Futapy

HW 10

per http://informationcomputingandthefuture.blogspot.com/p/hw-10.html

A1)

A. Decide on your interest

There is a trend in batteries in consumer devices such as laptop computers, cell phones, electric cars and motorcycles, and others yet to be invented requires batteries to be smaller and lighter and more powerful. At the same time, the power density of these batteries has necessitated device manufactures to monitor state of charge, charge rate, under or over-voltage conditions, temperature, and perhaps even shock or other parameters to ensure safe operating conditions and long battery life. As a result replacing the battery in a modern device is difficult or impossible outside of a technical service center.

Changing a laptop battery involves looking up the kind of laptop battery needed, ordering it, opening the laptop, swapping the battery, closing the laptop back up and testing it.

B. Write down more steps

using a search engine and the model number, search for the model of the computer and available batteries. There are already companies like iFixit that have a repository of battery information and make the parts available at reasonable prices. Once the battery arrives, search up on youtube a video of how to open the laptop and follow those directions. If no videos exist, examine the device to try to find fasteners to remove, and start removing fasteners and parts until the battery is visible. Usually this involves taking out many tiny screws and keeping track of them; a magnetic mat is useful to keep track of what has been removed from where. Then carefully remove the battery connector, being careful not to damage any connections. Remove the adhesive holding in the battery; this sometimes needs a little heat from a hairdryer, heat gun or other heating device to fully loosen. Once the old battery is out, apply some new adhesive to the new battery if needed, put it into place, reattach the connectors, reassemble the removed parts, replace all the fasteners, and charge the device.

C. Find "pain points"

D. Invent solution(s)!

A solution to the first pain point would be a standard or set of standards for laptop batteries. Most modern batteries are flat, lithium-ion based, and need careful monitoring through charging and discharging. A standard set of sizes and voltage ranges would help, and a standard way to communicate with a battery-specific monitoring device on the battery would be needed. The monitoring device would need a way to communicate back its capabilities (such as the SMART format for hard drives does today), would need to be able to serialize communications among multiple batteries in series (such as is done with individually addressable RGB Christmas lights in a series string), and a standard charging capability would need to be negotiated (as is already done with electric cars and their chargers) but on a single-battery scale.

The second and third pain points could be addressed with an invention I'll call the "battery door", or a removable compartment door that would expose the location of the battery within the device. The door could be held in place with friction or some easy to operate screw or fastener such as Velcro. This would save a lot of effort disassembling a unique device to find the battery.

The fourth pain point could be addressed by using some easy to use and standardized method such as screws or clamps to hold the battery to the device instead of industrial-strength adhesive. The battery standard for physical size and form could include holes or lugs for screws or standardized slots for a friction fit, much like 3.5 inch hard drives have standard screw holes.

E. The lean canvas

The problem: laptop and portable device batteries, a consumable component in an otherwise durable device, are proprietary and cannot be changed by the typical consumer without great effort either in time or investment in professional repairs. This leads to consumer frustration, more e-waste than necessary when consumers choose to simply buy new rather than refurbish a battery, dissatisfaction with the brands (Apple, HP) that use these difficult and proprietary systems, and (one can hope) regulator scrutiny for monopolistic or anti-consumer practices.

Existing alternatives: highly engineered but proprietary and incompatible high-energy-density battery systems, or low-energy-density but standard form factors (like AA, AAA, C) non-rechargable batteries, or high-energy-density but bulky non-smart batteries such as 18650 round lithum-ion cells found in high power flashlights or bulkier equipment.

The solution: I wish to market an open laptop battery standard that is flexible enough to allow for capacity growth within the same physical form, evolving forms (scaled up or scaled down) as device demand evolves over time or different applications, a standard built-in battery monitoring module to allow different battery chemistries and capabilities to be used in the same device, and a reference chassis access implementation to make changing device batteries as easy as changing flashlight batteries.

Unique value proposition: Using my system will build brand loyalty and ensure compliance with any "right to repair" laws, ease the engineering burden of supporting multiple battery monitoring systems, allow competition and therefore lower prices for standardized battery components, and market items as longer-lasting, lower e-waste and more desirable overall.

High level concept: "It's like flashlight batteries for laptops and other portable devices, but better"

Unfair advantage: As the first to market, we can write the standards around the least expensive technology and make our system the household name in portable device battery standards.

Key metrics: number of manufactures that have committed to the standard and how many devices they will standardize annually, number of smart batteries manufactured or shipped, name recognition surveys and sentiment analysis among consumers

Channels:

Customer segments:

Early adopters:

Cost structure: fixed costs for research, early-adopter outreach, engineering the development of the standard, testing prototypes and publicity; variable costs for production samples; potentially patent license fees

Revenue streams: Manufacturer licenses (similar to USB or Bluetooth), profit on compatible units sold under the original name brand, or do like Facebook, Amazon and Google which was to make something big and important first, and then figure out how to make money on it.

(NOTE: I just noticed at the bottom of the LEAN canvas map there is a canvas fill order and some other directions for examining risks; I did them in the order listed above)

F. Customer discovery: I asked my wife if she wanted this since her Apple laptop battery just died after 4 years, she said "yes, I'd like that".

