolio. Content on this site including opinions on specific themes in technology, market estimates, and estimates and commentary regarding publicly traded or private companies is not intended for use in making any investment decisions and provided solely for informational purposes. We hold no obligation to update any of our projections and the content on this site should not be relied upon. We express no warranties about any estimates or opinions we make.