A2) This is a very large topic; I keep getting sucked into interesting internet links and trying to categorize them appropriately. I have 7 pages of blurbs and links, with some prose of ideas intermixed.

I found an entire subreddit just about GPT3. It is so easy to get lost in the conversation; the debate on how exactly will be be able to tell human from bot, what is in store for GPT4, what OpenAI is up to, who is also trying to make a large scale AI, etc. I'm very interested in the ethical questions. At the start of this project I had wondered aloud if I could get it to write my paper for me; clearly the answer now is yes and even exploring this topic is interesting. I wrote "in industry, we think nothing of programmers looking up the solution to a thorny problem on StackExchange. 30 years ago a programmer was expected to know their language and environment inside and out, or at least have books on the shelf for reference. 15 years ago in a job interview, when asked about an obscure setting in a commercial software package, I replied “That’s what Google is for. You have Google here, right?” and got the job. Today, I’ve thought that programming constructs such as Pandas in Python or anything related to Hadoop would be almost useless without a search engine due to the rapid pace of change and the speed at which new features are implemented and old techniques are deprecated.  I can foresee a time, soon, when a writer without AI access will be as useless as a Pandas programmer without online access." It would be interesting to pay for enough access to the GPT-3 based tool to use this as a writing prompt at the shortly.ai website.

But I am at least making forward progress. I have roughly 60 source links which is far, far too much to synthesize in the time remaining, but I don't want to miss anything profound. So the very next task is to start cutting what I won't be able to get to and continue writing about what I can in some detail, enough to make it a cohesive paper and presentation. I think I can do it.

A3) OK, the book Predictions 138-157, essays about and predictions by Stephen J. Gould and Susan Greenfield. Gould is a popularizer in the same arena as Rickard Dawkins. He is know for his work with zoologist Niles Eldredge on the theory of "punctuated equilibria", in which Darwinian evolution is not constant but rather species stay the same over long periods with bursts of development during which new species are formed. He claims that the fossil record show no evidence of gradual changes within a species. He is critical of evolutionary psychology in that it often speculates to the usefulness of a human behavior trait in the past, which he calls "speculative storytelling" but not science. He hold interesting views on man's self-importance and sees that humanity is the creation of random motion rather than the inevitable result of natural selection for increased complexity. Interestingly he refuses to offer a prediction for the next century, seeing the major events of the last one as arising unpredictably and how complex systems can be destroyed in a tiny fraction of the time that it took to create them. "Even to anticipate a single scientific breakthrough in the next century and then to speculate about its implications for human life carries our hopes for prophecy too far". Clearly that's a radical opinion, but one that has been informed by a lifetime of looking at the fossil record and the amazing diversity that once existed but was erased in a geological blink of an eye.

Agree: Complex systems undergo changes rapidly; we are likely the cusp of such profound change in our environment and our technology that the only accurate prediction would be that it will definitely be different. Disagree: he completely ignores extrapolation from trends as a useful tool for predicting in the near term.

Greenfield has been troubled by the riddle of consciousness, the "hard problem" of how do physical phenomena in the brain translate to a subjective experience, a sense of self? She has studied psychology, experimental psychology, neuroscience, synaptic pharmacology. She is making progress linking Alzheimer's disease and Parkinson's (at the time of this writing). She is interested in brain imaging as a tool to peek into how it is working, but finds it far too course of a tool both spatially and temporally to be of much use to explain what is going on at the synapse level and how that matches up with consciousness. She doesn't believe the artificial community will achieve the goal of a conscious robot; she believes that the brain with its 3d architecture and chemical nature would be too difficult to simulate correctly. She has co-edited a book Mindwaves: Thoughts on Intelligence, Identity, and Consciousness on the debate between scientists and philosophers on the topic, which would be good to add to my reading list.

Greenfield wants to see more women in science, and earn equivalent salaries. She laments the imposter syndrome that many women in science feel, and argues for a change of mindset to help women deal with confrontation and attain a sense of their own worth. Her prediction (in 1999) was that the human genome would certainly be mapped but fears that "a gene for a particular trait will be over-interpreted" when it comes to the human brain. She predicts brain imaging to become much more useful and accurate at mapping the brain's physical and mental states. She fears this, along with virtual reality, will be used to standardize individuals by 2084 in an Orwellian sense, but that we can still choose to create a world that values and celebrates the diversity of our individuality.

Agree: Our culture has not been set up to value diversity, and the pushes to do so over the last few decades have been recently met with equal and opposite reactionary forces to further define standards of religion, sexuality and culture within the United States. She states that time is running out; I am worried that it may have already. Disagree: she sees the brain structure as the only path to consciousness, a sense of self; I have already read the writings of GPT-3 that indicate a sense of self and purpose and consciousness, higher order reasoning and the ability to think about thinking. The successor to GPT-3 will undoubtedly possess what we would call consciousness without any brain chemicals or the 3D structure of the human brain; it is becoming increasingly apparent to me that the brain is one path to consciousness but when enough information is ordered in one place, consciousness will emerge.

Reviews: I am grateful for the variety of voices represented in this book, and I am glad I chose this book for this course. I've spent a career focused on my navel technically speaking; I need to spend some time in the heads of our contemporary scientists like Greenfield and Gould and this book is just a very brief introduction to them.